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Artificial intelligence (AI) offers solutions for analyzing complex Advanced Therapy Medicinal Products (ATMPs), addressing challenges in chemistry, manufacturing, and controls (CMC). AI enhances potency testing, process monitoring, and stability assessment while ensuring data protection and regulatory compliance.

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Area of Science:

  • Biotechnology
  • Pharmaceutical Sciences
  • Data Science

Background:

  • Advanced Therapy Medicinal Products (ATMPs) present unique analytical challenges due to their inherent complexity and variability.
  • Current methods for potency testing, process monitoring, and stability assessment often struggle to keep pace with ATMP development.
  • The evolving global regulatory landscape, including data protection laws, adds another layer of complexity to ATMP analysis.

Purpose of the Study:

  • To review the application of artificial intelligence (AI) in the analysis of Advanced Therapy Medicinal Products (ATMPs).
  • To identify how AI can address challenges in chemistry, manufacturing, and controls (CMC) for ATMPs.
  • To explore the integration of AI while considering data protection and regulatory compliance.

Main Methods:

  • Literature review of AI applications in pharmaceutical analysis, with a focus on ATMPs.
  • Analysis of AI techniques for potency testing, real-time process monitoring, and stability assessment.
  • Discussion of regulatory considerations, including data protection (e.g., GDPR, HIPAA) and AI explainability (e.g., SHAP values, physics-informed neural networks).

Main Results:

  • AI tools show significant potential in improving the accuracy and efficiency of ATMP analysis.
  • AI can facilitate real-time process monitoring and enhance stability assessments for complex biologics.
  • Addressing data privacy and ensuring AI model transparency are critical for regulatory acceptance.

Conclusions:

  • AI integration is crucial for overcoming analytical hurdles in ATMP development and manufacturing.
  • Successful AI implementation requires robust data governance and adherence to global privacy regulations.
  • Explainable AI methods are essential for building trust and ensuring compliance in AI-driven ATMP analysis.