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AI and machine learning for clinical pharmacology: A Primer
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  • David Ryan,
  • Rory Maclean,
  • Alfred Balston ,
  • Andrew Scourfield,
  • Anoop Shah,
  • Jack Ross
David Ryan
University College London Hospitals NHS Foundation Trust
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Rory Maclean
University College London Hospitals NHS Foundation Trust
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Alfred Balston
Guy's and St Thomas' NHS Foundation Trust
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Andrew Scourfield
University College London Hospitals NHS Foundation Trust
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Anoop Shah
University College London Hospitals NHS Foundation Trust
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Jack Ross
University College Hospital

Corresponding Author:jackross@nhs.net

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Abstract

Artificial intelligence (AI) will impact many aspects of clinical pharmacology including drug discovery and development, clinical trials, personalised medicine, pharmacogenomics, pharmacovigilance and clinical toxicology. The rapid progress of AI in healthcare means clinical pharmacologists should have an understanding of AI and its implementation into clinical practice. As with any new therapy or health technology, it is imperative that AI tools are subject to robust and stringent evaluation to ensure that they enhance clinical practice in a safe and equitable manner. This review serves as an introduction to AI for the clinical pharmacologist, highlighting current applications, aspects of model development and issues surrounding evaluation and deployment. The aim of this article is to empower clinical pharmacologists to embrace and lead on the safe and effective use of AI within healthcare.
08 Aug 2023Submitted to British Journal of Clinical Pharmacology
08 Aug 2023Submission Checks Completed
08 Aug 2023Assigned to Editor
08 Aug 2023Review(s) Completed, Editorial Evaluation Pending
12 Aug 2023Reviewer(s) Assigned
29 Aug 2023Editorial Decision: Revise Minor
04 Oct 20231st Revision Received
05 Oct 2023Submission Checks Completed
05 Oct 2023Assigned to Editor
05 Oct 2023Review(s) Completed, Editorial Evaluation Pending
06 Oct 2023Editorial Decision: Accept