eChalk Talk: Bioanalytical Strategy for PK Assessments of ATMPs

The market for advanced therapy medicinal products (ATMPs) is expanding rapidly, with 34 FDA-approved products to date¹. The growth trajectory for these novel therapeutics is expected to continue with over 4,000 ATMPs in development and an estimated 10 to 20 more approvals in 2026.¹  

ATMPs offer promise for a range of diseases, but the pharmacokinetic (PK) assessment of these complex therapeutics poses unique challenges. In this webinar, we explore the nuances of PK assessment of ATMPs, with a focus on approaches and applications for gene and cell therapies.

Challenges of PK assessment for ATMPs

ATMPs, often referred to as cell and gene therapies, are medicines for human use that are based on genes, tissues, or cells and which offer groundbreaking opportunities for the treatment of disease and injury.²  

PK data provides information on what the human body does to a given drug and generally examines four main parameters: absorption, distribution, metabolism, and excretion (ADME). Unlike small molecules and basic large molecules, ATMPs often consist of living entities (cell therapies) or genetic material (gene therapies), making classic PK parameters less applicable:

• Absorption. ATMPs are usually administered directly to the target or systemically, bypassing conventional absorption pathways.
• Distribution. Biodistribution can be unpredictable due to factors such as vector dissemination or cell migration.
• Metabolism. Living cells can proliferate, differentiate, or die, altering their therapeutic potential over time.
• Excretion. To date, the elimination pathways for genetic materials and cells are not well-defined.

While bioanalytical method validation (BMV) and regulatory guidance is well-established for traditional drugs quantified by ligand binding assays (LBA) and LC/MS, it is less well-defined for ATMPs that may require other platforms for PK analysis. As these innovative products continue to increase in complexity, so does the bioanalytical strategy for quantifying these therapies and understanding their PK.

PK assessment strategies for ATMPs

Unlike classic small and large molecules, ATMPs are often comprised of multiple components, The complexity of ATMPs and the extensive amount of processing they undergo while in the body result in a complicated interplay of PK and pharmacodynamics.

PK assessments for gene therapies

In preclinical studies, biodistribution of a viral vector-based gene therapy examines the exposure of the drug product by assessing its distribution into tissues and biofluids. In clinical studies, PK assessment involves measuring the vector and the transgene in the target tissues and in the circulation to demonstrate exposure and persistence. Shedding of that viral vector and secreta and excreta from the body characterizes excretion, another component of PK. It is also important to understand the expression of the transgene at both the mRNA and protein level since that is the pharmacologically active portion of the gene therapy. Taken together, all these assessments not only inform safety and efficacy, but also contribute to dosing decisions or PD assessments.

For biodistribution studies, the viral vector or the components encompassing the promoter element or spanning both the promoter and the transgene are used as a target region for quantification via quantitative polymerase chain reaction (qPCR) or digital PCR (dPCR). Transgene expression at the mRNA level can be quantified by qPCR or reverse transcription qPCR (RT-qPCR). Quantification of the transgene product at the protein level can be quantified using various platforms including ligand binding assays (LBA), immunoaffinity capture liquid chromatography-mass spectrometry (LC/MS), immunohistochemistry (IHC), western blotting, and other protein detection techniques. Viral shedding is quantified using qPCR or dPCR to measure the copy number of viral vector genomes in shedding matrices.

Among the challenges associated with using qPCR and newer technology platforms such as digital PCR for gene therapy PK assessment are:

• Navigating gaps in regulatory guidance on how to validate these assays
• Understanding the target and optimal sensitivity limits of the assay
• Validating the assay in multiple matrices of interest, particularly for biodistribution assays designed to quantify the target in various tissues and biofluids

Typically, for a biodistribution assay, a primary matrix is validated and then a representative matrix or subset of matrices is assessed in a qualification.

PK assessments for cell therapies

Measuring the PK of living cells such as CAR-T cell therapies is complex. The most common methods for quantitating CAR-T cell therapies in circulation for exposure and persistence are:

• qPCR, which quantifies the level of transgene DNA in the cell and infers the concentration of CAR-T in circulation
• Flow cytometry, which uses anti-CAR fluorescent labelled antibody to stain CAR-T cells as a direct measure of of CAR-expressing cells

Both methods are acceptable, but each approach has its pros and cons.³ qPCR and flow cytometry can also provide very different information.

The biggest advantage for qPCR is increased sensitivity that enables detection of low copy numbers, which is helpful for understanding persistence. Flow cytometry offers the advantages of direct measurement of CAR-expressing cells and flexibility for high-parameter panels that provide additional insight into the phenotype and activation status of the cells.

As with gene therapies, there are challenges to understanding and measuring cellular kinetics for cell therapies. The first is platform selection and, oftentimes, the integration of data from multiple platforms or measures is needed. There is also a lack of formal regulatory guidance on the validation assessments and acceptance criteria for qPCR PK assays for cell therapies. For flow cytometry PK assays for cell therapies, the Clinical & Laboratory Standards Institute (CLSI) H62 guideline for flow cytometry has offered recommendations and best practices for validating flow cytometry assays. Other potential hurdles to PK assessments for cell therapy are:

• Critical reagent availability, especially for flow cytometry. If anti-CAR, anti-transgene antibodies are not available, validation in the absence of patient samples is very difficult and will need to rely on surrogates such as transduced cell lines.
• Extremely low cell numbers, due to the lymphodepletion required prior to cell therapy infusion, can make sample analysis and data reporting difficult.
• Concordance between PCR and flow cytometry results
• Historical PK assessments, such as incurred sample reanalysis (ISR), may be difficult or not applicable.

Key takeaways

PK assessment of ATMPs is inherently complex due to their biological nature and the unique mechanisms by which they exert therapeutic effects. This complexity requires complicated bioanalytical strategies. To understand the efficacy and safety of these innovative therapies, there is a need to expand the bioanalytical toolbox to include non-traditional platforms for measuring the components that comprise these drugs. Every ATMP is unique, therefore the acceptance criteria used for an assay must be informed by the platform, context of use, and underlying scientific objective.

To learn more about how BioAgilytix can support PK assessment of ATMPs, speak to a scientist.

References

1. American Society of Cell + Gene Therapy. Gene, Cell, & RNA Therapy Landscape. Q2 2024 Quarterly Report. Available at https://www.asgct.org/global/documents/asgct-citeline-q2-2024-report.aspx.
2. European Medicines Agency. Advanced therapy medicinal products: Overview. Available at https://www.ema.europa.eu/en/human-regulatory-overview/advanced-therapy-medicinal-products-overview.
3. Hays A, et al. Bioanalytical Assay Strategies and Considerations for Measuring Cellular Kinetics. Int J Mol Sci. 2022;24(1):695.