Biosimilars Intensify the Need for Harmonized Data

When complexity and competition compete with similarity

To get the most out of recent innovations in biopharma development and QC such as multi-attribute monitoring, it’s time to better connect the systems that manage biopharma data. This series explores the what, the why, and the how of better biopharma data.

To understand this key emerging area of biopharma, let’s start with a broad data picture of biosimilars:

• Number of atoms in one aspirin molecule: 25
• Number of atoms in one monoclonal antibody (mAb) molecule: ~25,000¹
• Development time for an innovator biologic (Infliximab): ~10-12 years²
• Development time for Infliximab biosimilar (Infliximab-abda): ~7 to 8 years³
• Discount of first FDA-approved biosimilar (Infliximab-dyyb), compared to Infliximab: 15%
• Discount of second FDA-approved biosimilar (Infliximab-abda), compared to Infliximab: 35%⁴
• Number of Infliximab biosimilars in development: 17
• Total number of biosimilars currently in development: ~700⁵

Three things stand out in this picture: the complexity of the molecules, declining prices for biosimilars, and increasing competition to make them. And this is still the early days of the sea of change biosimilars are bringing to the industry. The FDA is taking steps to smooth the approval process for these drugs and educate physicians about their use.⁶ And so far, originators are failing in their efforts to halt or slow biosimilars’ path to market through patent litigation.⁷

Revisit part 1: Biopharma Data: Chaos or Harmony?

What will happen when more infliximab biosimilars get approved? No rule says the discount has to stop at 35%. In Norway, for example, one infliximab biosimilar goes for 70% less than its reference product, a move that has enabled its distributor to capture 50% of the market.⁸

Of course, at a certain point a harsh reality will set in for some of the seventeen infliximab biosimilar development efforts. As prices fall, the potential profits will no longer justify the roughly $100-$250 million in estimated development costs (compared to $1 to $4 million to develop a small molecule generic product), and the companies involved will pull the plug on their programs.³ This has already been observed with a simpler bacterial derived biosimilar, filgrastim, in the EU. Of the nine filgrastim biosimilars approved in the EU, two are already off the market.⁹

Biosimilars represent a race by many competitors to bring a complex, high quality product to market. And the companies that so far seem to be winning have made a key investment: process innovation. And behind those advances in streamlining and controlling the process are improvements in gathering and managing data.

The process is the product, and the data reflects the process

The key to getting a biosimilar to market lies in establishing similarity to its reference molecule. That means demonstrating similar clinical performance. It also means giving regulators a detailed data package on the molecule’s structure and biology, the process used to make it, and the ongoing QC techniques that will ensure the quality, safety, and efficacy of each batch.

For example, Samsung Bioepis presented a robust set of 29 product quality attributes to show comparability between its candidate molecule and Infliximab.¹⁰ These included the molecule’s:

• Primary structure
• Glycosylation
• Cytotoxicity
• Binding activity

The full range of these 29 attributes represent measurements from about 25 different assays, utilizing about 15 different techniques ranging from structural characterization to cell-based assays. This represents only a portion of the data generated during the characterization process development of the molecule.¹⁰ All in all, that’s a huge amount of data to process, analyze, and integrate.

One key to presenting such a broad range of quality attributes included a multi-attribute monitoring approach using liquid chromatography/mass spectrometry techniques. For example, much of the structural information such as amino acid sequence, terminal sequence, and deamidation came from one LC-MS assay.¹⁰ This offers efficiency in merging multiple assays into one, though still poses a considerable data challenge—producing gigabytes per day and terabytes per month to store and analyze.

Winning the data race in biosimilars

However complex the analytical data supporting a biosimilar may be, it has to exist within and support the full context of a development program. This means multiple people–both inside and outside labs–must understand the data as it relates to the changing market, the internal benchmarks a company has set for go/no-go decisions, and the need to show tight quality parameters to regulators.

Biosimilars provide an acid test for how efficient drug development can become. The drug makers who can best integrate product quality data will get the best understanding of their molecule where it matters: across different structural and biological attributes, across early- to late-stage development and commercialization phases, and across the different contractors or facilities that may be involved in development or manufacturing.

That efficiency isn’t only about reducing delay, errors, or regulatory setbacks. Gaining a more comprehensive and integrated understanding of your molecule–and your process–gives you the ability to innovate. For example, by demonstrating quality and comparability thoroughly, Samsung Bioepis showed they could make their biosimilar using a CHO expression system, rather than the murine system used for Infliximab.¹⁰ When CHO-based systems can produce titers up to ten times higher than murine systems, this has a huge potential to increase production efficiency.

Other potential innovations that biosimilar makers are pursuing – and supporting through more integrated data–include single-use or continuous manufacturing models, real-time monitoring, improved culture media, and process automation.

Next in this blog series, we’ll take a look at what biopharma’s data systems could become—and what they could do for you.

Visit legacy-stage.waters.com/tamethechaos for more information.

References:

1. Otto R, Santagostino A, and Schrader U. Rapid growth in biopharma: Challenges and opportunities. McKinsey & Co. Dec 2014.
2. PhRMA. Biopharmaceutical Research & Development: The Process Behind New Medicines. 2015.
3. Blackstone EA, Joseph PF. The Economics of Biosimilars. American Health & Drug Benefits. 2013;6(8):469-478.
4. Nisen M. “Merck, Samsung Accelerate A Biosimilar Price War.” BloombergGadfly. July 2017.
5. Reinke T. “Biosimilars: The Pipeline Seams Seem To Be Bursting.” Managed Care. March 2017.
6. Gottlieb S and Christi L. “FDA Taking New Steps to Better Inform Physicians about Biosimilars Through Education about these Potentially Cost-Saving Options.” FDA Voice. Oct 2017.
7. Lee J. “Janssen drops U.S. lawsuit against Samsung Bioepis’ Remicade copy.” Reuters. Nov 2017.
8. Palmer E. “Deep discounts allow Remicade biosimilar to grab 50% of Norway’s market.” FiercePharma. Apr 2015.
9. “Biosimilars approved in Europe,” Gabionline.net. August 7, 2011. Web. Last modified October 6, 2017,
10. Hong J, Lee Y, et al.  Physicochemical and biological characterization of SB2, a biosimilar of Remicade® (infliximab). mAbs. 2017; 9 (2): 365-383.

Related:

• Part Three: From the Results of Yesterday to the Biologic Drugs of Tomorrow
• Part One: Biopharma Data: Chaos or Harmony?
• From Characterization to Late Development, Manufacturing, and QC: The Expanding Role of Mass Spectrometry in Biotherapeutics