{"title":"整合临床药理学和人工智能:潜在的益处、挑战和临床药理学家的作用。","authors":"Harmanjit Singh, Dwividendra Kumar Nim, Aaronbir Singh Randhawa, Saher Ahluwalia","doi":"10.1080/17512433.2024.2317963","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction: </strong>The integration of artificial intelligence (AI) into clinical pharmacology could be a potential approach for accelerating drug discovery and development, improving patient care, and streamlining medical research processes.</p><p><strong>Areas covered: </strong>We reviewed the current state of AI applications in clinical pharmacology, focusing on drug discovery and development, precision medicine, pharmacovigilance, and other ventures. Key AI applications in clinical pharmacology are examined, including machine learning, natural language processing, deep learning, and reinforcement learning etc. Additionally, the evolving role of clinical pharmacologists, ethical considerations, and challenges in implementing AI in clinical pharmacology are discussed.</p><p><strong>Expert opinion: </strong>The AI could be instrumental in accelerating drug discovery, predicting drug safety and efficacy, and optimizing clinical trial designs. It can play a vital role in precision medicine by helping in personalized drug dosing, treatment selection, and predicting drug response based on genetic, clinical, and environmental factors. The role of AI in pharmacovigilance, such as signal detection and adverse event prediction, is also promising. The collaboration between clinical pharmacologists and AI experts also poses certain ethical and practical challenges. Clinical pharmacologists can be instrumental in shaping the future of AI-driven clinical pharmacology and contribute to the improvement of healthcare systems.</p>","PeriodicalId":12207,"journal":{"name":"Expert Review of Clinical Pharmacology","volume":" ","pages":"381-391"},"PeriodicalIF":3.6000,"publicationDate":"2024-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrating clinical pharmacology and artificial intelligence: potential benefits, challenges, and role of clinical pharmacologists.\",\"authors\":\"Harmanjit Singh, Dwividendra Kumar Nim, Aaronbir Singh Randhawa, Saher Ahluwalia\",\"doi\":\"10.1080/17512433.2024.2317963\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction: </strong>The integration of artificial intelligence (AI) into clinical pharmacology could be a potential approach for accelerating drug discovery and development, improving patient care, and streamlining medical research processes.</p><p><strong>Areas covered: </strong>We reviewed the current state of AI applications in clinical pharmacology, focusing on drug discovery and development, precision medicine, pharmacovigilance, and other ventures. Key AI applications in clinical pharmacology are examined, including machine learning, natural language processing, deep learning, and reinforcement learning etc. Additionally, the evolving role of clinical pharmacologists, ethical considerations, and challenges in implementing AI in clinical pharmacology are discussed.</p><p><strong>Expert opinion: </strong>The AI could be instrumental in accelerating drug discovery, predicting drug safety and efficacy, and optimizing clinical trial designs. It can play a vital role in precision medicine by helping in personalized drug dosing, treatment selection, and predicting drug response based on genetic, clinical, and environmental factors. The role of AI in pharmacovigilance, such as signal detection and adverse event prediction, is also promising. The collaboration between clinical pharmacologists and AI experts also poses certain ethical and practical challenges. Clinical pharmacologists can be instrumental in shaping the future of AI-driven clinical pharmacology and contribute to the improvement of healthcare systems.</p>\",\"PeriodicalId\":12207,\"journal\":{\"name\":\"Expert Review of Clinical Pharmacology\",\"volume\":\" \",\"pages\":\"381-391\"},\"PeriodicalIF\":3.6000,\"publicationDate\":\"2024-04-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Expert Review of Clinical Pharmacology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1080/17512433.2024.2317963\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/2/15 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q2\",\"JCRName\":\"PHARMACOLOGY & PHARMACY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Expert Review of Clinical Pharmacology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1080/17512433.2024.2317963","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/2/15 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
Integrating clinical pharmacology and artificial intelligence: potential benefits, challenges, and role of clinical pharmacologists.
Introduction: The integration of artificial intelligence (AI) into clinical pharmacology could be a potential approach for accelerating drug discovery and development, improving patient care, and streamlining medical research processes.
Areas covered: We reviewed the current state of AI applications in clinical pharmacology, focusing on drug discovery and development, precision medicine, pharmacovigilance, and other ventures. Key AI applications in clinical pharmacology are examined, including machine learning, natural language processing, deep learning, and reinforcement learning etc. Additionally, the evolving role of clinical pharmacologists, ethical considerations, and challenges in implementing AI in clinical pharmacology are discussed.
Expert opinion: The AI could be instrumental in accelerating drug discovery, predicting drug safety and efficacy, and optimizing clinical trial designs. It can play a vital role in precision medicine by helping in personalized drug dosing, treatment selection, and predicting drug response based on genetic, clinical, and environmental factors. The role of AI in pharmacovigilance, such as signal detection and adverse event prediction, is also promising. The collaboration between clinical pharmacologists and AI experts also poses certain ethical and practical challenges. Clinical pharmacologists can be instrumental in shaping the future of AI-driven clinical pharmacology and contribute to the improvement of healthcare systems.
期刊介绍:
Advances in drug development technologies are yielding innovative new therapies, from potentially lifesaving medicines to lifestyle products. In recent years, however, the cost of developing new drugs has soared, and concerns over drug resistance and pharmacoeconomics have come to the fore. Adverse reactions experienced at the clinical trial level serve as a constant reminder of the importance of rigorous safety and toxicity testing. Furthermore the advent of pharmacogenomics and ‘individualized’ approaches to therapy will demand a fresh approach to drug evaluation and healthcare delivery.
Clinical Pharmacology provides an essential role in integrating the expertise of all of the specialists and players who are active in meeting such challenges in modern biomedical practice.