Artificial intelligence and machine learning for clinical pharmacology.
David K Ryan1, Rory H Maclean1,2, Alfred Balston3
1Department of Clinical Pharmacology, University College London Hospitals NHS Foundation Trust, London, UK.
British Journal of Clinical Pharmacology
|October 16, 2023
Summary
Artificial intelligence (AI) offers significant advancements in clinical pharmacology, impacting drug discovery, trials, and personalized medicine. Clinical pharmacologists must understand and rigorously evaluate AI tools for safe and equitable healthcare integration.
Area of Science:
- Clinical pharmacology
- Healthcare technology
- Artificial intelligence
Background:
- Artificial intelligence (AI) is rapidly advancing in healthcare.
- Clinical pharmacology encompasses drug discovery, clinical trials, personalized medicine, pharmacogenomics, pharmacovigilance, and clinical toxicology.
- Understanding AI is crucial for clinical pharmacologists.
Purpose of the Study:
- To introduce clinical pharmacologists to AI.
- To highlight current AI applications in clinical pharmacology.
- To discuss AI model development, evaluation, and deployment challenges.
Main Methods:
- Review of current AI applications in clinical pharmacology.
- Discussion of AI model development processes.
- Analysis of evaluation and deployment considerations for AI tools.
Main Results:
- AI impacts numerous areas of clinical pharmacology.
- AI tools require robust and stringent evaluation for safe and equitable enhancement of clinical practice.
- Understanding AI empowers clinical pharmacologists to lead its integration.
Conclusions:
- Clinical pharmacologists need to understand AI for its effective implementation.
- Rigorous evaluation of AI tools is essential.
- AI has the potential to transform clinical pharmacology practice safely and equitably.
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