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Updated: Jan 10, 2026

Fluorescence Microscopy for ATP Internalization Mediated by Macropinocytosis in Human Tumor Cells and Tumor-xenografted Mice
Published on: June 30, 2021
AI and ATMP: Patients First
Toni Manzano1, William Whitford1
1Summer 2025.
None:
This review article explores the application of artificial intelligence (AI) within Advanced Therapy Medicinal Products (ATMP) analysis, specifically focusing on challenges related to chemistry, manufacturing, and controls (CMC) and manufacturing processes. The inherent complexity and variability in ATMPs necessitate innovative solutions for potency testing, real-time process monitoring, and stability assessment. We examine how AI tools can contribute to these areas while navigating increasingly stringent regulatory landscapes. This work acknowledges the growing importance of data protection regulations worldwide, including frameworks such as HIPAA, GDPR, PIPEDA, POPIA, and LGPD, highlighting the need for secure data handling and patient privacy considerations within ATMP development and analysis. The integration of AI also necessitates attention to explainability and transparency, potentially leveraging techniques like SHAP values and physics-informed neural networks to ensure regulatory compliance and build trust in AI-driven insights.
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