Unlocking faster IND filing: Unparalled in vivo correlation of CAR-T therapies

10-minute cell avidity assay reliable in vivo correlation

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Cell Avidity Unravels the Downfall of the APRIL CAR: Insights from a Failed Clinical Trial

Latest publication by University College London (UCL)

A recent JITC paper “Limited efficacy of APRIL CAR in patients with multiple myeloma indicate challenges in the use of natural ligands for CAR T cell therapy” published by the research team of Dr. Lydia Lee unveils the potential of cell avidity measurements in averting the failure of the APRIL-CAR clinical trial in a retrospective study.

Summary:

  • APRIL CAR was well tolerated in patients; however, the clinical responses were poor leading to 9 out 11 patient deaths
  • APRIL CAR demonstrated significantly reduced cell avidity to BCMA expressing target tumor cells compared to other FDA approved BCMA CAR-T cells
  • While traditional in vitro and in vivo (mouse) assays failed to identify the poor clinical efficacy of APRIL CAR, cell avidity successfully pinpointed the issue

 

Learn more about how cell avidity predicted the poor clinical outcome from the APRIL CAR trial and how to accelerate your path to successful IND filings

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From concept to clinic: unravelling the iterative, time-consuming, and expensive process of cell therapy drug development

A staggering 83% of CAR-T lead candidates fail post-preclinical development, a trend that may worsen as we tackle more complex target. This not only prolongs the highly iterative development process, but also significantly inflates costs with a high failure rate in clinical trails.

We’ve been heavily dependent on the same in vitro endpoint assays, such as cytokine secretion and killing, during preclinical development. While these traditional assays can produce valuable data on a molecular level, they fall short in providing understanding of cellular interaction. This is a critical, yet often overlooked, piece of information.

Thus, we’ve historically had to make an educated guess when selecting a lead candidate, based on the limited information at hand. However, recent advancements have started to change this scenario…

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Leveraging cell avidity measurements to accelerate your path to successful IND fillings

Cell avidity measurements produce a real-time readout on the initiating event of cellular killing, providing an improved prediction of in vivo efficacy compared to current in vitro assays (Larson et al. 2022, Nature, Chockley et al. 2023, Nature Biotechnology, Leick et al. 2022, Cancer Cell), which produce highly variable readouts.

Incorporating cell avidity measurements in the early stages of cell therapy development helps to streamline the process, reducing iteration cycles, inconclusive results and in vivo failures. This facilitates quicker identification of superior candidates, accelerates IND filings, and boosts R&D efficiency, saving both time and costs.

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The z-Movi Cell Avidity Analyzer provides the ONLY simple, direct solution to measure cell avidity

Marcela Maus, MD, PhD, Associate Professor at Harvard Medical School and Director of Cellular Immunotherapy at Massachusetts General Hospital recently published in Nature and Cancer Cell, showcasing the necessity of measuring cell avidity to pick the best CAR candidates. In her webinar with our team, she mentions:

“Interestingly, of the pre-clinical assays used to compare CAR constructs, only binding avidity correlated with in vivo results”  

From Dr. Maus’ groundbreaking work in Cancer Cell, Non-cleavable hinge enhances avidity and expansion of CAR T cells for acute myeloid leukemia, Leick et al. tested various CAR variants with different in-vitro methods and mouse models, looking for the best functioning CAR to develop further.

They found that cytokine secretion and cytotoxicity assays, even serial re-stimulation assays, couldn’t differentiate between the different CAR constructs. However, when her group used avidity to evaluate their constructs it very clearly indicated a lead candidate.

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Business impact of a better in vitro assay – save time and cost in R&D AND gain confidence going into clinical trials

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