- Biosimilar drugs are non-generic alternatives to traditional biologic medicines, that sell at a fraction of the price.
- Scrutiny of pay-to-delay cases in the pharmaceutical market has increased following the emergence of biosimilars competing with complex biologic medicines.
- In this Research Alert, Fideres outlines two methodological frameworks to estimate damages from pay-to-delay cases involving biosimilars.
What are Biosimilars?
Differences Between Branded-Generics and Biologic-Biosimilars
A biosimilar is a biological medicine that is highly similar to another biological medicine already licensed for use. Biosimilars are developed to be clinically equivalent in efficacy to their biological reference drugs. Biologic drugs are “grown” using biologic processes involving living cells, organisms, or tissues. Currently it is not possible to make an exact copy of a biologic drug using different cells or tissues. Generics, on the other hand, are manufactured by chemical processes, which can be copied by other firms to produce an identical active ingredient.1
McKinsey estimates that the global biosimilars market will triple in sales from $5 billion in 2017 to $15 billion by 2020.2 Comparatively, the US generic drug market reached a value of more than $93 billion in 2017 and is forecast to grow to more than $123 billion by 2023.3
According to the American Bar Association, generic competitor drugs provide significant consumer savings. The first generic typically enters the market at a price 20%-30% lower than that of brand-name counterparts, and subsequent generics enter at prices as much as 80% lower.4 The limited data available on biosimilar competition suggests a more modest price impact than what the generic market has seen, as shown in the table below.
|Biosimilar / Generic Name||Share of Sales Captured||Share of Sales Captured|
|Zarxio: biosimilar to Neupogen (2 years post launch)||34%||15%|
|Granix: quasi-biosimilar to Neupogen (4 years post launch)||25%||21%|
|Inflectra: biosimilar to Remicade (1 year post launch)||4%||15%|
|Generic Drug Average (1 year post launch)||88%||78%|
Source: Biosimilar drug outcomes, Symphony Health Solutions. Generic Drug Average, Grabowski et al. (2016)
US FDA Approved Biosimilars
Although the Food and Drug Administration (FDA) has approved 16 biosimilar drugs, as of March 2018, there were only 7 biosimilar products available in the US market. In comparison, the European market featured 14 biosimilars in a comparable timeframe.5
|Biosimilar||FDA Approval||Biologic Referenced To||Biosimilar||FDA Approval||Biologic Referenced To|
*Approved and Launched on the US Market
Impact of Pay-to-Delay Deals on Biosimilars
Reverse payments or “pay-to-delay” settlements are a form of patent litigation in which a manufacturer of a biologic (or branded) drug pays its potential biosimilar (or generic) competitor to abandon a patent challenge and delay entering the market with a lower cost drug.
As biosimilar drugs tend to enter the market at a lower price than the biologic, the price competition upon entry of a biosimilar is beneficial for the end-consumer.
Pay-to-delay agreements, however, can be anticompetitive as the innovator manufacturer enjoys monopoly profits for a longer period than the patent protection should allow. This may lead to insurers and (indirectly) consumers paying higher-than-necessary prices for the biologic drug.
Recent news relating to anticompetitive conduct involving biosimilars are:
- On 28 January 2019, the European Commission released their findings on ‘Competition Enforcement in the Pharmaceutical Sector (2009-2017)’. The report mentions the growing relevance of biosimilars and asks authorities to “remain vigilant and proactive in investigating anti-competitive situations”.
- AbbVie, the manufacturer of Humira, one of the highest revenue generating drugs, entered into an agreement with Amgen and Samsung to delay the entry of their biosimilars until 2023. In response to increased competition in Humira’s European market, in October 2018, AbbVie cut the price of Humira by 80% to win a government tender and maintain a hold in the European market, according to Bernstein analysts.6
- In 2017, Pfizer filed an antitrust complaint against Johnson & Johnson over the insurance contracts of its biologic rheumatoid arthritis drug, Remicade. Pfizer claims that the contracts are anticompetitive and block the sale of their new biosimilar drug.
- The US Senate passed a bill in September, 2018, revising existing law to require the disclosure of settlements reached between biologic and biosimilar developers to the Federal Trade Commission (FTC). This bill expands the FTC’s powers to scrutinize pay-to-delay agreements.
How to Estimate Damages?
There is a large literature on damages modelling for cases involving generic drug pay-to-delay settlements. There are two broad classes of model that have been used in the literature on generic drugs, both of which can be adapted to the case of biosimilars.
Nash Bargaining Models
The first class of model is grounded in game theory and can be referred to as a “Nash bargaining model”. The key determinant of whether the settlement is made is both side’s perception of the strength of the branded drug’s patent.
To estimate prices absent the settlement, two approaches are possible. One method involves assumptions about perceived patent strength to solve for expected payoffs under duopoly and monopoly retrospectively. It is also possible to estimate expected payoffs for each firm using internal transaction data or firm profit projections. Finally, market-structure models, such as Cournot and Bertrand bargaining models, can be used to infer expected payoffs without the settlement in the absence of price data. Using these estimates, we can quantify direct purchaser damages as:
|Damages = (Actual Price - But-for Price) * Quantity Purchased|
- This framework uses a bargaining model determine patent strength of the originator firm
- The model allows us to conduct a counterfactual but-for analysis of the market impact of the biosimilar drug had it launched without delay
Time Series Regression Models
Grabowski et al (2007) propose a different approach to estimating cost savings as a result of the entry of generics. Their regression model captures important changes after the introduction of generics, such as:
- How many generic competitors entered the market and when
- How prices for the branded drug responded to generic entry
- How total consumer spending on the branded drugs and related generics responded to patent expiry
Their model can, in principle, be adapted to predict the timing of biosimilar entry and related cost savings.
Data can be used from real-life biosimilar cases to model the competitive dynamics of a market more accurately. This data along with secondary literature can be used to better estimate fixed costs in this industry. A wider range of biosimilars has also entered the European market, which offers a possible larger sample to model market dynamics for this case.
1 Zangeneh, Farhad, M.D., and Richard Dolinar M.D. “BIOSIMILAR DRUGS ARE NOT GENERICS.” Endocrine Practice 22.1 (2016): 6-7.
5 Frank, Richard G., PhD. “Friction in the Path to use of Biosimilar Drugs.” The New England journal of medicine 378.9 (2018): 791-3.
Max joined Fideres in 2016. He has led the development and implementation of economic models for major collective actions in the US and the UK, contributing to litigation on a variety of topics. His reports and econometric work has been included in cases for conduct including, among others, the FX and LIBOR benchmark manipulation, digital market monopolization by Apple and Amazon, and consumer claims against a cartel of US generic drug manufacturers, abuse of market power by large regional US hospital systems, restriction of the right to repair by John Deere, and the combined abuse of dominance by Visa and Mastercard in UK payment systems. Before joining Fideres, Max worked at the national laboratory in Los Alamos, New Mexico, as part of a team designing neural networks for applications in machine learning. Max holds an MSc in Economic History from the London School of Economics.