Cell & Gene Comparability: FDA's Recommendations For Coping With Change
By Anna Rose Welch, Director, Cell & Gene Collaborative
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Our discussions of comparability in the cell and gene industry have historically centered around two big questions: Will this change have a minor, moderate, or major impact on the quality of our product? And: What information will we need to provide to demonstrate that our pre- and post-change products are highly similar?
Unfortunately, I wouldn’t go so far as to say the FDA’s recent cell and gene therapy town halls provided us a clearer blueprint from which we can proceed in answering these questions. After all, the answers to our biggest comparability-related questions will depend on how our individual products react to what we do to them and when we make the changes.
However, we did receive some helpful high-level reminders and/or clarifications during these town halls, several of which I’ve summarized below.
- There is an FDA comparability guidance forthcoming. As this was originally on the docket for 2022, we can expect an early 2023 release. Until we have this in our hands, ICH Q5E remains your go-to resource for guiding your individual risk assessments.
- As the mention of “individual risk assessments” above should have indicated, the FDA did not/was not able to answer the one question we all would like to know about making changes to our manufacturing process: What change(s) would result in the need to carry out additional clinical studies to demonstrate comparability?
- However, we are starting to get a better sense of what has the potential to be or may be considered a major/significant change for which we will need to demonstrate comparability (at least analytically). As the FDA specified during its town halls, shifting from an adherent to a suspension-based manufacturing process or changing to a new CDMO/manufacturing facility will most likely be considered significant changes requiring a comparability study.
- I’d also draw attention to Chapter 8 of ARM’s A-Gene (specifically pages 200 and 207), which provides us with a breakdown of commonly seen changes and takes a stab at broadly classifying them as minor, moderate, or major changes. Chapter 2 of ARM's A-Cell (specifically pages 43-48) also unpacks some of the unique comparability considerations for autologous and allogeneic cell therapies.
- We were politely reminded that release testing alone is not going to cut it for demonstrating comparability. Rather, the FDA emphasized the need for additional analytical characterization (using sensitive methods) or in-process testing — accompanied by analytical characterization data from early phase studies.
- You can expect that the later in development the change is made the heavier the analytical burden will be for the manufacturer. We’ve heard it said many times before, but here it is once more: Make big changes earlier in development (i.e., prior to clinical development), if possible, and make sure to keep retains from early lots.
- Having a good statistician in-house or on your payroll will be beneficial, as well, considering the statistical challenges that can arise in demonstrating comparability early in development and/or when working with a small number of lots.
- Don’t forget that you can discuss your comparability protocol in a formal meeting with the FDA, or you can submit your protocol to the FDA by amending your IND.
In the grand scheme of things, comparability may not be a new concept for most of us. But demonstrating the pre-and post-change quality of our products during clinical development (as opposed to post-approval) makes the exercise a lot less run-of-the-mill. It’s infinitely more difficult to identify and quantify a potentially clinically meaningful change when we have a hazy understanding of our products’ CQAs (and their acceptable ranges) and limited clinical data.
I’ve spent a lot of time and thousands of words in the past month alone delving into the industry’s biggest questions and concerns around how much is, should, and/or will be expected analytically to demonstrate a product’s quality (in particular, its potency). To demonstrate comparability, we are also faced with a similar question: What will ultimately be the most thorough — and also most efficient — way(s) to demonstrate we understand how our process influences our product, and/or how our product’s structure influences its clinical function?