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Updated: May 6, 2026

Author Spotlight: Advancements in CAR-T Cell Manufacturing and Gene Therapy Production
Published on: August 18, 2023
A systematic analysis of the inherent dose uncertainty in autologous CAR T-cell products
1Biostatistics, Cell Therapy Development and Operations, Bristol Myers Squibb, Seattle, WA, USA.
Abstract:
Chimeric antigen receptor (CAR) T-cell therapy represents a form of human gene therapy where T-cells are genetically engineered to recognize specific target antigen(s) in the human body. The target dose level of autologous CAR T-cell products is established through clinical trials to ensure the administration of an appropriate amount of viable CAR T-cells to patients. However, the actual dose calculated based on the measured drug product strength inherently includes a degree of uncertainty. This study aims to conduct a systematic analysis to quantify the inherent uncertainty arising from product dose calculation and administration. Key sources of dose uncertainty include those emanating from rounding of dose volume calculations, analytical methods to measure product strength, physical limitations of the syringes used for drug administration and in-use stability during administration. The dose uncertainty is a critical indicator of the accuracy of the dose estimate and is quantified as the total error around a target dose, which is decomposed into systematic error (bias) and random error (variability). We propose a systematic approach for quantifying the bias and variability of each uncertainty source and for integrating them to calculate the total error and determine the dose uncertainty range around the target dose. Two case studies involving lisocabtagene maraleucel (liso-cel), a commercially approved CAR T-cell product, illustrate the proposed dose uncertainty calculation. This statistical uncertainty modeling methodology is useful to understand the distribution of actual CAR T-cell doses and thus to support dose range determination and guide efforts to reduce process and analytical variability.

