A biosimilar is a biological product that is highly similar to and has no clinically meaningful differences from an existing FDA-approved reference product.
If you want to bring a biosimilar to market, you’ll need to demonstrate that it is highly similar to the reference product in both structure and function.
However, since biologics are derived from living organisms, they are usually large, complex, and variable molecules, making it difficult to establish a process that can produce a biosimilar molecular entity identical to the reference product in a reproducible fashion.
According to the FDA, the evaluation and approval of a proposed biosimilar should be based on the totality-of-evidence approach. This means that FDA will consider all data and information in the application from analytical studies, nonclinical evaluation, human PK and PD data, clinical immunogenicity data, and comparative clinical studies data.
To support the demonstration of biosimilarity the FDA recommends a stepwise approach for obtaining the totality-of-the-evidence. In this approach, the analytical similarity assessment plays a key role and, as the FDA states, it must be based on an extensive analysis of the structure and function of both the reference product and the proposed biosimilar using state of the art technology.
Because of that, this blog post will focus on this assessment for biosimilars and how you can streamline it.
The stepwise approach and the importance of Analytical Similarity Assessments
The stepwise approach recommended by the FDA starts with an analytical similarity assessment. In fact, this assessment based on structural and functional analyses is the foundation of a biosimilar development program.
According to the FDA, the more comprehensive and robust this comparative structural and functional characterization is, the more useful it will be in determining which additional studies may be needed.
Additionally, with this assessment you can also demonstrate if any molecular or functional difference is clinically relevant or not. This demonstration is performed in terms of CQAs that are relevant to clinical outcomes. The relationship between these attributes and the clinical safety and efficacy helps to determine residual uncertainty about biosimilarity.
But how do you perform these analytical studies? Let’s find out!
Analytical Similarity Assessment: a three-tiered approach
In these analytical studies, FDA recommends the sponsor to identify CQAs and classify them into three tiers according to the criticality or risk ranking relevant to clinical outcomes:
- Tier 1 – most relevant CQAs to clinical outcomes
- Tier 2 – CQAs that are mild-to-moderate relevant to clinical outcomes
- Tier 3 – least relevant CQAs to clinical outcomes
Furthermore, FDA also suggests specific statistical approaches according to the different tiers, with the statistical rigour of these approaches decreasing from Tier 1 to Tier 3:
- Tier 1 – equivalence test
- Tier 2 – quality range approach
- Tier 3 – raw data or graphical presentation
Although this is a well-structured three-tiered approach, there is frequently a vast number of CQAs relevant to clinical outcomes, which can make the identification and classification into tiers somewhat complex. Therefore, it’s not difficult to understand how performing one-to-one CQA assessments can be quite challenging.
How to easily assess analytical similarity
The structural and functional characterization of biologics include its primary and secondary structure, post-translational modifications such as glycosylation, charge heterogeneity, product-related impurities, and biological properties such as target and receptor bindings activity. This results in the identification of multiple clinically relevant CQAs.
Therefore, you should leave simple and classical methods behind when it comes to assess biosimilarity and adopt multivariate methods instead. These methods can more easily detect similarities and differences between the proposed biologic and its reference product. Thus, this leads to a more accurate and less time-consuming analytical similarity assessment.
Because of this, our solution to improve and streamline your analytical similarity assessment is exactly a multi-parametric and multivariate approach that is aligned with FDA’s totality-of-evidence framework.
Additionally, you can greatly benefit from the association of our two platforms: iRISK™, our quality risk management software that can help you identify and classify the CQAs, and iSEE™, our robust Data-Science platform with a comparability module especially designed for biosimilars!
Want to know more about Biosimilarity studies?
Interested in biosimilars and comparability studies? If so, you should check our Blog Post: Streamlining the demonstration on Biosimilarity.