What CGT can learn from biologics: high‑value AI use cases for manufacturing
Cell and gene therapy manufacturing continues to face efficiency and scalability challenges, yet the sector can draw directly on the biopharmaceutical industry’s established experience applying AI and machine learning across biologics production, spanning digital infrastructure, process analytical technology (PAT), cloud-based digital applications, and generative AI. This article examines how those lessons translate to CGT, arguing that manufacturers should prioritize electronic batch records, contextualized metadata, and cloud-based data pipelines before layering on advanced AI, while planning early for GMP validation of AI-driven tools.
Authors
- Shyam Panjwani (ORCID: https://orcid.org/0000-0001-7611-8425)
Institutions
- Bayer (United States) (US)
Publication Details
- Journal
- Cell and Gene Therapy Insights
- Published
- 2026-07-30
- DOI
- https://doi.org/10.18609/cgti.2026.080
- Primary Topic
- Viral Infectious Diseases and Gene Expression in Insects
- Type
- article
- Field-Weighted Citation Impact
- 0.00