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Empowering personalized pharmacogenomics with generative AI solutions.

Mullai Murugan1, Bo Yuan1,2, Eric Venner1,2

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Summary
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An AI assistant using GPT-4 and retrieval-augmented generation (RAG) improves pharmacogenomic (PGx) test interpretation. This technology enhances clinical decision-making and patient care by providing accessible, accurate PGx information.

Keywords:
AI assistantOpenAI GPT-4generative AIlarge language modelspharmacogenomic testingretrieval-augmented generation

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Area of Science:

  • * Pharmacogenomics and Artificial Intelligence
  • * Clinical Genetics and Decision Support

Background:

  • * Pharmacogenomic (PGx) testing provides crucial information for personalized medicine.
  • * Interpreting complex PGx data can be challenging for healthcare providers.
  • * Improving access to and understanding of PGx results is essential for equitable patient care.

Purpose of the Study:

  • * To evaluate an AI assistant powered by OpenAI's GPT-4 for interpreting PGx results.
  • * To enhance clinical decision-making, knowledge sharing, and patient care in genetics.
  • * To promote equitable access to pharmacogenomic information.

Main Methods:

  • * Development of an AI assistant using retrieval-augmented generation (RAG).
  • * Integration of a knowledge base (KB) with Clinical Pharmacogenetics Implementation Consortium (CPIC) data.
  • * Utilizing context-aware GPT-4, prompt engineering, and guardrails for tailored responses.

Main Results:

  • * The AI assistant demonstrated high efficacy in answering PGx queries.
  • * Outperformed ChatGPT 3.5, particularly for provider-specific questions needing specialized data and citations.
  • * Identified areas for improvement: accuracy, relevancy, and representative language.

Conclusions:

  • * Context-aware GPT-4 combined with RAG significantly boosts AI utility for PGx data.
  • * RAG effectively incorporates domain-specific CPIC data and recent literature.
  • * Further development of specialized PGx models and addressing ethical concerns are crucial.