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Current Status and Future Directions: The Application of Artificial Intelligence/Machine Learning for Precision

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Artificial intelligence (AI) and machine learning (ML) accelerate precision medicine but require trustworthy methods. Strategies like differential privacy and federated learning protect data while regulatory collaboration enhances AI adoption.

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Area of Science:

  • Computational biology
  • Biomedical informatics
  • Regulatory science

Background:

  • Precision medicine aims to tailor treatments using individual variability.
  • Artificial intelligence (AI) and machine learning (ML) offer powerful tools for analyzing complex health data.
  • Technological advancements present both opportunities and challenges for AI in healthcare.

Purpose of the Study:

  • To discuss the goals and applications of AI in precision medicine.
  • To identify challenges associated with AI implementation in healthcare.
  • To propose strategies for trustworthy AI and data protection in precision medicine.

Main Methods:

  • Review of innovative AI applications in precision medicine from a 2023 FDA workshop.
  • Discussion of challenges in AI, focusing on trustworthiness.
  • Exploration of privacy-preserving techniques like differential privacy, synthetic data, and federated learning.
  • Consideration of risk-based management and agile regulatory frameworks.

Main Results:

  • AI/ML applications show promise in predicting tumor growth, identifying biomarkers, and stratifying patient populations.
  • Key challenges include ensuring AI trustworthiness and protecting sensitive data.
  • Differential privacy, synthetic data generation, and federated learning are viable strategies for data protection.
  • A risk-based management approach and agile regulatory ecosystem are crucial for AI integration.

Conclusions:

  • AI and ML are vital for advancing precision medicine.
  • Addressing AI trustworthiness and data privacy is paramount.
  • Collaborative efforts, including data sharing and regulatory guidance, are essential for the responsible advancement of AI in precision medicine.