Advancing cell and gene therapy: Application of AI/ML in clinical development and patient management

This article explores the transformative potential of artificial intelligence (AI) and machine learning (ML) in advancing cell and gene therapy (CGT) development, with an emphasis on chimeric antigen receptor (CAR) T-cell therapy. We examine how AI/ML advanced analytics can enhance CGT clinical development by optimizing patient selection with robust eligibility criteria, facilitating clinical trial site and patient recruitment, and informing study design through risk profiling and biomarker development. Furthermore, we discuss the application of AI/ML for improving patient management, focusing on personalized dosing strategies, as well as post-treatment monitoring using wearable technology and mobile health. Opportunities and challenges presented by AI/ML in addressing the complexities of CGT, and a brief review of legislation and regulatory agency policy as it relates to AI/ML, are discussed. Overall, the integration of AI/ML offers promising avenues to enhance the efficiency, quality, and equity of CGT development and patient care.

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Publication Details

Journal
Journal of Biopharmaceutical Statistics
Published
2026-03-12
DOI
https://doi.org/10.1080/10543406.2026.2629434
Primary Topic
CAR-T cell therapy research
Type
article
Field-Weighted Citation Impact
0.00
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article

Advancing cell and gene therapy: Application of AI/ML in clinical development and patient management

Sanhita Sengupta, James B. Whitmore, Kelly Speth, Qinghua Song et al.
Journal of Biopharmaceutical Statistics
CAR-T cell therapy research
article

Advancing cell and gene therapy: Application of AI/ML in clinical development and patient management

Sanhita Sengupta, James B. Whitmore, Kelly Speth, Qinghua Song, Zhenzhen Xu, Alan Y. Chiang, Daniel Li, Md Shamsuzzaman
article en

Abstract

This article explores the transformative potential of artificial intelligence (AI) and machine learning (ML) in advancing cell and gene therapy (CGT) development, with an emphasis on chimeric antigen receptor (CAR) T-cell therapy. We examine how AI/ML advanced analytics can enhance CGT clinical development by optimizing patient selection with robust eligibility criteria, facilitating clinical trial site and patient recruitment, and informing study design through risk profiling and biomarker development. Furthermore, we discuss the application of AI/ML for improving patient management, focusing on personalized dosing strategies, as well as post-treatment monitoring using wearable technology and mobile health. Opportunities and challenges presented by AI/ML in addressing the complexities of CGT, and a brief review of legislation and regulatory agency policy as it relates to AI/ML, are discussed. Overall, the integration of AI/ML offers promising avenues to enhance the efficiency, quality, and equity of CGT development and patient care.

Journal of Biopharmaceutical Statistics
United States Food and Drug Administration (US), Bristol-Myers Squibb (Germany) (DE), Eli Lilly (Singapore) (SG), Lyell Immunopharma (United States) (US), Food and Drug Administration (TH), Gilead Sciences (France) (FR)
Partnerships for the goals
Openalex Percentile: Top 25%
CAR-T cell therapy research
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Advancing cell and gene therapy: Application of AI/ML in clinical development and patient management — Sanhita Sengupta, James B. Whitmore, et al. · Journal of Biopharmaceutical Statistics (2026) | TGRS Research Map | TGRS