Author: Dr. Andrew J. Reason
As FDA and EMA guidance continues to reinforce analytical comparability as the foundation of biosimilar development, investing in comprehensive early-stage characterization is becoming essential to reduce uncertainty and improve development outcomes, says Dr Andrew J. Reason, CEO at BioPharmaSpec
Regulatory expectations are driving a significant shift in biosimilar product optimization. This poses a challenge for biosimilar developers who must generate robust analytical datasets that demonstrate biosimilarity with a high degree of confidence.
The latest development reflecting this shift is the EMA’s “Reflection Paper on a Tailored Clinical Approach in Biosimilar Development,” which highlights the growing importance of structural and physicochemical characterization of the biosimilar product, with a reduced reliance on clinical studies and the analysis of multiple batches of the innovator or reference medicinal product (RMP) in the evidence package supporting biosimilarity.
Before the development and comparability assessment of a biosimilar product can begin, a suitable cell line or clone must be selected for recombinant manufacture.
Historically, this decision has largely been based on which cell line yields the highest cell titer and product volume or on an initial analytical assessment followed by a cursory evaluation of product functionality.
This is largely because the sheer number of cell line/clone candidates in the initial comparison matrix has made a more thorough analysis too time-consuming.
Until recently, generating a broad dataset across the full range of required structural and physicochemical attributes was not feasible, as the necessary analytical equipment was either unavailable or inadequate.
The best decisions in early phase biosimilar development (particularly when large numbers of sample matrices are produced) are based on the broadest understanding of the product's structure and physicochemical properties. Historically, generating this level of information within large sample sets has been impractical owing to limitations in analytical throughput and data processing.
With the technologies and data handling processes now available, high-quality data can be generated by analyzing large numbers of samples in short timeframes, enabling more informed early-stage decision-making.
Too many products have failed in the later stages of development simply because early decisions were based on minimal data.
To support a more informed process, analytical strategies should deliver high-quality data across the required structural attributes. At BioPharmaSpec, this is achieved with a combination of complementary analytical platforms that generate comprehensive structural and physicochemical datasets within development-relevant timelines:
In summary, it is now possible to obtain in-depth structural data about a product’s critical quality attributes. This enables more informed decisions about the best cell line or clone to use to manufacture the product in a time- and cost-effective way.
As such, decisions are based on data rather than intuition, supporting early product development and significantly reducing any risks related to biosimilar comparability and product quality.
This article, by Dr. Andrew J. Reason, was originally published in Manufacturing Chemist (July/August 2026) and is reproduced here with permission.
