The Impact of the Entry of Biosimilars:
Evidence from Europe
Fiona M. Scott Morton
Ariel Dora Stern
Scott Stern
Working Paper 16-141
The Impact of the Entry of Biosimilars:
Evidence from Europe
Fiona M. Scott Morton
Yale School of Management
Ariel Dora Stern
Harvard Business School
Scott Stern
Massachusetts Institute of Technology
Working Paper 16-141
Copyright © 2016 by Fiona M. Scott Morton, Ariel Dora Stern, and Scott Stern
Working papers are in draft form. This working paper is distributed for purposes of comment and discussion only. It may
not be reproduced without permission of the copyright holder. Copies of working papers are available from the author.
THE IMPACT OF THE ENTRY OF BIOSIMILARS:
EVIDENCE FROM EUROPE
Fiona M. Scott Morton, Ariel Dora Stern, and Scott Stern*
January, 2017
Biologic drugs (therapeutic proteins or “large-molecule drugs”) represent a large and growing
share of all drug spending in the United States, accounting for less than 1% of prescriptions filled
but nearly 28% of drug spending. Whereas traditional (chemically-synthesized, “smallmolecule”) drugs have historically faced price competition from generic drugs after patent
expiration, biosimilars – biologic drugs that have been shown to be therapeutically equivalent to
an already approved original biologic drug – have only been approved in the United States since
2015. Europe has had biosimilar entry since 2006. This paper considers how competition from
biosimilars may impact the U.S. biosimilar market by examining data from the first eight years
of biosimilar competition in 23 European countries. A major contribution of this project is the
completion of a detailed survey, allowing us to precisely characterize European biologic drug
procurement institutions over time. Using data from three classes of biosimilar drugs, we analyze
how market features and public policies predict entry, market prices, and penetration of
biosimilars. We find significant heterogeneity across countries and drug classes in all of these
outcomes. While we observe that effective buyer institutions (in particular, committed tenders)
are associated with increased biosimilar entry and penetration, price patterns are more difficult to
glean from the available data. Our estimates can inform ongoing policy discussions on both sides
of the Atlantic about the economic implications of biosimilar policies.
*We are grateful to Ernie Berndt, Bill Comanor, Innessa Colaiacovo, James Leung, Robert Meyer, Andrew Mulcahy,
Stacy Springs, Robert Town, and seminar participants at Boston University, UCLA, the Kellogg Health Care Markets
Conference, Harvard Business School, Harvard Medical School, Tulane University, the University of Virginia, IFS, KU
Leuven, ASHEcon, and the Bates White Life Sciences Symposium for helpful suggestions. Several experts in and well
acquainted with the health ministries of European countries in our sample provided valuable information on domestic
drug procurement policies. Suzette Kox, Julie Maréchal, Pieter Dylst, and Maarten Van Baelen from Medicines for
Europe were particularly generous with their time. Prof. Fernando de Mora in the Department of Pharmacology,
Therapeutics and Toxicology at the Universitat Autònoma de Barcelona – Spain provided detailed scientific and
regulatory detail. Melissa Ouellet, Oliver Falvey, Lila Kelso, Brittany Ngo, and Kathrin Lampert provided excellent
research and editorial assistance. Funding from the National Science Foundation award number 1064341 (The Industrial
Organization of the Biologics Industry: Theory, Empirics and Policy) and the National Institute on Aging, through grant
number T32-AG000186 to the National Bureau of Economic Research, is gratefully acknowledged. We are particularly
appreciative of access to IMS data provided by Pfizer Inc. and IMS.
1.! INTRODUCTION
A central challenge facing health care policymakers is balancing the provision of innovation
incentives for private firms with access to medical innovation at a reasonable margin above the
cost of production. In the area of pharmaceuticals, this trade-off has largely been managed
through a policy regime in which there is regulation of entry during the time that a drug is
protected by patent-based intellectual property rights, followed by active encouragement of entry
and price competition after the expiration of the key patent underlying a pharmaceutical
innovation.
In the United States, this policy regime was realized through the bipartisan 1982 HatchWaxman Act, which provides innovator pharmaceutical firms with a longer period of guaranteed
exclusivity in exchange for the ability for generic drug manufacturers to subsequently enter
markets through an abbreviated regulatory process. Under Hatch-Waxman, generic entry
involves only the demonstration of “bioequivalence” between a generic candidate and the
reference product, once the period of exclusivity has passed and the active pharmaceutical
ingredient can be shown to be virtually identical (Grabowski and Vernon, 1986; Scott Morton,
1999). While this regime has involved policy challenges over time as the result of the strategic
interaction among pioneer and generic firms (see, for example, Scott Morton, 2000, or Bulow,
2004), there is a relatively consistent body of evidence that the Hatch-Waxman regime was
efficacious for the types of drugs that had been the mainstay of the pharmaceutical industry
1
through the 1990s, particularly once buyer institutions developed products that facilitated price
competition between branded and generic products once a patent had expired.1
However, whereas most new drugs prior to 1990 were “small molecule” compounds whose
chemical composition could be copied exactly by a generic manufacturer, a new class of drugs
began to appear starting in the 1980s: biologics, therapeutic proteins obtained from biologic
sources. Due to their biologic origin and complexity, these molecules are both impossible to
perfectly copy and far more expensive on a per-patient basis. A direct consequence of this
technological change has been the need to develop a policy regime that encourages entry after
patents on original biologics have expired, even though follow-on entrants will only be able to
demonstrate biosimilarity (i.e. a very high level of structural homology with no significant
changes of safety and efficacy) rather than an exact match between pioneer and generic drug’s
active molecular ingredient.
In the United States, the development of a regulatory approval pathway for biosimilars was
long delayed and only formally began with the passage of the Patient Protection and Affordable
Care Act of 2010 (the first approval of a US biosimilar only occurred in 2015).2,3 In contrast,
biosimilars have been regulated, approved, and sold in Europe for over a decade, a fact that
1
The U.S. Food and Drug Administration estimates that over the decade ending in 2012, generic drug use generated
more than $1.2 trillion in savings to the health care system (Hamburg, 2014).
2
Sandoz’s Zarxio, which is a biosimilar of Filgrastim, a drug for neutropenia was approved by the U.S. Food and
Drug Administration on March 6th, 2015.
3
Though not the primary focus of our analysis, the long delay in the development of a practical biosimilars
regulatory pathway may reflect a significant level of regulatory capture and influence, insofar as pioneer
manufacturers have significant incentives to delay the introduction of competition relative to the incentives of the
biosimilars manufacturers to engage in the development of rules that would create the potential for market
competition.
2
motivates the primary objective of this paper: examining the European experience with
biosimilars in order to inform policy design and institutional choices for the United States.4
Two key features of the European experience are particularly important in shaping our
analysis. First, at the time of the introduction of the first biosimilars in Europe, there was not
only uncertainty about how biosimilar competition might play out, but also scientific and
technological uncertainty as to whether biosimilar products would be able to be produced,
distributed, and developed in a way that would ensure a consistent level of safety and efficacy
for patients.5 Over time, however, these safety and efficacy concerns have largely been
alleviated: in Europe, there have not been any unexpected adverse events attributable to the use
of biosimilars over the period from 2006 to 2015.6 Moreover, existing evidence highlights that
the precise structure of any biologic drug may significantly vary when an original biologic
manufacturer makes slight changes to its own processes, such as when changing an in-process
manufacturing step, scaling-up production, adapting to local policies, renewing equipment, or in
the extreme, by opening up an entirely new manufacturing facility (Sarpatwari, Avorn, and
Kesselheim, 2015; Weise et. al., 2014). The development of a biosimilar medicine may lead to
similar variability. In both situations, comparability is a common approach that allows an indepth understanding of the scope and magnitude of the impact of such changes. Thus, while the
4
In so doing, we build on prior work that has examined the potential for biosimilars such as Grabowski et al (2006)
and Grabowski et al (2007), and papers that have examined the European experience with biosimilars (such as
Rovira et. al., (2011)) and Berndt, et al (2015). As we explain below, our work moves beyond these prior analyses
by undertaking a detailed empirical analysis of the role of buyer institutions in shaping differences in entry and
market impact (quantity, price) across different European countries, and thus grounding our understanding of how
alternative policy choices might result in different patterns of diffusion and impact in the United States.
5
Unavoidable, minor molecular differences between reference drugs and biosimilars (e.g. glycosylation patterns)
may increase immunogenic responses or reduce clinical efficiency in ways that are unpredictable.
6
Cutroneo et al (2014) “Safety Profile of Biological Medicines as Compared with Non-Biologicals: An Analysis of
Intial Spontaneous Reporting System Database” Drug Saf (2014) 37:961-970; Vermeer, Niels (2012) “Traceability
of biopharmaceuticals in spontaneous reporting systems” European Medicines Agency, presentation. Vermeer, Niels
et al (2013) “Traceability fo Biopharmaceuticals in Spontaneous Reporting Systems…” Drug Saf (2013) 36:617625. GABI “No relevant difference in ADRs from biosimilars and originators” posted 10/01/2015
3
precise rules governing the production of biosimilars in the United States are separate from those
in Europe, the resolution of scientific uncertainty over the past decade implies that the adoption
of biosimilars will be shaped by economic and institutional factors rather than as a result of
meaningful differences in health care outcomes arising from use of the original formulation
versus a biosimilar product.
Second, while the approval process for all biotechnology drugs7 occurs through the European
Commission (EC) based on the recommendations of the European Medicines Agency (EMA) –
the scientific and regulatory body that evaluates products sold in the European Union (EU) –
market entry occurs on a country-by-country basis. In other words, while testing and approval
decisions for biologics in European markets are mostly centralized, each country has its own
policies and procedures governing the procurement, prescription, and pricing of biosimilars. Not
simply a matter of institutional detail, these procurement and buyer institutions facilitate or
discourage the use of biosimilars and, in facilitating biosimilar entry, can also encourage price
competition after the introduction of biosimilars. For example, whereas some countries such as
Poland have used country-wide tender offers to encourage price competition, other countries
such as France have allowed biosimilars into their markets, but have taken fewer decisive
concrete steps to encourage their use. In other words, while clinical experience allows us to
abstract away from scientific differences between pioneer biologics and biosimilars, variation in
policy across European countries allows us to understand the role of buyer institutions in shaping
the realized gains in accessibility and cost savings that result from biosimilar entry.
7
All biotechnology drugs (whether original or biosimilar) must be approved through the EMA. Some (non-biotech)
biologics may use another regulatory pathway, but those products do not appear in this study, nor are they likely to
be relevant for future policy, most of which will apply to biotech products.
4
Some experts in the US predicted that the entry of biosimilars would lead to little health care
expenditure savings – either because biosimilars would not be close enough substitutes to their
reference counterparts to create significant price competition, or because the high fixed cost of
entering new biosimilar markets would reduce entry and, in turn, price competition (see, for
example, Grabowski et. al., 2007). Of course, this assertion is really an empirical question, and
we now have nine years of data from Europe to examine its veracity.
The remainder of this paper leverages this insight using data from 23 different national
markets that fall under the jurisdiction of the EMA’s regulation of biosimilars.8 We organize our
analysis into two broad sections. First, we examine country-level determinants of whether
biosimilars have become a significant fraction of biologic drug consumption. We then ask
whether and by how much prices have fallen following biosimilar entry in three different
markets. We document a set of facts about the entry of biosimilars in Europe from 2007 through
2014, representing eight of the first nine calendar years of biosimilar availability. We have the
ability to study the first three classes of biosimilars that were approved in Europe in this time
period: Epoetin, Filgrastim, and Somatropin biosimilars (discussed in detail below). The number
of countries ever experiencing biosimilar entry in our data is substantial: in the 23 countries for
which we have data, each of these 3 classes of biosimilar products is sold in at least 19 markets.
Our key finding from this descriptive analysis is that there has been significant and striking
variation in the take-up of biosimilars across otherwise similar countries. For a given drug, the
rate of biosimilar penetration (relative to a country’s initial sales of biologic reference product)
can vary by an order of magnitude.
8
With respect to biosimilar approvals, the EMA’s polices also apply to Australia, as described below.
5
We then turn to the second part of our empirical analysis, in which we begin to evaluate
the reasons for these differences. To do so, we draw on an original survey that allows us to
precisely characterize biologic drug procurement policies over time for the major countries
covered by the EC’s approval decisions (which in turn are based on recommendations by the
EMA Scientific Committee, CHMP). Our detailed policy survey confirms the great extent to
which policies on procurement and pricing of biosimilars vary greatly across countries, and, in
some cases, within countries over time. We show that the existence and identity of the residual
claimant in the procurement process – namely the party who saves money when the biosimilar is
dispensed – is critical to understanding the penetration of biosimilars and cost savings from their
use. Our analysis documents a number of important and novel findings. First, our analysis of the
European experience shows that biosimilar competition can generate cost savings. Our results
primarily show that uptake of biosimilars in Europe has been gradual but significant, while price
declines have also been significant. The effects are strongest in the Epoetin and Filgrastim
markets, which have the highest number of entrants and the highest revenues. Larger markets
and markets with stronger tendering programs attract more entry. Specific results on prices are
weaker, perhaps due to measurement error in the data.
We find that the average price of biologics in a given class has been falling over time
since the first biosimilar approval, with particularly strong declines observed in Epoetin and
Filgrastim markets over the period studied. For these two product classes, we also find evidence
to suggest that savings are higher (i.e. prevailing market prices are lower) in countries with a
greater number of non-procurement policies to encourage biosimilar use. Penetration of all three
classes of biosimilars increases over time, and we see evidence that tendering and other
incentives can increase penetration in particular classes. We find some evidence that prices in the
6
largest and most populous market, Epoetin, are responsive to the nature of the tendering process;
when a country runs a winner-take-all tendering scheme, the price of the drug is lower than in
countries where tendering is not present, or is done in a way that does not guarantee the winner
all demand. The jurisdictions with a strong Epoetin tendering process (as defined below) also
have higher penetration of biosimilars.
The remainder of this paper proceeds as follows: Section 2 provides background on biologics
–both original and biosimilars—and institutions in Europe, Australia, and the United States.
Section 3 presents a conceptual framework for biosimilar entry and additional context. Section 4
presents the data and calculations used in the graphs and empirical estimation found in Section 5.
Section 6 concludes with discussions for policy.
2.! BACKGROUND
2.1 BIOLOGICS
Biologics, also called biopharmaceuticals or biologic drugs, are a broad class of products
including blood-derivatives, vaccines, somatic cells, gene therapies, and recombinant therapeutic
proteins. Biologics obtained through engineering of the biological source are called biotech
drugs. The FDA notes that drugs classified as biologics may be composed of molecular
structures ranging from sugars to proteins to nucleic acids – or a combination of these substances
– and may also include living cells or tissues9. Biologics are usually derived from or produced by
mammalian cells or microorganisms and typically require expensive, technology-intensive
manufacture through biological processes. Biologics are widely used to treat serious and life-
9
http://www.fda.gov/AboutFDA/CentersOffices/OfficeofMedicalProductsandTobacco/CBER/ucm133077.htm
7
threatening diseases such as cancer, diabetes and rheumatoid arthritis. According to the FDA:
“biological products often represent the cutting-edge of biomedical research and, in time, may
offer the most effective means to treat a variety of medical illnesses and conditions that presently
have no other treatments available.”1
Structurally, biologics are large, complex, and heterogeneous proteins with molecular
weights ranging from 6,000 to 150,000 Daltons (in the case of monoclonal antibodies). By
contrast, chemically synthesized (“small molecule”) drugs typically have molecular masses of
just a few hundred Daltons. Unlike chemical drugs, which have a known molecular structure,
most biologic drugs are so large and complex that they are difficult to completely characterize
molecularly. Moreover, the active substance in a biologic – whether original or biosimilar – is
typically a collection of large protein isoforms, with some heterogeneity, and is not a single
molecular entity. In part, this results from their production in bioreactors by biologic systems.
These facts make the characterization and manufacturing of biologics of all kinds much more
challenging than understanding and producing traditional small molecule drugs.
Biologics represent a large and growing share of global pharmaceutical spending;
worldwide revenue from biologic drugs quadrupled from US$46 billion in 2002 to over US$200
billion in 2013. Biologics are thought to be different economically from small molecule drugs for
a number of important reasons, including their (typically) small market size10 and high unit
prices, and high rate of growth in utilization. The prices of these drugs are typically high due to a
combination of factors including high manufacturing costs and disease severity (and as a result
inelastic or less elastic demand). The ability to charge high prices for treatments for serious
diseases allows innovators to earn a return on R&D spending even in smaller markets.
10
Some biologics are used for rare diseases, which have particularly small markets, but the sales for these diseases
only represent a small share of the total market for biologics.
8
Further, high prices may reflect limited competition; many biologic drugs that act on a
specific target have no (small molecule or other) counterpart from a pharmacological point of
view and therefore do not face price competition from (even weak) substitutes. For this reason,
policy concerning the entry and procurement of biosimilars is important. Although biologic
drugs account for less than 1% of all U.S. prescriptions dispensed, their sales amount to roughly
28% of all prescription drug spending, with both use and cost expected to grow over the coming
years (Sarpatwari, Avorn, and Kesselheim, 2015).
2.2 Biologics development and the market for biologics
The R&D process for new biological entities (NBEs) has several special characteristics.
NBEs often originate in venture capital-financed startups which themselves face significant
uncertainty. Additional sources of risk in the clinical trial process include formulation or dosing
of biologic drugs. The manufacturing, development, and scale-up challenges for commercial
supply are significant. Developing robust manufacturing capabilities and process specifications
is difficult because small details of bioprocessing can impact clinical attributes in unpredictable
ways. Changes in the medium, temperature, timing, and the materials out of which a piece of
equipment is made can all affect the nature of the final medication, making the manufacturing
process highly sensitive and complex, requiring more extensive in-process controls.
As with small molecule drugs, development times for new biologic therapies are quite
long – typically over a decade – and the combined costs of development activities are high.
Overall, biologic drug development costs are likely comparable in magnitude to estimates of the
9
cost of developing new chemical drugs,11 but the largest cost components are somewhat
different: on average, biologic drug development is characterized by (on average) higher
discovery and preclinical expenditures, longer average pre-clinical trial development times, and
higher costs associated with process engineering and manufacturing, but shorter subsequent
clinical trial times (Grabowski, 2008; Grabowski et. al., 2006).
Distribution systems for biologics and chemical drugs also differ dramatically: while
most chemical drugs are oral agents and can be distributed through retail and mail-order
pharmacies, biologics are often injectable products, which are typically administered by a health
care provider in a hospital, a clinic, or a physician’s office.12
Biologics represent the fastest growing segment of the pharmaceutical market: in recent
years, biologic growth has been nearly double that of total pharmaceutical growth (GaBI, 2012).
In 2015, eight of the top 20 drugs in the United States by revenue were biologics (IMS, 2016), up
from seven of the top 20 in 2010 (Lancet, 2012). This is in part because a typical biologic course
of treatment can be very expensive. An example is Lumizyme (alglucosidase alfa), an orphan
drug for the treatment of Pompe Disease, which is known to cost about $100,000 per year for
children and $300,000 per year for adult treatments.
11
DiMasi and Grabowski (2007) look at R&D costs for a sample of recombinant proteins and monoclonal antibodies
and confirm that some phases of the development process (e.g. manufacturing) are more costly, but that “estimated
total capitalized cost per approved new molecule was nearly the same for biopharmaceuticals as [chemical drugs].”
12
However, a few self-injectable products, including insulin and some growth hormones, may also be dispensed
through pharmacies. Specific policies vary from country to country and product to product: for example in Spain,
growth hormone is dispensed in hospital pharmacies, but insulin and Interferon-alpha are dispensed in retail
pharmacies.
10
2.3 BIOSIMILARS
High and rapidly growing expenditures on biologics is one reason that many health
systems are interested in utilizing biosimilars. By the end of 2016, worldwide sales of biosimilars
are expected to have reached between US$1.9 and $2.6 billion, as compared to $378 million in
the year leading up to mid-2011 (IMS Health, 2011; Rickwood and Di Biase, 2013). Some
estimates for the global biosimilar market predict that sales will reach nearly 4 billion by 2019, at
a CAGR of roughly 15% for the years 2014-2019 (Dewan, 2015).
Biosimilars differ from generics in terms of their physical characteristics as well as in
how they are regulated. Development of generic versions of chemically manufactured small
molecule drugs are based on pharmaceutical equivalence and bioequivalence.13 Whether two
chemically synthesized medicines are the same can be determined with precision using standard
chemistry assessments. Generic drugs can then be used in the same dose to treat the same disease
with equal expected efficacy. As a result, all states allow a pharmacist to move a patient from the
brand to an A/B rated generic – or between different generics – without permission from the
physician. This is feasible and there is little risk associated with this type of substitution, because
the active substance is identical and the treatment regimen is the same.
Biologics, on the other hand, have a unique set of features. The two primary
distinguishing features of biologics are their product heterogeneity and lower stability, leading to
the co-existence of multiple iso-forms of the same molecule with potentially different profiles.
13
When developing a generic, a firm can both synthesize the same chemical compound and carry out analytical
studies to confirm its molecular identity. Once this has been demonstrated, a bioequivalence study in humans is
sufficient to prove therapeutic equivalence. This is achieved through a comparative bioavailability
(pharmacokinetic) study that shows that the rate and extent to which an active substance is circulated is equivalent in
both drugs. Once established, it can be assumed on scientific grounds that both the original and generic candidate
products will share the same safety and effectiveness profile.
11
Thus, although the characterization techniques now available for proteins have improved to the
point that they can be fully characterized, some variability always remains. As such, biosimilars
are developed to match the variability of the reference biologic and the structural attributes, with
biological functions and human pharmacokinetics and pharmacodynamics that are highly similar.
Nevertheless, biosimilars face greater difficulty in establishing how much fidelity a copy of a
biologic molecule has to a reference product (original), leading to the common distinction
between biosimilars vs. chemically-synthesized generics. Indeed, because there is heterogeneity
associated with biologics – including added sugar groups in many cases (glycosylation) – it is
impossible to fully match the reference product. This is even a challenge among batches of the
originator’s product, but is most challenging when the details of the original bioprocess are not
available to the biosimilar developer. Follow-on products, such as biologically manufactured
recombinant proteins, are therefore approved based only on various methods of establishing a
high similarity standard vis-à-vis a reference product, rather than proof of identical molecular
structure (Manheim et. al. 2006).
Passed as part of the Patient Protection and Affordable Care Act (ACA) of 2010, the
Biologics Price Competition and Innovation Act (BPCIA) of 2009 instructed the U.S. Food and
Drug Administration (FDA) to create a pathway for approval of biosimilars “based on evidence
of structural similarity” with more customized confirmatory clinical trials than those typically
required for the approval of new drugs (Sarpatwari, Avorn, and Kesselheim, 2015). There are
two possible classifications of biosimilars: “substitutable” and “interchangeable.” A patient’s
physician must switch her from the brand to a substitutable biosimilar or between substitutable
biosimilars. By contrast, a pharmacist may switch a patient from the brand to an interchangeable
biosimilar without the physician’s permission.
12
Further, until the 2015 publication of three key pieces of regulatory guidance by the U.S.
Food and Drug Administration (FDA), there was significant uncertainty regarding the scientific
and quality considerations that U.S. regulators would take into account in reviewing biosimilar
dossiers for approval. 14 Relatedly, the FDA has not yet released regulatory guidance to clarify
the type and level of evidence required for interchangeability of biosimilars and reference
biologics, creating further market uncertainty for potential entrants into biosimilar drug markets.
2.4 Data exclusivity and regulatory issues
Definitions
When a government or regulatory agency gives a firm marketing exclusivity, it prohibits
other producers of the same drug from selling their product in the protected market. Marketing
exclusivity is distinct from patent protection, which is part of the legal system and enforced by
the courts. Data exclusivity is separate and refers to the ability of the regulator to refuse to allow
another manufacturer to reference the original applicant’s data in a different application. The first
applicant might have shown that its medication cures cancer, for example. A subsequent
applicant would want to reference that data to show the efficacy of its follow-on medication, but
legal restrictions may prohibit the regulator from considering such data if it is still protected by
data exclusivity. An entrant can still generate its own efficacy data, but that would often come at
the cost of running a full development program and would result in the entrant having similar
fixed costs to the original innovator. Part of the goal of allowing follow-on products, such as
14
While draft guidance was published in 2012, it was understood at the time that it would take several years for final
regulatory guidance to be published.
13
chemical generics, to enter markets is to lower the fixed cost of entry and thereby increase the
number of entrants and lower the price of the drug.
Throughout this paper, we apply the following definitions:
•! a class of drugs denotes a set of products with the same active substance that are used for
the same indications in the same patients. Drugs in the same class are typically very good
to excellent substitutes for one another and therefore competitors. The three classes15 of
drugs we consider are Epoetin, Filgrastim, and Somatropin.
•! a product entrant as the party that organizes and is granted marketing authorization from
the EC for a biologic drug (reference product or biosimilar). In EMA documents, the
entrant is referred to as the “marketing authorisation holder.”
There are multiple actors in biosimilar manufacturing tracked by the EMA. Further, sales data
identifies the companies responsible for distribution. We define the following:
•! the manufacturer of the biological active substance is the firm that is authorized by the
EMA to produce the active biologic molecules in a product.
•! the manufacturer of the biologic product is the firm that puts the biological active
substance into a dosage strength, form, and packaging. This is often the entrant or the
manufacturer of the biological active substance, but not always
•! the distributor is the name of the firm selling a drug in a given country.
EUROPE
The European Medicines Agency (EMA) is responsible for regulating biologics and other
drugs and evaluating applications for the European Economic Area (EEA).16 Chemically-
15
We use EMA definitions for all biosimilars. EMA-approved biosimilars are almost always defined as such in the
IMS data used. The primary exception to this is the biologic Grassalva, which is classified by IMS as a Filgrastim
biosimilar. Although it is recognized to include the same active ingredient as Tevagrastim (a biosimilar approved in
2009), Grassalva is a distinct product and was never approved by the EMA as a biosimilar.
16
The EMA’s process results in a single marketing authorization that is valid in all European Union (EU) countries
as well as in the EEA countries Iceland, Lichtenstein, and Norway.
14
synthesized generics are usually approved by individual country regulators. However,
biotechnology-derived medicines, whether original or biosimilar, must be approved through the
centralized process of the EMA. Europe provides data exclusivity under the “8+2+1” regime on
all products submitted for approval on or after October 30th, 2005. Under this regime, both new
chemical entities (NCEs) and new biologic entities (NBEs) are granted ten years of market
exclusivity (eight years of data exclusivity plus two years of additional marketing exclusivity).
An additional year of marketing exclusivity is provided if, “during the first eight years of those
ten years, the marketing authorization holder obtains an authorization for one or more new
therapeutic indications which, during the scientific evaluation prior to their authorization, are
held to bring a significant clinical benefit in comparison with existing therapies.”17
The EMA is responsible for regulating the manufacturing of biologics as well as
evaluating the scientific studies required to assess comparability of biosimilar candidates to their
reference products. The EMA defines a biosimilar as follows:
A similar biological or 'biosimilar' medicine is a biological medicine that is similar to
another biological medicine that has already been authorised for use. Biological
medicines are medicines that are made by or derived from a biological source, such as a
bacterium or yeast. They can consist of relatively small molecules such as human insulin
or erythropoietin, or complex molecules such as monoclonal antibodies.
In the case of biosimilars, products must meet higher approval requirements than those of
generic small-molecule drugs. These include quality, comparability, and showings from head-tohead pre-clinical and clinical studies to demonstrate comparable safety and effectiveness.
Guidelines concerning the nature of scientific data that may be used to substantiate a claim of
17
Directive 2001/83/ec, ammended
15
“similarity” are issued by the EMA’s Committee for Medicinal Products for Human Use
(CHMP).
Complicating matters further is the fact that depending on the structural and functional
complexity, the therapeutic indications, and the regimen of the biologic serving as the reference
medicine, requirements may vary for proving product comparability and subsequent safety and
efficacy. Such issues are not relevant for small molecule drugs and as a result, such tailored
regulatory measures are not necessary in small molecule generic drug approval, which simply
requires having an identical active substance in the same quantity/dose and demonstrating
bioequivalence (i.e. the same rate and extent of absorption of active substance) in both products.
The specific requirements for a biosimilar Marketing Approval Application (MAA)
dossier are articulated in Annex I to Directive 2001/83/EC and must satisfy the technical
requirements of the monographs of the European Pharmacopoeia and any additional
requirements (e.g. those defined in relevant CHMP guidelines). Appendix Table VII lists the
legal requirements for a new biosimilar application to the EMA.
The European Commission defines two terms:18
1)!
interchangeability: the medical practice of changing one medicine for another that is
expected to achieve the same clinical effect in a given clinical setting and in any
patient on the initiative, or with the agreement of the prescriber.
2)!
substitution: the practice of dispensing one medicine instead of another equivalent and
interchangeable medicine at the pharmacy level without consulting the prescriber. A
pharmacist can substitute a biosimilar at the time the product is dispensed without
consulting the physician.
18
http://ec.europa.eu/DocsRoom/documents/8242
16
Importantly, the United States uses the same two terms, but gives them opposite
definitions, with “interchangeability” indicating the ability for pharmacist substitution.19
Many European countries have expressed opposition to substitution by pharmacists. For
example, Spain maintains a no-substitution policy for all biologics – i.e. even among two
original products bearing the same product name such as different insulins. This, of course,
serves as a ban to the dispensing of a different biologic drug than the one prescribed by the
physician. In our data, pharmacy substitution was only flagged as being allowed in one countryyear (France in 2014), but it was not actually done in practice, given previous laws complicating
the question of whether it was actually permitted.20
There are three classes of molecules that experienced significant biosimilar entry in
Europe during our period of observation (2007-2014): 1) Epoetin, which stimulates red blood
cell production in the body, 2) Filgrastim, which stimulates the bone marrow to produce blood
cells (used after chemotherapy), and 3) Somatropin, a human growth hormone. 21
There are slightly different versions, or generations, of Epoetin on the market in Europe:
original biologics exist for both Epoetin Alpha and Epoetin Beta. Notably, only biosimilars to
Epoetin Alpha have been developed; there are no biosimilars to Epoetin Beta. The biologic
Epoetin Zeta only exists in biosimilar form and takes Epoetin Alpha as its reference product. We
19
The FDA defines an “interchangeable biological product” as one that is “biosimilar to an FDA-approved reference
product and meets additional standards for interchangeability. An interchangeable biological product may be
substituted for the reference product by a pharmacist without the intervention of the health care provider who
prescribed the reference product.”
(http://www.fda.gov/Drugs/DevelopmentApprovalProcess/HowDrugsareDevelopedandApproved/ApprovalApplicat
ions/TherapeuticBiologicApplications/Biosimilars/)
20
France adopted a law regarding substitution of biosimilars for naïve patients, however the law did not have an
implementing decree and therefore did not come into force during the period studied here. The French Agency
updated their position in May of 2016 to allow for interchangeability under conditions of patient transparency,
monitoring, and traceability of biosimilars.
21
Infliximab biosimilars began to be approved in 2014, but the original biologic’s patent did not expire until 2015 in
most European countries.
17
consider the Alpha and Zeta forms of Epoetin as one combined class in our analysis, since they
are approved by the EMA for the same set of indications and used interchangeably in a medical
setting.22
AUSTRALIA
Australia also has a regulatory pathway for biosimilar entry, and data from Australia are
included in many of the analyses below. Australian biosimilars are regulated by the Department
of Health's Therapeutic Goods Administration (TGA), which borrows much of its regulatory
policy from EU guidelines.
As in the EU, the TGA defines a biosimilar or similar biological medicinal product
(SBMP23) as a version of an already registered biological medicine that a) has a demonstrable
similarity in physicochemical, biological and immunological characteristics, efficacy and safety,
based on comprehensive comparability studies and b) has been evaluated by the TGA according
to this guideline and other relevant EU guidelines adopted by the TGA.24
The Australian data requirements for the approval of biosimilars are based almost entirely
on those outlined in EU guidelines as well as an International Conference on Harmonisation of
Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) guideline on
the assessment of comparability. Additionally, the TGA requires the submission of a limited
22
In robustness checks, we also consider the impact of each product’s introduction separately.
Although referred to as biosimilars in Australia, the term `similar biological medicinal products' (SBMPs) is
derived from the EU guidelines adopted by the TGA. The terms may be used interchangeably. In other jurisdictions,
they also are variously referred to as: similar biotherapeutic products (WHO), follow-on biologics, and subsequent
entry biologics.
24
http://www.tga.gov.au/industry/pm-argpm-biosimilars-00.htm
23
18
number of Australia-specific administrative documents.25 A full list of EU guidelines that have
been adopted by the TGA for the approval of biosimilars can be found below,26 but for all intents
and purposes, policies and standards that govern the approval of biosimilars in Australia are the
same as those employed in the European Union and EMA decisions are adopted directly. Hence
we include Australia in our empirical work.27
THE UNITED STATES
At present, most biologic therapies available in the United States are regulated through
the Public Health Service Act, which does not have a provision for “follow-on” versions of
biologics (biosimilars). That is, there is no analog to generic chemical drugs as provided for
under the Hatch-Waxman Act, which grants a 5 - 7.5 year data exclusivity period for NCEs.
With the exception of some early biologics such as human growth hormone (hGH), insulin, and
conjugated estrogens, which were approved as original drugs under the federal Food, Drug, and
Cosmetic Act (FD&C Act), biologics in the United States are regulated separately from chemical
drugs by the FDA. Biologics are regulated by the Center for Biologics Evaluation and Research
25
These include a Pre-Submission Planning Form (PPF), information for sponsors completing the PPF, mandatory
requirements for an effective application, general submission dossier requirements, and a risk management plan
guideline.
26
Additional cites: adopted docs: CHMP/437/04: Guideline on similar biological medicinal products;
EMEA/CHMP/BWP/49348/2005: Guideline on similar biological medicinal products containing BiotechnologyDerived Proteins as Active Substance: Quality Issues; CPMP/ICH/5721/03 ICH Topic Q 5 E: Comparability of
Biotechnological/Biological Products Note for Guidance on Biotechnological/Biological Products Subject to
Changes in their Manufacturing Process; EMEA/CHMP/BMWP/42832/2005: Guideline on similar biological
medicinal products Containing Biotechnology-Derived Proteins as Active Substances: Non-Clinical and Clinical
Issues; CHMP/BMWP/101695/2006: Guideline on Comparability of Biotechnology-Derived Medicinal Products
after a change in the Manufacturing Process - Non-Clinical and Clinical Issues; EMEA/CHMP/BMWP/14327/2006:
Guideline on Immunogenicity Assessment of Biotechnology-Derived Therapeutic Proteins; Product-specific
guidelines detailing the clinical and safety data requirements. (http://www.tga.gov.au/industry/pm-euguidelinesadopted-clinical.htm)
27
However all empirical results presented below are robust to excluding Australia from the sample.
19
(CBER), while small molecule drugs are regulated by the Center for Drug Evaluation and
Research (CDER).
In April of 2015, the FDA released final regulatory guidance on several, but not all
aspects of the biosimilar approval process. The three final guidance documents issued address 1)
“Scientific Considerations in Demonstrating Biosimilarity to a Reference Product”; 2) “Quality
Considerations in Demonstrating Biosimilarity of a Therapeutic Protein Product to a Reference
Product”; and 3) “Questions and Answers Regarding Implementation of the Biologics Price
Competition and Innovation Act of 2009.”28, 29, 30 The first of these documents, which is the most
important of the three “is intended to assist sponsors in demonstrating that a proposed therapeutic
protein product…is biosimilar to a reference product for purposes of the submission of a
marketing application” (FDA, 2015). Importantly, the FDA has not yet released regulatory
guidance to clarify the type and level of evidence required for interchangeability of biosimilars
and reference biologics, which the FDA will release in a future guidance document. The FDA
approved the first biosimilar application in March 2015, Sandoz’s Zarxio (Filgrastim),31 and the
second biosimilar application in April of 2016, Inflectra (Infliximab).32 Zarxio was marketed
beginning in March 2015 at a launch price 15% below the reference biologic Neupogen.
On February 4 of 2016, the Director of the Center for Drug Evaluation and Research
(CDER) testified that “59 proposed biosimilar products to 18 different reference products were
enrolled in the Biosimilar Product Development Program.”33 Enrolling in this program appears to
28
http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM291128.pdf
http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM291134.pdf
30
http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM444661.pdf
31
http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm436648.htm
32
http://www.fda.gov/NewsEvents/Newsroom/PressAnnouncements/ucm494227.htm
33
Testimony by Dr. Woodcock before the House Committee on Energy and Commerce, subcommittee on Health,
February 4, 2016.
29
20
both indicate interest in launching a product and also allows the applicant to meet with CDER,
which Dr. Woodcock testified was happening with great frequency. She also said that as of
December 31st 2015 five companies had publicly announced eight biosimilar applications. At the
time of writing, only four biosimilar products34 had actually been approved by the FD and only
one of those, Sandoz’s Zarxio had been launched.
2.5 POLICY CONSIDERATIONS
Often referred to as “the Hatch-Waxman Act,” the Drug Price Competition and Patent
Term Restoration Act of 1984 (Hatch-Waxman) was landmark in establishing the Abbreviated
New Drug Application (ADNA) process for generic drug approvals in the United States. With
the generic drugs market now accounting for over 80% of US prescriptions, and very low US
generic prices, it is clear that Hatch-Waxman has been successful in both encouraging generic
entry and slowing overall drug expenditure growth. This successful US experience has framed
the policy-making, academic, and business mindset around follow-on medicinal products. Much
of the recent academic and policy literature related to biosimilars focuses on the question of the
extent to which biosimilars will be treated like, or have competition effects similar to, those seen
in small-molecule generics. These questions cover regulation, production, pricing, health care
policy, marketing and competition, but are still speculative, given that the US does not yet have a
meaningful market for biosimilar products.
An early wave of analysis of biosimilars considered the question of exclusivity length
(see, e.g. Grabowski, 2008). This research is often cited by biologic innovators, who are most
The four FDA-approved biosimilars as of January, 2017 were: 1) Zarxio, biosimilar to Neupogen, approved in March,
2015; 2) Inectra, biosimilar to Remicade, approved in April, 2016; 3) Erlezi, biosimilar to Enbrel, approved in August,
2016; and 4) Amjevita biosimilar to Humira, approved in September, 2016.
34
21
likely to benefit from a lengthy exclusivity period enforced by the FDA. A related early wave of
work warned that price competition would be less vigorous than in the small-molecule generic
context because the biosimilar would not be identical to the originator, but rather a differentiated
product (see, e.g., Grabowski et. al, 2006). This is surely true due to the economics of biologic
drug production described above, but the implied policy response – namely, that society should
therefore be less concerned about stimulating entry of biosimilars – does not follow in our view.
Smaller percentage savings, but savings that are significant in absolute size, are likely to be
valuable to health systems, patients, and those paying for health care.
In this paper we extend the literature to the next logical policy question: how can buyers
best stimulate price competition when biosimilars enter the market? There are different
procurement approaches, different regulatory environments, and different tools available to
buyers that may affect their ability to obtain lower prices on the purchase of biologic
medications. This paper considers the European and Australian experience in detail and presents
findings from the introduction of biosimilars on subsequent entry, prices, and penetration of
biosimilar products. We assemble a novel policy data set to categorize variation in country-level
institutions in order to understand the role of various procurement and non-procurement
(demand-side) biosimilar policies in Europe, and discuss policy implications for the United
States.
One such U.S. implication concerns the naming convention used for biosimilars. The current
(at the time of writing) regulation is explicitly temporary. It requires all biologic products to
attach a four-letter suffix to the scientific name of the drug, e.g. “Somatropin-abcd.” This suffix
is intended to indicate the firm selling the product, for example, the first FDA approved
biosimilar, Sandoz’s Zarxio, has been required to use the active ingredient name “Filgrastim-
22
sndz.” This labeling convention serves no safety purpose at the time of administration; rather, it
is intended to be used to identify the manufacturer in post-marketing surveillance. However,
details on the manufacturing facility and batch – which are likely the detailed information that
would be most relevant for investigating product safety concerns – are not included in the
product name. This means that in any case, regulators would still need to go back to detailed
records of a medication’s administration and dispensing in order to investigate the source of any
reported adverse events.
The Federal Trade Commission has formally objected to use of a suffix, noting that its use
“could result in physicians incorrectly believing that biosimilars’ drug substances differ in
clinically meaningful ways from their reference biologics’ drug substances, especially since
differences in drug substance names have traditionally connoted meaningful differences in drug
substances” (FTC, 2015).35 The Institute of Medicine has previously advocated for the
standardization of naming in accordance with the U.S. Pharmacopeial Convention (USP), noting
that drug-naming terminology “should be standardized to the extent possible to improve safety
and minimize misinterpretation” (Wolcott et. al., 2007). The USP has itself also recently
objected to the use of a suffix, pointing out that there is already a scientifically-based existing
non-proprietary naming system that has worked for over a century and that the use of suffixes in
naming biosimilars could have unintended consequences (USP, 2015).36 PhRMA
(Pharmaceutical Research and Manufacturers of America), the brand trade association, is in
favor of this suffix convention, and has even advocated for additional labeling differences.37
Notably, this differs from policies for naming conventions for different innovator products using
35
https://www.ftc.gov/system/files/documents/advocacy_documents/ftc-staff-comment-submitted-food-drugadministration-response-fdas-request-comments-its-guidance/151028fdabiosimilar.pdf
36
http://www.usp.org/sites/default/files/usp_pdf/EN/AudienceBio/usp-bio-naming-comment.pdf
37
http://phrma.org/sites/default/files/pdf/biosimilars-101-naming.pdf
23
the same active pharmaceutical ingredient (API). For example, Rebif and Avonex, two original
non-comparable medicines for Multiple Sclerosis, have been on the market for years with the
same API, “Interferon beta 1a.”
This stance is unsurprising because the additional letters included in the suffix has the
potential to create confusion among prescribers, and to create friction in drug lists and
formularies, where pharmacists can no longer sort prescriptions on the product’s non-proprietary
name and see all the biosimilars and their reference products adjacent to one other. This creates
greater switching frictions for pharmacists and greater perceived product differentiation among
buyers and providers. In Europe, by contrast, biosimilars use the same active ingredient name as
their reference product, which likely makes the level of competition we see in the European data
stronger than it will be in the US, if the naming convention is not improved.
3.! CONCEPTUAL FRAMEWORK
After the regulator (in this study, the EMA) opens the (European) market to biosimilars, a
biosimilar distributor must make a decision over choice of market and whether or not to enter.
There is an established literature in the economics of industrial organization that considers such
entry decisions. We will draw conceptually on two types of models as the framework for our
empirical analysis. First, we call upon models from the classic market entry literature such as
Bresnahan and Reiss (1991) and Berry (1992). These emphasize that entry will occur in the case
of an anticipated positive-profit project. Therefore, the market must be large enough to
accommodate the entrant at a competitive scale. This concept has been operationalized in a
pharmaceutical context by Scott Morton (1999), looking at the entry of generic drugs in the
United States. Entry is more likely in larger markets, and is more likely when the characteristics
24
of the entry opportunity match the capability of the entrant. For example, a firm specializing in
injectable drugs will be more likely to enter an injectable drug market than a market for pills.
Likewise, a firm with significant sales in drugs for cardiovascular diseases will be more likely to
enter a new cardiovascular drug market. We see some related patterns in biosimilars: firms with
established distribution channels and manufacturing expertise for biologic drugs are entering
biosimilar markets.38
The entry of biosimilars into a market will have different effects than that of smallmolecule generics because of their cost structure and level of differentiation. Graboswki, et. al.
(2006) and Grabowski et. al. (2007) lay out these issues. They point out that higher
manufacturing barriers to entry, limited acceptance, and U.S. regulatory conservatism will mean
that adoption of biosimilars is slow, and that their presence will not lead to the same price
decreases as those observed among chemical generics. Further, similarity rather than
substitutability means that consumers will not respond as elastically to price differences.
A small number of researchers have already considered biosimilar entry. Noting that a) large
markets are more likely to have more entrants and that b) firms consider fixed costs, variable
costs, and market size in market entry decisions, Grabowski et. al. (2007) construct a model of
monopolistic competition, in which the ratio of generic price to pre-entry monopoly price is the
key dependent variable. The authors then estimate market entry and prices in the biosimilar
market using estimates from generic small-molecule pharmaceuticals. In keeping with previous
studies, they estimate that the number of generic pharmaceutical manufacturers will be
38
Kyle (2007) studies the timing and the launch of new drugs, given differences in price controls across countries.
She finds that price controls have an important effect on pharmaceutical launches and that drugs invented by firms
based in countries with price controls reach fewer markets. We note that this phenomenon is unlikely to be a
concern in our setting, where we are looking at the entry of less expensive substitutes into already-established
markets.
25
increasing in total market size and decreasing with restrictions on product use and that generic
price will be closer to the branded product's price when there are fewer entrants. Further, the
authors note that the production of follow-on biologics will have substantially higher fixed costs
than those of generic chemical drugs due to required clinical testing, higher capital needs, and a
costlier manufacturing processes. As such, they estimate that there will be less entry than has
been observed historically in small molecule drug markets, and as a result, that the potential for
price-reduction will be less than that typically observed in generic drug markets. Importantly,
Grabowski et. al.’s (2007) paper does not use actual biosimilar data, but rather data from other
small molecule drug markets.
Consider the following simple market structure: one biologic firm that produces a
reference product (firm 1) faces post-patent entry from a biosimilar firm (firm 2). The biosimilar
firm faces unit production cost c and will enter the market when expected profits are positive. In
a single period model, with differentiated Bertrand competition, firm 2 thus considers its
expected profits from market entry as:
!"# = %" − ' ( %) , %" , +# − ,# ---------------- 1
where +# indexes the nature of price competition in country i and ,# summarizes the fixed cost of
entry. In this model, how a national health system procures a biosimilar,-+# , is a policy choice of
regulators. Notably, F may also be affected by regulators and/or policy makers, but not the fixed
cost of getting a molecule approved, which has already happened (in our setting, at the EMA
level) prior to the decision that a biosimilars firm makes about entering a given country’s market.
Rovira et. al., (2011) present early data on European biosimilar entry. The European
experience with biosimilars suggests that the market penetration of biologics is indeed lower
than what one would expect from generic drugs. Rovira et. al. (2011) estimate that biosimilars’
26
market value grew from 33 million Euros in 2007 to 65 million Euros in 2009, which
corresponded to an increase in market penetration of biosimilars from 0.34% to 6.64%. The
authors find that following biosimilar introductions, biosimilar prices, on average, were between
10% and 35% lower than their respective reference products.39
IMS Health calculated that in 2011, Europe comprised 80% of the world’s spending on
biosimilars (IMS Health, 2011), but this is based on just a few years of observations of on
biosimilar competition in Europe. Our study uses a consistent source of country-level price and
quantity data on all biologic drugs (both reference products and biosimilars) to take a more
comprehensive look at the European experience with the introduction of biosimilars.
The second set of concepts we use in this paper are models of procurement and
associated policy incentives. We focus the motivation of our framework here on the case of
hospitals’ use of biologic drugs, as that is an important setting for the three categories of
biosimilar drugs that were introduced in Europe during our period of observation. Health care in
Europe is public in either its provision or funding. The buyer of biosimilars, typically the
hospital, is thus almost always a non-profit regulated firm. The regulation literature examines the
motivation of the regulated entity to purchase the lower cost input. An important distinction is
between cost-plus regulation and fixed-price. In a cost-plus setting, the hospital (or other
procurement institution, e.g. a state or region) would be paid the costs it incurs to treat all the
patients who arrive in a given time period. The manager of such a system would experience no
budgetary difference between using the reference biologic and a less expensive biosimilar,
because its costs are fully paid in either case. In contrast, under a fixed-price system, the system
39
Rovira et. al. (2011) also provide a country-by-country summary of substitutability, availability, pricing and
reimbursement in the following European Union countries: Italy, Spain and the UK as well as partial information for
Germany, Hungary and Norway.
27
would be paid some amount for a procedure or diagnosis and would subtract its costs from that
revenue to determine its surplus.
Notice that in such a setting the central health care authority (“center”) does not have the
information or ability to control the hospital's activities and set them optimally. For example, if
the center identified the social costs and benefits of each procedure, it could give a list of
approved socially valuable services to the hospital. In such a world, if the cost of a biologic drug
were to fall, the center might want the savings back, rather than letting the hospital provide
additional services.
The classic work of Averch and Johnson (1962) lays out this issue. In a setting in which
the regulator has imperfect information concerning next year’s cost, it cannot perfectly instruct
the regulated firm how to choose inputs. The managers of the firm have preferences not to exert
effort, though effort reduces costs. For example, creating and running a tendering process for
biologic drugs at the hospital would require effort. As in Laffont and Tirole (1993), the regulator
does not know the firm’s possible costs. Thus it does not realize the benefit of creating a
tendering process, while the managers of the hospital do. However, if the regulator pays the firm
a fixed price contract, then managers will exert effort to lower costs up to the point where
marginal disutility of effort is equal to the marginal utility from the cost savings. This effort
might include setting up a tendering system and convincing the clinicians in the system to use the
winning product.
In this paper we focus on the impact that the choice of regulatory design has on
biosimilar price and quantity in our set of markets. We note that the impact of competition could
appear in price, quantity, or both. For example, if a biosimilar bid were used to create
competition for the reference biologic, but then hospitals never actually purchase the biosimilar,
28
market prices would be lower as a consequence of the tendering, while biosimilar sales could
still be zero. Likewise, a tendering process might result in limited price competition by the
reference biologic and therefore a high market share for the biosimilar.
A number of researchers have examined the impact of buying institutions on price
discrimination in the pharmaceutical industry (e.g. Danzon and Chao, 2000). First, there is
considerable price dispersion in what different countries pay for prescriptions drugs. This is
likely partially due to income differences and willingness to pay. However, buying institutions
also matter, as shown in Duggan and Scott Morton (2010).40 There are two basic mechanisms at
play. One is that in a bargaining game the outside options of both parties matters. If the buyer
can set up institutions in its country to make the outside option of the pharmaceutical
manufacturer worse, then it can obtain a better contract. Another mechanism is to alter
institutional design in a way that causes the buyer(s) to become more price elastic: optimal price
declines in response to increased buyer elasticity.
Many national health systems create an official drug list in which the center approves a
product to be included on the list at a particular price. The national health system pays for drugs
on the list and physicians prescribe off the list. The drug’s negotiated price may vary depending
on the center’s bargaining power. However, regardless of that price, national demand will not be
elastic under a ‘list’ system because there is no way for the manufacturer to sell more product by
setting a lower price. Schemes such as reference price groups – where consumers pay the
residual cost above the lowest cost product in the group – do create elasticity. Likewise, a
competitive tender by the hospital, region, state, or insurer (sickness fund) as a residual claimant
also creates elasticity.
40
See also Price Discrimination in Input Markets (Inderst and Valetti, 2009).
29
4.! DATA
4.1 EUROPEAN APPROVALS
To date, 21 unique biosimilars have been approved41 for use in Europe and Australia.
Table 1 lists these biosimilars by date of approval and provides detail on each product’s class,
international product name, and clinical indications as of the time of data collection. The EMA
may recommend approval (authorization by the EC) of multiple biosimilars on the same date, or
approval recommendations may be staggered over time.
The identity of a biosimilar entrant, as well as the manufacturer(s) of the biological active
substance and the manufacturer(s) responsible for batch release, must be authorized at the time
of approval. We are therefore able to use the EMA’s official documents to construct a complete
picture of authorized biosimilar entrants in Europe and the manufacturing facilities they work
with in the highly regulated production process (Table 2).42 A potentially confusing aspect of the
manufacturing data is that the firm name on the drug label (the distributor) and authorized
entrant need not be the same corporation, although they often are. In some instances, a firm
separate from those listed in EMA authorization documents can be seen branding and selling a
particular biosimilar. For example, consider Binocrit, an Epoetin biosimilar. The EMA entrant
(“marketing authorisation holder”) is Sandoz, the manufacturers of the biological active
substance are Rentschler Biotechnologie GmbH (Germany) and Lek Pharmaceuticals d.d.
(Slovennia), the manufacturer of the biologic product is Sandoz, and the distributor is the
Eruimpharm in Germany. Table 2 lists each approved biosimilar and maps each entrant (i.e. the
“marketing authorisation holder”) to all registered manufacturer(s) in the production process.
41
42
Two biosimilars were approved and then subsequently withdrawn from the market by their producers.
All documents are available athttp://www.ema.europa.eu/
30
We further document the ownership of each manufacturer of a biological active substance
and record whether that firm is independent or a subsidiary or joint venture of a particular
pharmaceutical company (Appendix Table III). Finally, we consider distributors of biosimilars,
who, as noted, may be different parties than those holding manufacturing authorizations.
Appendix Table I lists countries of market entry and the total number of distributors of each
biosimilar. Figures 3a-3c show the number of distributors relative to the number of approved
products in our full sample over the years studied. We look at the number of unique distributors
entering a country as our primary measure of entry.
Table 2 reveals several interesting facts about the manufacture of biosimilars. First, we
see that the manufacturer of the biological active substance is typically different from the
manufacturer responsible for the drug’s batch release. Second, we note that many separately
approved biosimilar entrants share a common firm that is responsible for the manufacture of the
biological active substance and/or firm responsible for batch release of the drug – i.e. distinct
entrants use many of the same manufacturers in the production of biosimilars. For example, two
separate companies, Stada and Hospira, are product entrants for two unique Epoetin Zeta
biosimilars (Silapo and Retacrit, respectively), however, both products’ active ingredients are
manufactured by Norbitec GmbH in Germany. Similarly, all three approved Epoetin Alfa
products (Epoetin Alfa Hexal, Binocrit, and Abseamed) list the same two manufacturers of the
biological active substance (Rentschler Biotechnologie in Germany and Lek Pharmaceuticals in
Slovenia) and the same manufacturer responsible for batch release (Sandoz, Austria) in their
approval documents.43 We believe that additional research into manufacturing expertise and scale
43
Epoetin Alfa Hexal and Abseamed are based on duplicate applications. This is no longer allowed by the European
Commission. (http://ec.europa.eu/health/files/latest_news/2011_09_upd.pdf)
31
economies in the manufacturing processes for biosimilar medicines will be an important focus
for future research.
In this paper, we focus on two primary measures of “entry” into new biosimilar markets:
1) the identity of unique distributors – i.e. the firms under whose names the drugs are sold; and
2) the identity of unique product entrants – i.e. the firms that have successfully pursued and been
granted marketing authorization from the EMA for a biosimilar (a.k.a. the “marketing
authorisation holder”). Price competition may be carried out at the country level by distributors,
but such distributors also face a (potentially common) marginal cost, which would be set by the
product entrant. As such, we consider both measures in our empirical analysis.
We observe a substantial amount of entry by biosimilars across markets and drugs.
Figures 3a-3c show the number of biosimilar distributors and total approved entrants over time.
Notably, the two lines may cross and one need not be above or below the other. When the total
number of EMA-approved products is greater than the number of unique distributors in the
sample, this indicates that either some products are not distributed at all or (more commonly),
that the number of distributors that are active in our sample countries in a given year and class of
biosimilars is smaller than the total number of approved biosimilars in that class. This will be the
case, for example, if a single distributor is responsible for the European distribution of more than
one biosimilar product within a class of drugs. More commonly, we see that the number of
distributors active in our sample is greater than the number of approved products. This is the case
when one product uses different distributors in different countries or when one product is sold by
multiple distributors within a country. This information is captured in Appendix Table I.
32
4.2 BIOSIMILAR SALES
We obtained data from IMS Health (MIDAS™ Database) on revenues and quantities sold
of all biologics in 22 European countries plus Australia. Appendix Table II tabulates the data by
country and shows the first year each class of biosimilar was sold in each of the countries in our
sample. The years covered are 2007 to 2014, inclusive.44 The data include a flag for type:
reference product or biosimilar. We carefully examined and cleaned the data and corrected minor
inconsistencies in biosimilar vs. other biologic product categorizations, but found no other errors
in the classification of products.45 Table 3 presents total dollar sales of biologics and biosimilars
by class and year.
However, one perennial issue with pharmaceutical data is the potential existence of ex
post rebates. If a hospital receives rebates after it places its order, and those rebates do not appear
on the original invoice, they will not be captured in the data used. As such it is likely that price is
sometimes overstated. We do not have any data to indicate for which products and in which
countries these issues are most likely to be relevant. Any such error will be correlated within
country, as purchasing practices are more similar within countries than across them.
When considering market entry, we designate the first year in which a country recorded a
positive quantity for a biologic or biosimilar, respectively, as the entry year in our analysis.
Nearly all countries have sales of reference biologics in all three classes in our first year of
observation, 2007. For biosimilars, any year in which the quantity of biosimilars sold was greater
44
There are four exceptions to this: due to lack of full data availability, data for Lithuania, Slovakia, and Sweden are
only included through 2012 and data for Latvia are only included through 2010.
45
Other researchers should be aware that IMS creates a price by dividing revenues by quantities, but then reports a
rounded quantity. Re-creating price by dividing revenue by the rounded quantity results in large price outliers when
quantities are small. It is possible to reconstruct the non-rounded quantity by dividing revenue by price again.
33
than or equal to 0.05% of total units sold for that class of drugs was categorized as having
biosimilar entry.
The biologic drugs we consider are produced in several different forms. For example, we
see different packaging options that reflect the number of milliliters of liquid in a pre-filled
syringe. It is often the case that a biosimilar enters a national market with only one form while
the incumbent reference product produces several forms. Treating each form as a separate
product results in very little “entry” as a fraction of the number of markets, and probably does
not reflect the increased choice available to most patients (those who do not need a specialized
form). Instead, we combine all forms of a biosimilar sold by the same firm in the same country
and year into one observation, scaled by standard units of active drug. We can do this very
accurately because IMS provides a variable called “standard units” which converts each form of
every biologic product into common units. Other researchers have used standard units from the
IMS data to capture quantities sold (e.g. Berndt and Trusheim, 2015). Alternative volume
measures include defined daily dosage (DDD), extended units, and so-called “eaches.” We
follow Berndt and Trusheim (2015) in using standard units. Based on the prices reported to IMS,
we create average prices for the brand, for biosimilars, and a weighted overall average price for
each year, biosimilar drug class, and country in the dataset.46
We create several relative price variables for biosimilars as follows. Our first measure
takes the branded price in the first year of the data (2007) or the year before the biosimilar first
appears in the data (whichever is later) as the benchmark branded biologic price. It is the
denominator of our relative price variable in all future years. We denote innovator i’s price in
46
Other researchers (e.g. Ganslandt and Maskus, 2004) have written about the role of parallel imports in European
pharmaceutical Markets. Such imports are legal and happen frequently. They are, however, less likely to be relevant
in the setting we study, since biologic drugs are relatively costly and often procured by health systems for
administration in hospitals.
34
country c at time zero, /#012 . The price of biosimilars sold in that country, c, in each subsequent
year, t, is the numerator. There may be multiple distributors of biosimilars, s, in which case we
take a weighted average of their prices each year. For each of our three drugs in the sample:
: 9:;< =:;<
2 -----/-45671#85
=01
: 9:;<
/#012
Thus, if one biosimilar enters at 80% of the pre-entry branded price, the relative price
variable will be 0.8. If a second entrant sets a price of 60% of the original brand price and has
equal sales to the first, the weighted average relative price will be 0.7. If the brand matches the
biosimilar price in subsequent years, our ratio will not return to one. This is desirable because
both products’ prices are lower than the initial brand price due to biosimilar entry.
We also consider the average market price in a given year relative to the average market
price in the year before biosimilar entry. This is defined similarly, however the numerator
includes weighted average prices of all products and distributors in a given drug class, a, not just
the weighted average price of biosimilars in that class:
? 9;< =;<
3 -----/-45671#85
=01
? 9;<
/#012
The variable calculated in equation 3 corresponds to the overall average market savings
in a given year relative to the year prior to price competition. This value is of particular interest,
since, as noted above, the average price of the reference product may drop in response to
biosimilar competition and therefore there are savings to the payer when buying reference
product in years prior to biosimilar entry as well.
Prices vary over time and across countries – even for the same product from the same
manufacturer – but quantities grow almost exclusively monotonically (Appendix Figure II).
35
Appendix Figure III plots relative prices over time. Relative prices of biosimilars also show
considerable variation, though the mean is below one, as we would expect. There are a number
of drug-country-year combinations where the biosimilar is much more expensive than the 2007
branded biologic. However, the average quantity sold in these observations is low.
Our quantity variable is a measure of penetration of biosimilars by unit volume. We sum
biosimilar units in a country and year to form the numerator. The denominator is the sum of all
units sold of a given biologic drug class (i.e. both reference products and biosimilars) in a given
country year, qact. Price is not used to weight the units sold. For each of our three classes of
biosimilars in our sample:
BC745
4 ------A01
=-
B DB01
B D701
Growth in biosimilar market shares over time is presented in Appendix Figure I.
Our analysis will be focused on these outcome measures as well as on the number of
entrants into each country-level biologic drug market. The empirical section of the paper
considers policy predictors of entry, changes in price conditional on biosimilar entry, and
whether biosimilars become a significant fraction of consumption in the countries in our data.
4.3 Survey and policy data: procurement of biosimilars in Europe and
Australia
For each country in our sample, we collected detailed data on the manner in which each
class of biologic drugs and biosimilars are purchased. Recall that the EMA recommends
approval of these medications for safety and efficacy simultaneously for all of the European
Union, and that EMA guidelines also apply to Australia. The variation across countries in entry,
36
price, and quantity consumed thus occurs because each market has a different set of processes to
determine procurement, reimbursement, and to encourage usage of biosimilars – either in general
or for products from particular firms who have successfully tendered for the nation’s needs.
In each country, there is a government agency that determines whether a new product
will be included in the national health scheme, and either sets a price or a reference group for it.
In a typical procedure, the pharmaceutical division of the health ministry negotiates with the
manufacturer and agrees that the biosimilar will be added to the list of drugs for which providers
will be reimbursed. The biosimilar's price is then determined, often through negotiation. For
example, the health ministry and the manufacturer might agree that the biosimilar will be priced
20% below the price of the reference brand product. Alternatively or additionally, tendering may
occur at the hospital, regional, or state level, as discussed below. After the drug is available in
the country, physicians prescribe it in hospital, clinic, or outpatient settings and the government
pays the bill. Note that in the example above, the taxpayer/government benefits if the biosimilar
is used because it is 20% less expensive. However, it should be noted that there may or may not
be any financial or organizational incentives for hospitals, clinics, physicians, or patients to use
the biosimilar.
Recognizing this problem, some countries in Europe have devised procurement schemes
to stimulate competition between the reference biologic and the biosimilar. Most typically, this is
done by empowering an agent in the system to seek competitive bids for drugs in a certain class,
where the agent retains the savings from carrying out a competitive tender. For example, in
England, each hospital has a budget and can procure biologics through a competitive tendering
process. If the biosimilar bid is the lowest, then the hospital has an incentive to purchase the
biosimilar instead of the reference product and use the saved resources for some other activity. In
37
Germany, the large state-level insurers (sickness funds) are paid in a capitated fashion and create
and run drug formularies. These organizations negotiate for discounts and may choose the
biosimilar to be the biologic on the formulary for everyone covered by their insurance. These
types of financial incentives and procurement schemes are likely to both push down the price of
the biosimilar and increase its use.
With the assistance of a team of research assistants, we assembled documents and
regulations from each country in our dataset about the nature of their domestic biologic drug
procurement processes. We also conducted telephone surveys of domestic biosimilar drug
procurement experts. A full list of individuals and institutions that gave permission for us to
include their names as references for the data collected through our surveys is included in
Appendix Table VI.
Determining the nature of procurement was difficult for two reasons. First, it varies by
drug because the drugs studied here are distributed through different channels, e.g. hospital
versus dialysis clinics vs. ambulatory distribution. Secondly, the official regulations do not
always deliver a complete picture, and an interview is required to determine the true nature of the
regulation. This problem occurs because biologics are frequently “carved out” of standard health
care regulations because they are so expensive, require different handling, and are often used by
a small group of patients. Further, biosimilars may be carved out of standard generic
procurement policies and patient cost-sharing policies. For example, in some countries the
patient must pay a copayment if she chooses to buy the brand rather than the generic. Because
biosimilars are not technically generics, they are often exempted from this type of financial
incentive scheme.
38
In addition, there can be regulations that generate perverse incentives that can be
explained by a market participant. For example, hospitals in Ireland and Belgium could procure
biologics by competitive tendering, but until recently were incentivized to purchase the product
with the highest list price. In that way, the absolute size of the discount was largest, and the
system was set up so that the discount was retained by the hospital, while the total cost of the
purchases was paid by the center. Tendering designed in this way has the perverse effect of
encouraging the hospital to choose the high-priced reference biologic. In other cases, a hospital
may be officially permitted to tender under the regulations, but it chooses not to.
The procurement categories used in our analysis are presented with their averages in
Table 4. We note that tenders were quite common in the markets we studied; many respondents
attributed this to EU rules that require public tendering for all large purchases. Tendering for
Epoetin occurred in 94% of country-years, tendering for Filgrastim in 93% of country-years, and
tendering for Somatropin in 87% of country-years. We learned, however, that tendering
processes vary in strength. The variable “strength of tender” was defined as 0 when no tendering
existed at the country-class-year level and as 1 when the winner of a tender was assigned all
demand at the level of the tender in a given country, drug class, and year. A value of 0.5 was
assigned for cases where the winner of a tender was only guaranteed the market of “naïve” (new
patient) demand. The strongest tenders – those that guaranteed all patient demand – were
observed only in 53-59% of country-years (Table 4).
To account for effects due to the size of a drug purchase, we created a measure of
expected demand of the buyer. We imputed the average size of the tendering population by
dividing the national population by the number of tendering units for a country-product-year.
Thus, the size of the tendering population is equal to the size of the national population in cases
39
where tendering is done at the national level.47 When tendering is done at the state or regional
level (e.g. Sweden), the tendering population is calculated as the average population per state or
region. When tendering is done at the hospital level only (e.g. Germany), the tendering
population is calculated as the average population served by each hospital. In a limited number
of cases in which tendering is done at two different levels (e.g. as is the case in the U.K.), the
tendering size was assigned as the value of the population served by the larger of the two units.
Finally, based on the results of our surveys of experts from various national health
ministries, we collected data on a set of non-procurement incentives to use biosimilars, such as
whether there was any physician or patient education about biosimilars (for any products, at any
point(s) in time), whether there were any financial or non-financial incentives for physicians to
use biosimilars, and whether any domestic biosimilar effectiveness study was done, etc. These
types of policies may serve to effectively increase (decrease) the demand for biosimilars by
growing (shrinking) the size of the potential population of biosimilar users. These nonprocurement data are summarized in Table 4. While several such policies might be implemented,
the average number of non-procurement policies at the country level was quite low, at 1.3 to 1.35
policies. This was all combined with national population, GDP, and pharmaceutical expenditures
(both as a fraction of GDP and imputed in 2010 dollars).
Biosimilars represent a novel category of medicines, particularly in the area of cancer.
We were therefore aware that countries might have altered their policies (both procurement and
non-procurement related) during the analysis period. Thus, in our interviews, we explicitly
included questions about changes over time. When we learned of a policy change, we note the
47
In one case (Slovakia) tendering was done at the insurer level, where the national health system reported that the
tender only applied to 60% of the population, so the relevant population imputation was adjusted to reflect this.
40
first year in which that change occurred (came into effect), and include that in our dataset. For
example, if a country adopted competitive tendering in 2010, its indicator would only be coded
as “1” for that country for years 2010 and later. Aggregate data summarizing the results of our
policy survey for all country-years are shown in Table 4. We see considerable variation in
procurement policies, such as the type and strength of tendering, non-procurement incentives,
and country-level indicators across countries and over time.
We note that overall national fiscal health does not seem to be strongly related to the
existence of competitive tendering. To the extent that there is a correlation, it is that more fiscally
healthy countries are more likely to have effective procurement policies. For example, Germany
has been very successful in this regard. However, while Greece had no policies to promote
biosimilars and Spain has very few, Sweden also did very little to incentivize their use over the
years studied. We view the lack of correlation between fiscal health and more aggressive
purchasing as an interesting example of the difficulties of getting financial incentives to trickle
down within a bureaucracy. While the health ministry may be very concerned about the national
spending on pharmaceuticals, suitably incentivizing the purchasing manager for biologics at a
hospital is not always a result of that concern.
5.! GRAPHS AND ESTIMATION
The take-up of biosimilars can be seen visually in Figure 2 and Appendix Figures I – III. Much
of the story is clear by inspection: quantities and dollar values of biosimilars purchased trend up
across almost all countries over time. Average per unit prices (Appendix Figures IV-V) are
stable or trending down in most cases. There are a few cases of very high biosimilar prices
relative to the brand and many of these are likely due to our inability to capture ex-post rebates
41
for certain products in certain markets. We note that some high relative prices occur in countries
that purchase very small amounts, and several occur in settings where known features of the
reimbursement system and/or hospital price reports may result in recorded prices that are higher
than the costs ultimately incurred by payers, for reasons such as rebates.
The first set of regression models (Table 5) considers predictors of distributor entry at the
country-drug-year level. The dependent variable in all models is the number of unique
distributors observed selling positive quantities of biosimilars by country and year. We see that
entry of distributors increases over time and is higher for Epoetin biosimilars than for Filgrastim
biosimilars or Somatropin biosimilars (the omitted category). On average, Epoetin markets have
an additional 0.5 distributor entrants per country and Filgrastim markets an additional 0.2
distributor entrants per country, controlling for all other factors.
We note that both national GDP and national pharmaceutical expenditures are associated
with more distributor entry. In our sample, on average, a country with an additional $1.5 trillion
in GDP would be expected to have one additional distributor entrant per class of biologics. This
result is predicted by theory: fixed costs of entering a new market – e.g. negotiating price and
conditions of reimbursement with the health authority – are likely similar across countries, but
some markets are much larger in (potential) size. Country level fixed cost should not be confused
with the fixed regulatory costs of scientific approval, which occur at the European level. Since
national pharmaceutical expenditure provides slightly more explanatory power than using
national GDP (R-squared of 0.432 vs. 0.428), we use national pharmaceutical expenditures as a
control for market size in subsequent regressions.48
48
GDP and national pharmaceutical expenditures are highly collinear and other coefficients are virtually identical
regardless of which of these two variables is used on the right hand side of our regression models.
42
Further, we see in Table 5 that biosimilar quotas are associated with more entry. With
respect to the number of distributors entering a given market, stronger tenders are also associated
with more entry. On average, the presence of any quota is associated with roughly 0.4 additional
distributors in a given country’s market for a given class of biologics, while going from no
tender to a tender for all patient demand (both new and existing) is associated with a similar
increase of roughly 0.4 additional entrants. We note that both sets of results are even stronger
when Epoetin is considered alone; in this case, the presence of a quota in a domestic Epoetin
market is associated with an average of 0.75 additional distributors, while going from no
tendering to a tender for all patient demand is associated with roughly one additional distributor.
These results also confirm what theory would predict, since both quotas and (strong) tenders
serve to increase the effective potential market size for biosimilars and should be associated with
more biosimilar distributor entry.
Table 6 presents the same regression models as Table 5, but the dependent variable in all
models is the number of unique product entrants. As was the case with distributor entry, the
number of products increases over time and is higher for Epoetin biosimilars than for Filgrastim
biosimilars or Somatropin biosimilars (the omitted category). On average, Epoetin markets have
an additional 1.0 products per country and Filgrastim markets an additional 0.7 products per
country, controlling for all other factors. Again, both national GDP and national pharmaceutical
expenditures are associated with more distributor entry, as predicted by theory. In our sample, on
average, a country with an additional $3 trillion in GDP would be expected to have one
additional product entrant per class of biologics.
Here as well, we see that biosimilar quotas are associated with more entry; on average the
use of any quota is associated with roughly 0.4 additional products in a given country’s market
43
for a given class of biosimilars. The primary difference between models predicting entry of
individual products versus individual distributors as that in the case of products, the strength of
the tender is not a statistically significant predictor of entry. This indicates that bidding at the
distributor level may be an important determinant of entry dynamics in the European context.
The second set of regression models explores policies associated with the price variables
represented in Equations 2 and 3 above. Table 7 uses the price variable in Equation 2 to compare
biosimilar prices in a given year to pre-biosimilar entry reference product prices. Table 8
compares average market prices (for all drugs in a given class of biologics) in a given year to
average prevailing market prices in the year prior to biosimilar entry. For the reasons explained
above, we believe that Table 8 likely best captures the product market level savings associated
with the introduction of biosimilars, and we focus on interpreting those results here. However,
we note the caveats discussed above with respect to this price data: since IMS data does not
capture ex post rebates, we should not be surprised that these regression models are not able to
strongly predict price dynamics.
Table 8 indicates that in the IMS data, average market prices fall over time at a rate of
about 3 percentage points per year following biosimilar entry. However, this decline is steepest
in Epoetin and Filgrastim markets, where average annual price declines are roughly 8 and 7
percentage points, respectively. Considered alone, there is no time trend in prevailing average
market prices for Somatropin. This is consistent with only a small decline in prices for this class
of biosimilars, where there have been few entrants.
We further note that the price declines associated with biosimilar competition were
higher (by about 24 percentage points) for Filgrastim relative to Epoetin and Somatropin. In this
case, we see an ambiguous relationship between national pharmaceutical expenditures and
44
prices: in aggregate there is no clear trend, but higher national pharmaceutical expenditures
appear to be associated with slightly lower Epoetin prices (roughly one percentage point), but
slightly higher Filgrastim prices (roughly 0.4 percentage points).
In some specifications, the size of the tendering population appears to be positively
associated with (higher) prices, but the result is not statistically significant in most specifications.
We are concerned that while tenders may lead to lower negotiated prices, they also involve ex
post rebates, which we do not see in our data. If some country-year-drugs have this relationship,
then it will create a spurious positive correlation between tendering and high prices.
In alternative specifications, we remove the time trend from the models in Table 8 and
control for the number of entrants. We find that the number of entrants into a class of biosimilars
is weakly negatively correlated with our measure of price. This raises the possibility that
countries with relatively high drug prices may attract more product entrants. If countries with
higher overall price levels have more product entry, we should control for whether a market was
“expensive” prior to biosimilar competition. Thus, we instrument for the number of product
entrants in each class of biosimilars using the average price level of biologics in a given country
at the start of our period of observation by creating a weighted average of the per unit prices of
three largest biologics that did not have biosimilar entry49. This price ratio approximates whether
a country was an expensive market for biologic drugs before biosimilar competition. The
instrumental variables regressions result in predictive models of price that are qualitatively and
quantitatively similar to those presented in Table 8, with one main exception: in these models,
49
We identify these by looking at the largest biologics markets in all countries over the entire period of observation
and taking the top three products, which were Etanercept (brand name Enbrel), Adalimumab (brand name Humira),
and Infliximab (brand name Remicade).
45
stronger tenders are associated with lower price levels for Epoetin. Appendix Tables IV and V
present these results.50
We also note that the count of non-procurement policies to encourage the use of
biosimilars in a country and drug class (e.g. physician education, incentives to use biosimilars,
and domestic effectiveness studies) is associated with lower prices, and that the count of nonprocurement incentives is statistically significantly associated with lower prices for both Epoetin
and Somatropin products, when considered independently. Each additional non-procurement
policy is associated with a roughly 9 percentage point decrease in prevailing market prices for
Epoetin and a roughly 3 percentage point decrease in prevailing market prices for Filgrastim.
Finally, Table 9 considers unit penetration of biosimilars. Figure 2a and Appendix Figure
1 show that there is a strong trend for biosimilar penetration to rise over time, although, as noted
above, there is no theoretical reason to expect this trend, since competition may cause prices to
fall even in the absence of take-up. This trend is also seen in Table 9, with, on average, a roughly
6 percentage point increase in biosimilar penetration with every passing year. There is a good
deal of heterogeneity in this average increase in penetration, with biosimilar Epoetin penetration
growing at about 9 percentage points per year, biosimilar Filgrastim penetration growing at about
4 percentage points per year and biosimilar Somatropin penetration growing at about 2
percentage points per year. The penetration of biosimilar Epoetin is higher than for the other two
classes of biosimilars in every year by approximately 19-20 percentage points.
When moving from a setting with no tendering to a tender that guarantees the winner full
demand, we observe that stronger tenders are, on average, associated with significantly higher
rates of biosimilar penetration on the order of 14-15 percentage points, all else equal. This
50
Note: this relationship cannot be modeled for Somatropin alone due to the fact that no market experienced more
than one Somatropin entrant.
46
relationship is mainly driven by Epoetin. Finally, we note that the number of non-procurement
policies to encourage the use of biosimilars in a country and drug class is associated with higher
rates of take-up overall. The relationship between non-procurement policies and take-up is
particularly strong for Filgrastim biosimilars, where each additional policy is associated with a
roughly 3 percentage point increase in biosimilars as a fraction of total sales volume.
One concern about using same-year policy and biosimilar sales data in our regression
models is that the full impact of policies may lag their implementation. While we were careful in
our data collection and survey wording to focus on only coding a policy as being in place in
years in which it had been implemented, we tested for a delay in response to policies by using
lagged independent variables. For example, if a country implemented tendering in 2008 and we
were worried that we would not see the full impact of the tendering until 2009, we should regress
2009 entry (or price or penetration) on 2008 policies. We checked all of our regression models
for evidence of policy lags and found none; the results of lagged regressions were virtually
indistinguishable from the main regressions presented here with respect to both the magnitude
and statistical significance of the coefficients estimated.
Another concern may be that omitted variables influence entry decisions of biosimilar
firms. Perhaps the most obvious example is a set of political economy questions regarding the
existence of a domestic industry. For example, do we observe more biosimilar entry in countries
with a domestic interest in biosimilars? We test for this by defining a binary indicator for “any
biosimilar industry” which is equal to one when a firm within a given country is either a licensed
manufacturer or marketing authorization holder. Thus, the indicator is positive for countries
whose domestic firms stand to gain from biosimilar adoption. We find no clear evidence for the
role of domestic industry in predicting adoption, and are therefore unconcerned about this source
47
of omitted variable bias. In fact, if anything, countries with any domestic biosimilar industry
experience entry marginally later than countries without a domestic biosimilar industry for all
three classes of biosimilars (see Appendix Table II).
6.! CONCLUSIONS AND IMPLICATIONS FOR THE UNITED STATES
We find that entry of both distributors and unique products increases over time and is
higher for Epoetin biosimilars than for Filgrastim biosimilars or Somatropin biosimilars. Further
the presence of biosimilar quotas is associated with more entry as measured by both distributors
and unique products, and the results are strongest when considering Epoetin biosimilars alone. In
predicting distributor entry, the strength of the tendering process used to procure biologic drugs
is also positively associated with more entry, indicating that bidding at the distributor level may
be an important determinant of entry dynamics in the European context.
We also consider predictors of average product prices following biosimilar competition.
Prevailing market prices fall over time at a rate of about 3 percentage points per year following
biosimilar entry. This decline is steepest in Epoetin and Filgrastim markets. Considered alone,
there is no time trend in prevailing average market prices for Somatropin. This is consistent with
only a small decline in prices for this class of biosimilars, where there have been few entrants.
We find that price declines associated with biosimilar competition were higher for
Filgrastim relative to Epoetin and Somatropin. A count of non-procurement policies to
encourage the use biosimilars in a country and drug class (e.g. physician education, incentives to
use biosimilars, and domestic effectiveness studies) is associated with lower prices. We remain
concerned that while tenders may lead to lower negotiated prices, they also involve ex post
48
rebates, which we do not see in our data. If some drugs in some locations have this relationship,
then it will create a spurious positive correlation between tendering and high prices. Since our
data do not capture ex post rebates, it is unsurprising that price regression models are not able to
make detailed predictions on price dynamics.
We also examine penetration of biosimilars. There is a strong trend for biosimilars as a
share of total sales to increase over time with, on average, a roughly 6 percentage point increase
in biosimilar penetration with every passing year. There is a good deal of heterogeneity in this
average increase in penetration, with biosimilar Epoetin penetration growing at about 9
percentage points per year, biosimilar Filgrastim penetration growing at about 4 percentage
points per year and biosimilar Somatropin penetration growing at about 2 percentage points per
year. Stronger tenders are, on average, associated with significantly higher rates of biosimilar
penetration, and this relationship is mainly driven by Epoetin biosimilars. Finally, we note that
the number of non-procurement policies to encourage the use of biosimilars in a country and
drug class is associated with higher rates of take-up overall, and the relationship between nonprocurement policies and take-up is particularly strong for Filgrastim biosimilars.
Now that the US is moving towards biosimilar competition several years after Europe,
how should US policymakers structure payer institutions and policies in order to create the price
competition for biologics? One open policy question is the degree to which biosimilars will be
judged to be “substitutable” vs. “interchangeable” in the United States; we note that the strongest
tenders (i.e. those for full demand) observed in European countries most represent
interchangeability,51 whereas other types of tendering more closely mimic the types of settings in
which biosimilars are only seen as substitutable. Those stronger tenders are, on average,
51
As defined in the United States
49
associated with about 15 percentage points higher biosimilar penetration (moving from a setting
with no tendering to a tender that guarantees the winner full demand). In the Epoetin market,
which is the largest and most active of the three, a tender that gives the winner full demand is
associated with prices that are 60% lower than the reference product’s price.
The potential impact of biosimilars is affected by the logistics of biologics use. Physician
administered drugs are not included in Medicare Part D, but in Medicare part B, which is the part
of Medicare that covers doctor visits. Physician-administered drugs (PADs) are not typically
managed by a pharmacy benefits manager, nor are they subject to the same sort of formularies
that allow a buyer to move market share in response to price. The medical benefit insurer may
not be organizationally enabled to create competition among biologics.
Furthermore, a physician may purchase and store expensive biologics in his or her office
until they are used by patients who are likely to be covered by a variety of insurers. Using a
particular biosimilar for which a particular patient’s insurer has contracted may be difficult, as
the physician must have it to hand at the time of the visit. In the Medicare program, PADs are
normally recorded by the physician’s office under a J-code. If there is more than one drug that
treats a condition, they often share a J-code. Thus, the final payer/insurer may not be able to
figure out which product the physician bought, and therefore with which manufacturer to
negotiate for a lower price, even if that negotiation happens ex post instead of ex ante. This
presents another argument for improving the J-code to provide product detail, such as the
identity of a product’s manufacture.52
52
The Center for Medicare and Medicaid Services (CMS) is considering J codes for provider-administered
biosimilars under Medicare Part B and it is expected that private payers would follow suit (Sarpatwari, Avorn, and
Kesselheim, 2015)
50
Given the current way we insure, reimburse, and deliver biologic drugs in the United
States, it is difficult for the insurer to bargain for a discount in return for instructing physicians to
use a particular version of a biologic drug. Policy makers and insurers in the U.S. may therefore
need to analyze their buying institutions and consider new policies, such as creating physician or
hospital incentives for use, if they would like to successfully create price competition among
substitutable biologic drugs.
51
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54
Figure 1. Biosimilar share of total unit sales by class, 2014 (or most recent year)
BiosimilarLshareLofLtotalLunitLsales
2014LorLmostLrecentLyear
Australia
Austria
Belgium
Bulgaria
Denmark
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Norway
Poland
Portugal
Romania
Slovenia
Spain
UK
0
0.1
0.2
0.3
Somatropin
0.4
0.5
Filgrastim
0.6
0.7
Epoetin
0.8
0.9
1
Figure 2a. Annual units sold for all products, all countries in sample, 2007-2014
AnnualLUnitsLSold,LAllLProducts
AllLCountriesLinLSample,L2007S2014
25000
20000
15000
10000
5000
0
2007
2008
2009
2010
2011
2012
2013
2014
Year
Ref.LProductLUnitsL(1000s)
BiosimilarLUnitsL(1000s)
TotalLUnitsL(1000s)
Figure 2b. Annual Dollar spending on all products, all countries in sample, 2007-2014
AnnualLSpendingLonLAllLProducts
AllLCountriesLinLSample,L2007S2014
2000000
1500000
1000000
500000
0
2007
2008
2009
2010
2011
Year
Ref.LProductLSpendL(1000s)
TotalLSpendL(1000s)
2012
2013
BiosimilarLSpendL(1000s)
2014
2008
2008
2010
2012
distributors
2011
Number'of'entrants'in'the'Epoetin'market
2009
products
2010
2011
2012
Number'of'entrants'in'the'Filgrastim'market
2009
distributors
2013
2013
2014
2014
9
8
7
6
5
4
3
2
1
0
2007
2008
products
2010
distributors
2011
2012
Number'of'entrants'in'the'Somatropin'market
2009
2013
2014
Entry: products are EMA-approved biosimilars by end of a given year; distributors are a count of unique firms selling biosimilar drug in our sample.
Figure 3. Number of entrants in the Epoetin, Filgrastim and Somatropin markets, all countries, 2007-2014
10
9
8
7
6
5
4
3
2
1
0
2007
7
6
5
4
3
2
1
0
2007
products
International Product
Name
Indication(s)
Table 1. List of biosimilars by EMA Approval date
Active
Substance
Somatropin
Omnitrope
Dwarfism, Pituitary; Prader-Willi Syndrome; Turner Syndrome
Somatropin
Valtropin
Dwarfism, Pituitary; Turner Syndrome
Epoetin Alfa
Binocrit
Anemia; Kidney Failure, Chronic
Epoetin Alfa
Abseamed
Anemia; Cancer; Kidney Failure, Chronic
Epoetin Alfa
Epoetin Alfa Hexal
Anemia; Cancer; Kidney Failure, Chronic
Anemia; Blood Transfusion, Autologous; Cancer; Kidney
Epoetin Zeta
Silapo
Failure, Chronic
Anemia; Blood Transfusion, Autologous; Cancer; Kidney
Epoetin Zeta
Retacrit
Failure, Chronic
Filgrastim
Tevagrastim
Cancer; Hematopoietic Stem Cell Transplantation; Neutropenia
Filgrastim
Filgrastim Ratiopharm Cancer; Hematopoietic Stem Cell Transplantation; Neutropenia
Filgrastim
Ratiograstim
Cancer; Hematopoietic Stem Cell Transplantation; Neutropenia
Filgrastim
Biograstim
Cancer; Hematopoietic Stem Cell Transplantation; Neutropenia
Filgrastim
Zarzio
Cancer; Hematopoietic Stem Cell Transplantation; Neutropenia
Filgrastim
Filgrastim Hexal
Cancer; Hematopoietic Stem Cell Transplantation; Neutropenia
Filgrastim
Nivestim
Cancer; Hematopoietic Stem Cell Transplantation; Neutropenia
Arthritis, Psoriatic; Arthritis, Rheumatoid; Colitis, Ulcerative;
Infliximab
Inflectra
Crohn Disease; Psoriasis; Spondylitis, Ankylosing
Arthritis, Psoriatic; Arthritis, Rheumatoid; Colitis, Ulcerative;
Infliximab
Remsima
Crohn Disease; Psoriasis; Spondylitis, Ankylosing
Follitropin Alfa Ovaleap
Anovulation
Follitropin Alfa Bemfola
Anovulation
Filgrastim
Accofil
Neutropenia
Source: www.ema.europa.eu
*in process of product launch **launched in EU post 2014 ***launched in EU in 2014
10/2013
09/2013
03/2014
09/2014
10/2013
12/2007
09/2008
09/2008
09/2008
09/2008
02/2009
06/2009
08/2010
12/2007
04/2006
04/2006
08/2007
08/2007
08/2007
EMA Approval
Month / Year
n/a
n/a
n/a
n/a
n/a
n/a
n/a
04/2011
n/a
n/a
n/a
n/a
n/a
n/a
n/a
05/2012
n/a
n/a
n/a
Withdrawal
Month / Year
2013
n/a**
2014
n/a**
2013
2008
2009
2008
2008
n/a*
2009
n/a*
2010
2008
2007
n/a
2007
2007
2007
First Year of
Market Entry
Table 2. Manufacturers of biosimilar products, European markets, 2007-2014
Manufacturer(s)
responsible for
batch release
Manufacturer is
subsidiary or joint
venture of
Year of
approval
Manufacturer(s) of
biological active
substance (and
country)
2007
Molecule
International
product name
1. Independent; 2.
Sandoz
Entrant:
Marketing
authorization
holder (and
country)
Sandoz GmbH
(Austria)
Hexal AG
(Germany)
2007
Epoetin Alfa
1. Independent; 2.
Sandoz
Epoetin Alfa Hexal
Sandoz GmbH
(Austria)
2007
Sandoz GmbH
(Austria)
1. Independent; 2.
Sandoz
2007
Epoetin Alfa
Sandoz GmbH
(Austria)
Bioceuticals, Stada,
Nordmark
Binocrit
STADA
Arzneimittel AG
(Germany)
Medice Arzneimittel
Pütter GmbH & Co.
KG (Germany)
Norbitec GmbH
(Germany)
Epoetin Alfa
Stada R&D AG
(Germany)
Norbitec GmbH
(Germany)
SICOR Biotech
UAB (Lithuania)
Teva Pharma B.V.
(Netherlands)
Teva
Bioceuticals, Stada,
Nordmark
2008
2007
1. Rentschler
Biotechnologie
GmbH (Germany);
2. Lek
Pharmaceuticals d.d.
(Slovenia)
1. Rentschler
Biotechnologie
GmbH (Germany);
2. Lek
Pharmaceuticals d.d.
(Slovenia)
1. Rentschler
Biotechnologie
GmbH (Germany);
2. Lek
Pharmaceuticals d.d.
(Slovenia)
Epoetin Zeta
Hospira UK Limited
(UK)
Teva GmbH
(Germany)
Epoetin Zeta
Filgrastim
1. STADA
Arzneimittel AG
(Germany); 2.
HOSPIRA
Enterprises B.V.
(Netherlands)
Abseamed
Silapo
Retacrit
Tevagrastim
Nivestim
Filgrastim Hexal
Zarzio
Biograstim
Ratiograstim
Filgrastim
Filgrastim
Filgrastim
Filgrastim
Filgrastim
Filgrastim
Apotex Europe B.V.
(Netherlands)
Hospira UK Limited
(UK)
Ratiopharm GmbH
(Germany)
AbZ-Pharma GmbH
(Germany)
Sandoz GmbH
(Austria)
Hexal AG
(Germany)
Intas
Accord Healthcare
Pharmaceuticals Ltd.
Ltd. (UK)
(India)
Intas
Pharmaceuticals
Limited (India)
1. Hospira Zagreb
d.o.o (Croatia, A); 2.
Hospira Zagreb
d.o.o. (Croatia, B)
SICOR Biotech
UAB (Lithuania)
SICOR Biotech
UAB (Lithuania)
Sandoz GmbH
(Austria)
Sandoz GmbH
(Austria)
1. Merckle Biotec
GmbH (Germany);
2. Teva
Pharmaceuticals
Europe B.V.
(Netherlands)
Apotex Nederland
B.V. (Netherlands)
1. PLIVA Kraków,
S.A. (Poland); 2.
Hospira Enterprises
B.V. (Netherlands)
Merckle Biotec
GmbH (Germany)
Merckle Biotec
GmbH (Germany)
Sandoz GmbH
(Austria)
Sandoz GmbH
(Austria)
Independent
Teva
Independent: Intas
and Accord have a
biosimilars
manufacturing
agreement
Independent: Intas
and Apotex have a
biosimilars
manufacturing
agreement
Hospira
Sandoz
Sandoz
Teva
Teva
2014
2013
2014
2013
2010
2009
2009
2008
2008
Ovaleap
Accofil
Grastofil
Accord Healthcare
Ltd. (UK)
Merckle Biotec
GmbH (Germany)
Finox Biotec AG
(Liechtenstein)
Bemfola
Follitropin Alfa
Follitropin Alfa
Filgrastim
Teva Pharma B.V.
(Netherlands)
Polymun Scientific
Immunbiologische
Forschung GmbH
(Austria)
Finox Biotec AG
(Liechtenstein)
Inflectra
Remsima
Omnitrope
Infliximab
Infliximab
Somatropin
Hospira UK Limited
(UK)
Celltrion Healthcare
Hungary Kft.
(Hungary)
Sandoz GmbH
(Austria)
CELLTRION Inc.
(Korea, A)
1. CELLTRION Inc.
(Korea, A); 2.
CELLTRION Inc.
(Korea, B)
Source: http://www.ema.europa.eu, authors' own research
http://phx.corporate-ir.net/phoenix.zhtml?c=175550&p=irolnewsArticle&ID=1251979&highlight=biosimilars
http://www.norbitec.de/ "Die Norbitec GmbH wurde 2003 als Joint Venture gegründet und ist
ein Unternehmen der BIOCEUTICALS Arzneimittel AG, einer Beteiligungsgesellschaft der
STADA Arzneimittel AG (www.stada.de) und der Nordmark Arzneimittel GmbH & Co. KG
(www.nordmark-pharma.de)."
http://investing.businessweek.com/research/stocks/private/snapshot.asp?privcapId=1019078
http://www.tevapharm.com/Pages/Country.aspx?Country=Lithuania
Sandoz GmbH
(Austria)
Biotec Services
International Ltd.
(UK)
HOSPIRA
Enterprises B.V.
(Netherlands)
Sandoz
Hospira (Licensed
for Europe, some
CIS countries,
United States,
Canada, Australia,
and New Zealand)
Hospira (Licensed
for Europe, some
CIS countries,
United States,
Canada, Australia,
and New Zealand)
2006
2013
2013
Epoetin
Total
Biosimilar
748,455
1,533
717,970
33,630
711,063
69,121
714,455
101,778
710,840
144,250
697,703
178,346
705,153
217,549
730,019
271,389
Filgrastim
Total
Biosimilar
331,180
0
325,665
488
325,082
30,686
347,828
60,576
365,879
73,482
371,185
90,320
377,253
105,341
410,265
128,427
Table 3: Sales by class and year in U.S. Dollars, all sample countries
2007
2008
2009
2010
2011
2012
2013
2014
Somatropin
Total
Biosimilar
434,125
4,125
468,955
14,848
492,552
27,494
520,076
47,666
512,712
68,780
495,092
105,285
452,000
113,080
454,046
131,783
1.09
0.94
0.71
0.59
0.75
0.12
1.41
2.02
0.93
0.97
0.92
0.29
0.46
0.30
0.28
0.13
0.19
0.09
1.35
1.09
0.93
0.70
0.59
0.75
0.12
0.99
1.59
0.64
0.80
0.74
0.15
0.46
0.30
0.27
0.12
0.16
0.09
1.30
2.84
0.87
0.65
0.53
0.69
0.16
0.84
1.00
1.50
1.05
1.00
0.09
All
0.79
1.70%
12.49
0.46
0.30
0.27
0.12
0.16
0.14
1.30
Epoetin Filgrastim Somatropin
Table 4. Policy survey results from European countries: biosimilar procurement details (averages across all years)
IMS Data
Average number of distributors per country year
Average number of products per country year
Average relative price: biosimilar (current) vs. reference product (base year)
Average mid 90% relative price: biosim (current) vs. ref product (base year)
Average relative price: average (current) vs. reference product (base year)
Average fraction of biosimilar sales
Tenders
Average size of tender population (millions)
Country-years with tendering
Country-years for which winner of unit tender gets new patients
Country-years for which winner of unit tender gets all demand
Average tender strength (0 [none] - 1 [winner takes all])
Interaction of tender strength * tender size (millions)
Other incentive and policies
Country-years with non-financial physician pressure to use biosimilar
Country-years with physician financial incentive(s) to use biosimilar
Country-years with any physician education about biosimilars
Country-years with any public/patient education
Country-years with any domestic biosimilar effectiveness study
Country-years with any biosimilar quota
Average number of non-procurement incentives to use biosimilars
Market Size Indicators
GDP (2010 USD$), trillions
Average pharmaceutical expenditure as a % of GDP
National pharma expenditure (billions)
0.208**
(0.024)
0.563**
(0.124)
0.244+
(0.129)
499
0.166
499
0.428
0.195**
(0.020)
0.563**
(0.103)
0.234*
(0.107)
0.670**
(0.045)
499
0.432
0.041**
(0.003)
0.195**
(0.020)
0.563**
(0.102)
0.234*
(0.107)
Table 5: OLS models predicting number of distributors
VARIABLES
Years since biosimilar
approval
Epoetin
Filgrastim
GDP (2010 USD$), trillions
National pharma expenditure
(billions)
Any biosimilar quota
Tender size (fraction of
population)
Strength of tender (0 [none] 1 [winner takes all])
Tender strength * tender size
Number of non-procurement
incentives to use biosimilars
Observations
R-squared
Standard errors in
parentheses
** p<0.01, * p<0.05, + p<0.1
0.042**
(0.003)
0.391**
(0.138)
-0.034
(0.128)
0.329*
(0.129)
0.188**
(0.020)
0.524**
(0.102)
0.210*
(0.106)
0.042**
(0.003)
0.396**
(0.139)
0.314
(0.405)
0.372**
(0.138)
-0.406
(0.449)
0.189**
(0.020)
0.519**
(0.102)
0.207+
(0.106)
499
0.452
0.041**
(0.003)
0.392**
(0.139)
0.304
(0.406)
0.367**
(0.138)
-0.396
(0.450)
0.016
(0.039)
0.188**
(0.020)
0.519**
(0.102)
0.206+
(0.106)
174
0.500
0.046**
(0.006)
0.751**
(0.256)
1.168
(0.790)
0.989**
(0.307)
-1.621+
(0.881)
0.001
(0.075)
Epoetin
0.267**
(0.037)
151
0.492
0.029**
(0.004)
0.067
(0.195)
0.648
(0.548)
0.255
(0.185)
-0.636
(0.611)
0.022
(0.052)
Filgrastim
0.219**
(0.029)
174
0.452
0.048**
(0.005)
0.097
(0.246)
-0.642
(0.647)
-0.041
(0.212)
0.834
(0.710)
0.035
(0.064)
Somatropin
0.085**
(0.031)
499
0.450
499
0.451
Outcome = # of distributors at country-year-biosimilar level
499
0.443
0.040**
(0.003)
0.434**
(0.138)
0.005
(0.127)
All Biosimilars
0.189** 0.189**
(0.020)
(0.020)
0.543** 0.543**
(0.102)
(0.102)
0.231*
0.231*
(0.106)
(0.106)
0.040**
(0.003)
0.434**
(0.138)
499
0.443
0.033
(0.021)
1.006**
(0.098)
0.605**
(0.103)
320
0.261
320
0.431
0.055**
(0.019)
1.076**
(0.086)
0.647**
(0.090)
0.325**
(0.034)
Table 6: OLS models predicting number of products
VARIABLES
Years since biosimilar approval
Epoetin
Filgrastim
GDP (2010 USD$), trillions
National pharma expenditure
(billions)
Any biosimilar quota
Tender size (fraction of population)
Strength of tender (0 [none] - 1
[winner takes all])
Tender strength * tender size
Number of non-procurement
incentives to use biosimilars
Observations
R-squared
Standard errors in parentheses
** p<0.01, * p<0.05, + p<0.1
0.052**
(0.019)
1.061**
(0.088)
0.639**
(0.092)
0.018**
(0.002)
320
0.411
0.017**
(0.002)
0.379**
(0.108)
-0.054
(0.118)
-0.138
(0.114)
0.043*
(0.019)
1.051**
(0.087)
0.647**
(0.091)
0.017**
(0.002)
0.373**
(0.109)
-0.305
(0.419)
-0.162
(0.120)
0.285
(0.456)
0.041*
(0.019)
1.059**
(0.088)
0.655**
(0.092)
320
0.436
0.017**
(0.002)
0.368**
(0.110)
-0.308
(0.419)
-0.168
(0.121)
0.286
(0.456)
0.013
(0.033)
0.041*
(0.019)
1.060**
(0.088)
0.655**
(0.092)
117
0.414
0.031**
(0.005)
0.497*
(0.225)
0.612
(0.764)
0.347
(0.291)
-1.097
(0.853)
0.023
(0.068)
Epoetin
0.053
(0.041)
96
0.335
0.020**
(0.004)
-0.167
(0.220)
-0.593
(0.591)
-0.328
(0.221)
1.077
(0.689)
-0.019
(0.055)
Filgrastim
0.117**
(0.039)
107
0.000
(0.000)
0.000
(0.000)
0.000
(0.000)
0.000
(0.000)
0.000
(0.000)
0.000
(0.000)
Somatropin
0.000
(0.000)
320
0.435
320
0.436
Outcome = # of products at country-year-biosimilar level
320
0.433
0.017**
(0.002)
0.372**
(0.108)
-0.071
(0.117)
All Biosimilars
0.041*
0.041*
(0.019) (0.019)
1.044** 1.041**
(0.086) (0.087)
0.640** 0.638**
(0.090) (0.091)
0.018**
(0.002)
0.364**
(0.107)
320
0.432
270
0.132
-0.009
(0.016)
-0.201**
(0.074)
-0.488**
(0.077)
-0.008
(0.016)
-0.200**
(0.074)
-0.488**
(0.077)
0.000
(0.002)
270
0.133
-0.013
(0.016)
-0.208**
(0.074)
-0.487**
(0.077)
0.000
(0.002)
0.139
(0.086)
270
0.141
270
0.149
0.185+
(0.098)
-0.139
(0.094)
All Biosimilars
-0.009
-0.006
(0.016)
(0.016)
-0.202** -0.188*
(0.074)
(0.074)
-0.489** -0.475**
(0.077)
(0.077)
0.001
0.001
(0.002)
(0.002)
0.168+
(0.097)
270
0.142
270
0.150
0.365
(0.328)
-0.121
(0.099)
-0.206
(0.359)
-0.005
(0.016)
-0.194*
(0.075)
-0.481**
(0.078)
0.001
(0.002)
270
0.150
0.363
(0.328)
-0.124
(0.101)
-0.206
(0.360)
0.005
(0.031)
-0.005
(0.016)
-0.193*
(0.075)
-0.480**
(0.078)
0.001
(0.002)
270
0.159
-0.009
(0.017)
-0.202**
(0.075)
-0.480**
(0.078)
0.001
(0.002)
0.140
(0.088)
0.393
(0.328)
-0.127
(0.101)
-0.259
(0.360)
-0.002
(0.031)
99
0.256
-0.015**
(0.004)
0.461**
(0.148)
0.244
(0.499)
-0.629**
(0.198)
-0.065
(0.557)
-0.005
(0.051)
Epoetin
-0.041
(0.029)
85
0.343
0.004**
(0.001)
0.122*
(0.051)
0.035
(0.134)
0.027
(0.052)
-0.076
(0.156)
-0.037*
(0.015)
Filgrastim
-0.036**
(0.009)
86
0.122
0.009*
(0.004)
0.264
(0.196)
7.790
(6.613)
-0.228
(0.224)
-7.566
(6.608)
0.037
(0.081)
Somatropin
0.049
(0.032)
Outcome = [current price of biosim. / base year price of ref. product] at country-year-biosimilar level
Table 7: OLS models predicting relative (class) price of biosimilar vs. base year reference product price
VARIABLES
Years since biosimilar
approval
Epoetin
Filgrastim
National pharma expenditure
(billions)
Any biosimilar quota
Tender size (fraction of
population)
Strength of tender (0 [none] 1 [winner takes all])
Tender strength * tender size
Number of non-procurement
incentives to use biosimilars
Observations
R-squared
Standard errors in parentheses
** p<0.01, * p<0.05, + p<0.1
307
0.087
-0.028*
(0.012)
-0.075
(0.053)
-0.275**
(0.056)
-0.030*
(0.012)
-0.079
(0.054)
-0.277**
(0.056)
-0.001
(0.001)
307
0.090
-0.036**
(0.012)
-0.090+
(0.053)
-0.277**
(0.055)
-0.002
(0.001)
0.210**
(0.065)
307
0.121
307
0.113
0.157*
(0.072)
0.102
(0.069)
All Biosimilars
-0.031** -0.032**
(0.012)
(0.012)
-0.074
-0.082
(0.053)
(0.053)
-0.274** -0.281**
(0.056)
(0.056)
-0.000
-0.000
(0.001)
(0.001)
0.169*
(0.071)
307
0.107
307
0.114
0.012
(0.253)
0.088
(0.073)
0.165
(0.275)
-0.033**
(0.012)
-0.078
(0.054)
-0.276**
(0.057)
-0.000
(0.001)
307
0.118
0.015
(0.253)
0.101
(0.074)
0.168
(0.275)
-0.024
(0.021)
-0.032**
(0.012)
-0.080
(0.054)
-0.276**
(0.057)
0.000
(0.001)
307
0.146
-0.036**
(0.012)
-0.093+
(0.053)
-0.278**
(0.056)
-0.000
(0.001)
0.203**
(0.065)
0.056
(0.250)
0.102
(0.073)
0.096
(0.272)
-0.033
(0.021)
112
0.322
-0.012**
(0.003)
0.665**
(0.119)
-0.310
(0.403)
-0.205
(0.155)
0.116
(0.449)
-0.086*
(0.037)
Epoetin
-0.079**
(0.022)
92
0.533
0.004**
(0.001)
0.073
(0.049)
0.172
(0.130)
0.036
(0.049)
-0.167
(0.152)
-0.025*
(0.012)
Filgrastim
-0.066**
(0.009)
103
0.203
0.001
(0.002)
-0.005
(0.115)
-5.033
(4.102)
0.113
(0.120)
5.457
(4.099)
0.002
(0.039)
Somatropin
0.012
(0.018)
Outcome = [current average market price / base year price of ref. product] at country-year-biosimilar level
Table 8: OLS models predicting average overall (class) market price per standard unit in current year vs. base year
VARIABLES
Years since biosimilar
approval
Epoetin
Filgrastim
National pharma expenditure
(billions)
Any biosimilar quota
Tender size (fraction of
population)
Strength of tender (0 [none] 1 [winner takes all])
Tender strength * tender size
Number of non-procurement
incentives to use biosimilars
Observations
R-squared
Standard errors in parentheses
** p<0.01, * p<0.05, + p<0.1
0.057**
(0.004)
0.198**
(0.023)
0.084**
(0.024)
499
0.328
0.057**
(0.004)
0.198**
(0.023)
0.084**
(0.024)
0.000
(0.001)
499
0.328
499
0.330
0.056**
(0.004)
0.196**
(0.023)
0.084**
(0.024)
-0.000
(0.001)
0.040
(0.031)
499
0.368
0.029
(0.028)
0.151**
(0.028)
All Biosimilars
0.057** 0.056**
(0.004)
(0.004)
0.200** 0.190**
(0.023)
(0.022)
0.086** 0.077**
(0.024)
(0.023)
0.000
0.001
(0.001)
(0.001)
0.047
(0.029)
499
0.332
499
0.369
-0.051
(0.090)
0.141**
(0.030)
0.094
(0.099)
0.055**
(0.004)
0.191**
(0.023)
0.078**
(0.023)
0.001
(0.001)
499
0.371
-0.058
(0.090)
0.137**
(0.030)
0.101
(0.099)
0.012
(0.009)
0.054**
(0.004)
0.191**
(0.023)
0.077**
(0.023)
0.001
(0.001)
499
0.372
0.054**
(0.004)
0.191**
(0.023)
0.077**
(0.023)
0.001
(0.001)
0.016
(0.031)
-0.056
(0.090)
0.136**
(0.031)
0.099
(0.099)
0.011
(0.009)
174
0.487
0.000
(0.001)
0.041
(0.059)
-0.001
(0.181)
0.314**
(0.070)
-0.081
(0.202)
0.008
(0.017)
Epoetin
0.090**
(0.008)
151
0.328
0.003**
(0.001)
-0.020
(0.045)
0.030
(0.127)
0.063
(0.043)
-0.047
(0.142)
0.028*
(0.012)
Filgrastim
0.042**
(0.007)
174
0.299
0.000
(0.001)
0.051
(0.041)
-0.144
(0.108)
0.010
(0.035)
0.350**
(0.118)
0.005
(0.011)
Somatropin
0.024**
(0.005)
Outcome = biosimilar share of total sales
Table 9: OLS models predicting biosimilar quantity share of total sales
VARIABLES
Years since biosimilar
approval
Epoetin
Filgrastim
National pharma expenditure
(billions)
Any biosimilar quota
Tender size (fraction of
population)
Strength of tender (0 [none] - 1
[winner takes all])
Tender strength * tender size
Number of non-procurement
incentives to use biosimilars
Observations
R-squared
Standard errors in parentheses
** p<0.01, * p<0.05, + p<0.1
2013
Biosimilar'share'of'Epoetin'market,'by'units'sold
2012
2014
Latvia
France
Australia
Slovenia
Lithuania
Germany
Austria
Spain
Norway
Greece
Belgium
Sweden
Poland
Hungary
Bulgaria
UK
Portugal
Ireland
Denmark
Romania
Italy
Finland
0.8
0.6
0.4
0.2
Biosimilar'share'of'Somatropin'market,'by'units'sold
APPENDIX
Figure I. Biosimilar share of total domestic Epoetin/Filgrastim & Somatropin market (standard units) by country, 2007-2014
* Fraction of total standard units that are biosimilar, conditional on biosimilar units > .001 of total units
1.2
1
0.8
0.6
0.4
2011
1.2
2010
0.2
2009
1
2008
0
2007
Slovakia
Bios imilar' s hare' of'Filgras tim' market,' by'units 's old
Denmark
Italy
Finland
2014
Ireland
2013
Bulgaria
2012
Hungary
2011
Belgium
2010
Greece
2009
Austria
2008
Germany
2007
Australia
0
France
Romania
0.7
Finland
Portugal
Italy
Poland
Denmark
Norway
Ireland
Lithuania
Bulgaria
Latvia
2014
Hungary
0.6
2013
Belgium
UK
0.8
2012
Greece
Romania
Sweden
2011
Austria
Portugal
Spain
2010
Germany
Poland
UK
Slovenia
2009
Australia
Norway
Sweden
Slovakia
2008
France
Lithuania
Spain
0.5
2007
Latvia
Slovenia
0.4
0.3
0.2
0.1
0
Slovakia
Total'sales'(1000s'units)'in'Epoetin'market
France
2014
Finland
Lithuania
2013
Denmark
Italy
Slovenia
2012
Bulgaria
Ireland
Slovakia
2011
Belgium
Hungary
Romania
2010
Austria
Greece
Portugal
2009
Germany
Poland
UK
2008
Norway
Sweden
Total'sales'(1000s'units)'in'Filgrastim'market
Greece
Bulgaria
Hungary
Denmark
2012
Ireland
Finland
2013
2011
Austria
Portugal
2010
Germany
Poland
UK
2009
Australia
Norway
Sweden
2008
France
Lithuania
Spain
2014
Spain
2007
2007
Italy
Slovakia
250
200
150
100
50
0
2007
Germany
Belgium
Hungary
Bulgaria
Italy
Denmark
2013
Austria
2012
France
Portugal
2011
Australia
Poland
UK
2010
Finland
Norway
Sweden
2009
Latvia
Spain
Romania
Slovenia
2008
Total'sales'(1000s'units)'in'Somatropin'market
Figure II. Total sales in domestic Epoetin/Filgrastim/Somatropin markets (1000s units), 2007-2014
* Total biosimilar sales, conditional on biosimilar units > .001 of total units
1800
1600
1400
1200
800
1000
600
400
0
200
600
500
400
300
200
100
0
Romania
2014
Total'sales'(1000s'dollars)'in'Epoetin'market
France
2014
Finland
Lithuania
2013
Denmark
Italy
Slovenia
2012
Bulgaria
Ireland
Slovakia
2011
Belgium
Hungary
Romania
2010
Austria
Greece
Portugal
2009
Germany
Poland
UK
2008
Norway
Sweden
2007
Spain
Total'sales'(1000s'dollars)'in'Filgrastim'market
O
50000
45000
40000
35000
30000
25000
20000
15000
5000
10000
2013
Total'sales'(1000s'dollars)'in'Somatropin'market
2012
Denmark
2011
Italy
2010
Bulgaria
2009
Hungary
2008
Belgium
0
Germany
2007
Figure III. Total sales in domestic Epoetin/Filgrastim/Somatropin markets (1000s dollars), 2007-2014
* Total biosimilar sales, conditional on biosimilar units > .001 of total units
140000
120000
100000
80000
60000
40000
20000
0
45000
40000
35000
Austria
30000
France
2014
Finland
Finland
Australia
25000
Ireland
Romania
Denmark
Portugal
Portugal
Hungary
Poland
20000
Bulgaria
Poland
Norway
2013
Greece
Latvia
2012
Austria
Norway
15000
2011
O
UK
2010
Germany
UK
Sweden
2009
Australia
Lithuania
Sweden
Spain
2008
France
Spain
Slovenia
2007
Italy
Slovakia
10000
5000
0
Romania
2014
2007
2007
Relative'(unit)'price'of'Epoetin'biosimilars
vs.'base'year'reference'product'price
Denmark
Italy
Finland
2014
Bulgaria
Ireland
Romania
2013
Belgium
Hungary
Portugal
2012
Austria
Greece
Poland
UK
2011
Australia
Germany
Norway
Sweden
2010
France
Lithuania
Spain
2009
Latvia
Slovenia
2008
Slovakia
Relative'(unit)'price'of'Filgrastim'biosimilars
vs.'base'year'reference'product'price
Hungary
Bulgaria
Ireland
Denmark
Italy
Finland
2014
Belgium
2013
Greece
Romania
2012
Austria
Portugal
2011
Germany
Poland
UK
2010
Australia
Norway
Sweden
2009
France
Lithuania
Spain
2008
Latvia
Slovenia
6
5
4
3
2
1
0
2007
Belgium
Hungary
Bulgaria
Ireland
Denmark
Italy
Finland
2014
Greece
2013
Austria
Portugal
2012
Germany
Poland
UK
2011
Australia
Norway
Sweden
2010
France
Lithuania
Spain
2009
Latvia
Slovenia
Romania
Slovakia
2008
Relative'(unit)'price'of'Somatropin'biosimilars
vs.'base'year'reference'product'price
Figure IV. Relative prices: biosimilar vs. base year reference product price, Epoetin/Filgrastim/Somatropin, 2007-2014
* Relative prices, conditional on biosimilar units > .001 of total units
3.5
3
2.5
2
1.5
1
0.5
0
1.2
1
0.8
0.6
0.4
0.2
0
Slovakia
2007
2007
Relative'(unit)'price'of'Epoetin'biosimilars
avg'current'mkt'price'vs.'base'year'ref'product'price
Denmark
Italy
Finland
2014
Bulgaria
Ireland
Romania
2013
Belgium
Hungary
Portugal
2012
Austria
Greece
Poland
UK
2011
Australia
Germany
Norway
Sweden
2010
France
Lithuania
Spain
2009
Latvia
Slovenia
2008
Slovakia
Relative'(unit)'price'of'Filgrastim'biosimilars
avg'current'mkt'price'vs.'base'year'ref'product'price
Hungary
Bulgaria
UK
Portugal
Ireland
Denmark
Romania
Italy
Finland
2014
Belgium
Poland
2013
Greece
Sweden
2012
Austria
Norway
2011
Germany
Spain
2010
Australia
Lithuania
2009
France
Slovenia
2008
Latvia
3
3.5
2.5
2
1
1.5
0.5
0
2007
Relative'(unit)'price'of'Somatropin'biosimilars
avg'current'mkt'price'vs.'base'year'ref'product'price
Italy
Finland
2013
Denmark
Romania
2012
Ireland
2011
Bulgaria
Portugal
2010
Belgium
Hungary
2009
Austria
Poland
2008
Australia
Greece
UK
Norway
Sweden
Germany
Spain
Lithuania
Slovenia
Latvia
Slovakia
France
2014
Figure V. Relative prices: average market price in current year vs. base year ref product price, Epoetin/Filgrastim/Somatropin, 2007-2014
* Relative prices, conditional on biosimilar units > .001 of total units
4
3.5
3
2
2.5
1
1.5
0.5
0
1.4
1.2
1
0.8
0.6
0.4
0.2
0
Slovakia
Table I. Biosimilar products, European markets, 2007-2014
1
# of countries ever Countries of entry
experiencing entry
Epoetin Alfa Hexal
19
Product names
Binocrit
Germany
Austria, Belgium, Bulgaria,
Finland, France, Germany,
Greece, Hungary, Ireland, Italy,
Lithuania, Poland, Portugal,
Romania, Slovakia, Slovenia,
Spain, Sweden, UK
Austria, Germany, Greece, Italy,
Poland, Slovakia
Total
Distributors in
MIDAS
dataset
1
4
6
Country, # of cases in which
distributors > EMA mfg. approvals
Novartis (all)
CC Pharma, EMRA-Med,
Eurimpharm (Germany); Novartis (all
others)
Cambridge Major, Eurimpharm,
Gerke Pharma, Orifarm (Germany);
Fidia (Italy); Medice (Austria,
Germany, Greece, Poland, Slovakia)
Stada (all/Germany)
6
1
Hospira (all), Orifarm (Germany)
Abseamed
2
Aspen (Australia); Teva (all)
1
2
Teva (all)
Silapo
Australia, UK
1
Novartis (all/Germany + UK)
-
19
2
Austria, Denmark, Finland,
France, Germany, Hungary,
Ireland, Italy, Norway, Slovakia,
Spain, Sweden, UK
1
-
Retacrit
Tevagrastim
13
Germany, UK
-
Germany
Austria, Bulgaria, Denmark,
Finland, France, Germany,
Greece, Hungary, Ireland, Italy,
Norway, Poland, Portugal,
Romania, Slovakia, Slovenia,
Spain, Sweden, UK
Ratiograstim
2
-
Biograstim
Zarzio
Filgrastim Hexal
Nivestim
Omnitrope
19
19
Australia, Austria, Belgium,
Bulgaria, Denmark, Finland,
France, Germany, Hungary, Italy,
Latvia, Norway, Poland, Portugal,
Romania, Slovenia, Spain,
Sweden, UK
Australia, Austria, Bulgaria,
Finland, France, Germany,
Greece, Hungary, Ireland, Italy,
Lithuania, Norway, Poland,
Portugal, Romania, Slovakia,
Spain, Sweden, UK
11
3
ACA Mueller, AxiCorp Pharma, CC
Pharma, Concept Pharma, EMRAMed, EurimPharm, Kohl Medical
AG, OriFarm (Germany);
Medartuum, Pharmachim (Sweden);
Novartis (Australia, Austria, Belgium,
Bulgaria, Denmark, Finland, France,
Germany, Hungary, Italy, Latvia,
Norway, Poland, Portugal, Romania,
Slovenia, Spain, Sweden, UK )
Hospira (all); Abacus Medicine,
Cross Chemicals (Germany)
Source: http://www.ema.europa.eu, MIDAS, authors' own analysis
Table II. List of sample countries with first year of biosimilar entry* in each market, 2007-2014
Epoetin Filgrastim Somatropin
2012
2007
2008
2009
2009
2009
2011
2011
2012
2010
2009
2011
2008
2010
2008
2009
2009
2007
2007
2008
2007
2008
2011
2009
2009
2012
2008
2009
2009
2009
2007
2009
2010
2012
2008
2009
2012
2009
2012
2008
2010
2011
2009
2011
2008
2010
2009
2009
2010
2009
2009
2007
2008
2009
2007
2009
2008
2007
2007
2008
2006
2008.9
2009.8
2008.7
Australia
Austria
Belgium
Bulgaria
Denmark
Finland
France
Germany
Greece
Hungary
Ireland
Italy
Latvia
Lithuania
Norway
Poland
Portugal
Romania
Slovakia
Slovenia
Spain
Sweden
UK
First Approval
Average Year of Entry (all countries)
Average Year of Entry (countries with
any biosimilar industry)
2009.4
2010.3
2009.3
Average Year of Entry (countries
without any biosimilar industry
2009.0
2009.8
2008.9
*conditional on biosimilar units > .001 of total domestic units sold
Table III. Manufacturers’ parent companies or joint ventures, European markets, 2007-2014
Manufacturer(s) as listed in EMA approval documents
Manufacturer is subsidiary or joint venture of
CELLTRION Inc.
Licensed by Hospira
Hospira Zagreb d.o.o.
Hospira
Intas Pharmaceuticals Ltd. (India)
Independent biosimilars manufacturing agreement
Lek Pharmaceuticals d.d.
Sandoz
Merckle Biotec GmbH (Germany)
Teva
Norbitec GmbH
Bioceuticals, Stada, Nordmark
Polymun Scientific Immunbiologische Forschung GmbH (Austria)
Independent
Rentschler Biotechnologie GmbH
Independent
Sandoz GmbH
Sandoz
SICOR Biotech UAB
Teva
Source: http://www.ema.europa.eu, authors' own research
http://phx.corporate-ir.net/phoenix.zhtml?c=175550&p=irolnewsArticle&ID=1251979&highlight=biosimilars
http://www.norbitec.de/ "Die Norbitec GmbH wurde 2003 als Joint Venture gegründet und ist ein Unternehmen der BIOCEUTICALS
Arzneimittel AG, einer
Beteiligungsgesellschaft der STADA Arzneimittel AG (www.stada.de) und der Nordmark Arzneimittel GmbH & Co. KG (www.nordmarkpharma.de)."
http://investing.businessweek.com/research/stocks/private/snapshot.asp?privcapId=1019078
http://www.tevapharm.com/Pages/Country.aspx?Country=Lithuania
http://www.prnewswire.com/news-releases/hospiras-inflectra-infliximab-the-first-biosimilar-monoclonal-antibody-to-be-approved-in-europe223098561.html
258
0.133
0.001
(0.084)
-0.190+
(0.098)
-0.486**
(0.079)
0.003
(0.106)
-0.192+
(0.116)
-0.486**
(0.080)
-0.000
(0.004)
258
0.134
0.037
(0.089)
-0.227*
(0.105)
-0.489**
(0.079)
-0.002
(0.004)
0.096
(0.091)
258
0.137
0.005
(0.105)
-0.195+
(0.116)
-0.487**
(0.079)
0.000
(0.004)
0.043
(0.107)
-0.216+
(0.116)
-0.479**
(0.079)
-0.001
(0.004)
0.040
(0.106)
-0.219+
(0.116)
-0.487**
(0.080)
-0.001
(0.004)
0.363
(0.324)
-0.099
(0.104)
-0.243
(0.354)
-0.015
(0.032)
0.047
(0.108)
-0.227+
(0.118)
-0.491**
(0.081)
-0.001
(0.004)
258
0.136
0.087
(0.088)
-0.267*
(0.105)
-0.497**
(0.081)
-0.003
(0.004)
0.092
(0.092)
0.391
(0.326)
-0.107
(0.104)
-0.286
(0.358)
-0.022
(0.032)
All Biosimilars
0.135
(0.098)
0.149
(0.098)
-0.131
(0.097)
0.362
(0.323)
-0.107
(0.102)
-0.244
(0.354)
258
0.146
258
0.145
258
0.147
258
0.140
95
-0.029**
(0.007)
0.224
(0.197)
0.104
(0.587)
-0.744**
(0.242)
0.135
(0.663)
-0.051
(0.062)
0.309*
(0.131)
Epoetin
82
0.007+
(0.004)
0.053
(0.065)
-0.134
(0.234)
-0.057
(0.077)
0.183
(0.305)
-0.038
(0.023)
-0.223
(0.214)
Filgrastim
81
0.103
0.006
(0.008)
0.280
(0.194)
6.566
(6.495)
-0.156
(0.226)
-6.365
(6.494)
0.052
(0.082)
0.039
(0.175)
Somatropin
Outcome = [current price of biosim. / base year price of ref. product] at country-year-biosimilar level
Table IV: Instrumental variables models predicting average overall (class) market price per standard unit in current year vs. base year,
instrumenting for the number of distributor entrants using 2007 index of other biologic drug prices
VARIABLES
Number of distributors at
country year class level
Epoetin
Filgrastim
National pharma expenditure
(billions)
Any biosimilar quota
Tender size (fraction of
population)
Strength of tender (0 [none] - 1
[winner takes all])
Tender strength * tender size
Number of non-procurement
incentives to use biosimilars
Observations
R-squared
Standard errors in parentheses
** p<0.01, * p<0.05, + p<0.1
258
0.133
0.002
(0.179)
-0.191
(0.219)
-0.487**
(0.143)
0.005
(0.226)
-0.197
(0.279)
-0.490**
(0.173)
-0.000
(0.004)
258
0.132
0.070
(0.170)
-0.278
(0.212)
-0.532**
(0.142)
-0.001
(0.003)
0.084
(0.106)
258
0.115
0.011
(0.226)
-0.204
(0.280)
-0.494**
(0.173)
0.000
(0.004)
0.081
(0.204)
-0.278
(0.257)
-0.530**
(0.163)
-0.001
(0.004)
0.074
(0.200)
-0.276
(0.256)
-0.535**
(0.165)
-0.001
(0.004)
0.089
(0.209)
-0.296
(0.267)
-0.549**
(0.172)
-0.001
(0.004)
0.146
(0.151)
-0.371+
(0.197)
-0.590**
(0.138)
-0.002
(0.003)
0.068
(0.106)
0.476
(0.346)
-0.063
(0.112)
-0.362
(0.374)
-0.023
(0.033)
95
0.010
-0.027**
(0.006)
0.286
(0.175)
0.177
(0.549)
-0.696**
(0.223)
0.087
(0.620)
-0.053
(0.059)
0.360*
(0.143)
Epoetin
82
0.058
(0.662)
-0.271
(4.133)
-4.087
(50.269)
-1.946
(23.446)
5.287
(65.233)
0.030
(0.997)
-3.586
(43.793)
Filgrastim
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
n.a.
Somatropin
All Biosimilars
0.136
(0.102)
0.158
(0.102)
-0.113
(0.100)
0.409
(0.354)
-0.087
(0.109)
-0.288
(0.380)
0.419
(0.357)
-0.074
(0.114)
-0.296
(0.383)
-0.017
(0.034)
258
0.088
258
0.119
258
0.118
258
0.137
258
0.124
Outcome = [current price of biosim. / base year price of ref. product] at country-year-biosimilar level
Table V: Instrumental variables models predicting average overall (class) market price per standard unit in current year vs. base year,
instrumenting for the number of product entrants using 2007 index of other biologic drug prices
VARIABLES
Number of Intl Products at
country year class level
Epoetin
Filgrastim
National pharma expenditure
(billions)
Any biosimilar quota
Tender size (fraction of
population)
Strength of tender (0 [none] - 1
[winner takes all])
Tender strength * tender size
Number of non-procurement
incentives to use biosimilars
Observations
R-squared
Standard errors in parentheses
** p<0.01, * p<0.05, + p<0.1
Table VI. List of individuals/organizations that assisted with policy survey
Andreja Jerina, The Directorate for Health, Sector for the development of health care, Slovenian Health Ministry, Slovenia
Carlos Lens, Pharmacy Deputy Director in the Ministry of Health, Social Services and Equality (MSSSI), Spain
Claire Biot, Director at Agence Générale des Equipements et Produits de Santé (AGEPS) AP-HP, France
Dr Maria Skouroliakou, Assistant Professor of Enteral and Parenteral Nutrition, School of Health Science & Education, Greece
Dr. Helder Mota Filipe, Associate Professor of Pharmacology and Therapeutics and Vice-President of Executive Board, INFARMED (National
Authority of Medicines and Health Products, IP Portugal), Portugal
Dr. Fernando de Mora, Universitat Autònoma de Barcelona, Spain
Gustaf Befrits, Administrator in Pharma department of Stockholm County Council, Sweden
Hannes Enlund, FIMEA (Finnish Medicines Agency), Finland
Helga Festoy, Norwegian Medicines Agency, Norway
Italian Medicines Agency, Italy
Jens Ersboll, Danish Medicines Agency, Denmark
Karen Binnekamp, Pricing area of Department of Health, administer pharmaceutical benefit scheme (PBS), Australia
Maria Isabel Farfan, Expert economist, Belgium
Matthias Diesel, Head of Market Access, Pro Generika, Germany
Ministry of Health, Poland
Monika Lainczova, Manager of Drug Policy Deparment, Dovera Health Insurance Company, Slovakia
National Agency, Denmark
Pablo Serrano, Federal Association of the Pharmaceutical Industry BPI (Bundesverband der Pharmazeutischen Industrie e.V.), Germany
Roger Purcell, National Health Service, UK
Sabine Vogler, Gesundheit Österreich GmbH, Austria
Sandoz, Slovenia
Stanislav Primozic, Deputy Director of JAZMP, Slovenia
VFA Bio, Germany
Table VII: Legal requirements for a new biosimilar application to the EMA
Administrative data
Summary of product characteristics
Expert reports
Qualitative and quantitative particulars of the constituents.1
Description of manufacturing method
Controls of starting materials
Specific measures concerning the prevention of the transmission of animal spongiform encephalopathies
Control tests carried out at intermediate stages of the manufacturing process
Control tests on the finished product (including general characteristics of the finished product, identification and assay of active substance(s),
identification and assay of excipient constituents, safety tests)
Stability and toxicity tests
Examination of reproductive function and embryo/foetal and perinatal toxicity tests
Tests of mutagenic potential, carcinogenic potential
Data on pharmacodynamics and pharmacokinetics
Local tolerance tests
Well-established medicinal use
Conduct of trials
Presentation of results
Clinical pharmacology
Bioavailability/bioequivalence
Clinical efficacy and safety
Documentation for applications in exceptional circumstances
Post-marketing experience
Well-established medicinal use
The legal requirements of a new biosimilar application include all of the following:
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1 Active substances present in the form of compounds or derivatives shall be designated quantitatively by their total mass, and if necessary or relevant, by the mass of the active entity or
entities of the molecule. For allergen products, the quantitative particulars shall be expressed by units of biological activity, except for well-defined allergen products for which the
concentration may be expressed by mass/unit of volume.