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Variability instills consistency in advanced therapy medicinal products.
In a tightly regulated industry, certifying that a drug is authentic, safe, and effective requires passing through several different thresholds of proof. In the 2011 Guidance for Industry, Potency Tests for Cellular and Gene Therapy Products (CGT) (1), FDA states, “No lot of any licensed product shall be released by the manufacturer prior to the completion of tests for conformity with standards applicable to such product, (21 CFR [Code of Federal Regulations 610.1), which include tests for potency, sterility, purity, and identity (21 CFR Part 610, Subpart B).” These requirements apply to all biological products, including autologous and single patient allogeneic products, where a lot may be defined as a single dose.
The need to meet this guidance, and especially for rising levels of instances of single dose production for CGT, can create a burden in terms of time, economics, and staff training. The biopharmaceutics classification system (BCS)-based biowaiver approach is intended, along with other measures, to reduce the need for in vivo bioequivalence studies (i.e., it can provide a surrogate for in vivo bioequivalence). The International Council for Harmonisation’s (ICH) M9 guideline states, “In vivo bioequivalence studies may be exempted if an assumption of equivalence in in vivo performance can be justified by satisfactory in vitro data. The BCS is a scientific approach based on the aqueous solubility and intestinal permeability characteristics of the drug substance or substances” (2). In practical terms, CGT fields are moving so rapidly many identification and potency tests are being invented alongside the drug therapies themselves. It is an increasingly hopeful time for critically ill patients and also for the pharmaceutical industry, but this growing trend places a strain on scientists, suppliers, manufacturers, hospital staff, regulators, and insurers. In a industry insider survey (3), nearly half of all respondents replied that CGTs represented the largest opportunity for growth in terms of potential new therapies. While the surge is clearly a highly positive step, it also means taking care to solve inherent present challenges becomes more urgent.
A typical strategy is to apply lessons learned from more mature therapies, particularly the use of monoclonal antibodies (mAbs), where much has been optimized due to popularity, length of use, and to some degree (arguably), less complexity residing in these systems. But even here more work on potency assays is evidently required. An article offering a novel mathematical approach for fitting concentration-response curves on mAbs for potency data concludes, “the future strategy for bioassay analysis should include investments both in the development of the best Mechanism of Action (MoA) reflecting assay and the identification of cost-effective techniques for implementation; this investment should begin in the early phases of clinical development. There have been some noteworthy achievements in the utilization of mathematical models in the bioassay evaluation strategies in various segments, but there is a long way left to go. Because the mechanism behind monoclonal antibody development is complex or poorly understood, mathematical models, which are relatively simple, could be used to reduce time and expenses” (4).
Vibha Jawa, executive director, head of Biotherapeutics Bioanalysis in Nonclinical Disposition and Bioanalysis (NDB) Organization, Bristol Myers Squibb, describes which types of products require the closest watch for potency fluctuations. “I would say the novel complex modalities where we don’t know what expression levels are needed for these new targets in order to validate that the drug is adequately binding to the intended target. So, definitely novel modalities like multidomain biologics and CGT therapies require more consideration for potency.” So, ab initio, increased biological complexity itself, plays a central role in making these therapies more difficult. If we cannot match on a one-to-one basis the expression levels required for MoA, how then does one model an effective potency regime at the point of origin?
Jawa goes on to build on this observation, saying, “a common thread for these new modalities is that the drug product itself is a cell. And it’s a patient’s cell that we are talking about. So, it’s not a Chinese hamster ovary cell or antibody that comes to us already being well defined. In this case, the Chimeric antigen receptor T cell (CAR-T) for example, where we are taking cells from the patient, we are going to engineer them outside of the body, and we have to understand if the CAR we have transduced into these cells, are they going to be able to bind the tumor target, so for potency you are using this CAR-T cell, or a cell line which is very similar, which can go kill a tumor, and we have to do all potency testing upfront to know this receptor is dedicated or efficient enough.”
And as if to put an exclamation point on the issue of complexitiy, Jawa concludes, “so herein lies the complexity—each person has their own T cell, with its own level of T-cell antigen receptor variability. We just don’t know how the T cell receptors are going to interact with the tumor cell, and same for major histocompatibility complex class one and class two molecules which are the proteins present, which present the peptides. So, potency is, shall we say, a completely different question to answer for CAR-T therapies.”
There is some good news, however, when it comes to viral gene therapies. There is an intrinsically more consistent manufacturing base to pull from, and the adeno-associated viruses or lentivirus being used to transduce the modification into a cell of interest can therefore be manufactured more consistently, and with less variability, than for CAR-T therapies. Another direction would be to question if there is a significant rise in complexity, yet again, when dealing with emerging therapies such as allogenic CAR-Ts, Natural Killer cell-based CARs, or armored CARs. These new modalities require ingenuity in setting up biorelevant test systems for target cells, because the screening of multiple new test cells lines will be required. The further we go on this path, the more variability we need to account for in order to engineer consistency into these new products.
1. FDA. Guidance for Industry, Potency Tests for Cellular and Gene Therapy Products (FDA, 2011).
2. ICH. M9 Biopharmaceutics Classification SystemBased Biowaivers Guidance for Industry (ICH, May 2021).
3. Playter, G. Crossing the Same River Multiple Times. Pharm. Technol. 2023 47 (1).
4. Dash, R.; Mandal S; and Rathore, A. Mathematical Modeling of Cell-based Potency Data for mAb Biotherapeutics, BioPharmInternational.com, Nov. 17, 2022.
Chris Spivey is editorial director for BioPharm International.
Vol. 36, No. 2
When referring to this article, please cite it as C. Spivey. Potency Assays for Novel Complex Modalities. BioPharm International 2023, 36 (2)