{"title":"Large language models facilitating modern molecular biology and novel drug development.","authors":"Xiao-Huan Liu, Zhen-Hua Lu, Tao Wang, Fei Liu","doi":"10.3389/fphar.2024.1458739","DOIUrl":null,"url":null,"abstract":"<p><p>The latest breakthroughs in information technology and biotechnology have catalyzed a revolutionary shift within the modern healthcare landscape, with notable impacts from artificial intelligence (AI) and deep learning (DL). Particularly noteworthy is the adept application of large language models (LLMs), which enable seamless and efficient communication between scientific researchers and AI systems. These models capitalize on neural network (NN) architectures that demonstrate proficiency in natural language processing, thereby enhancing interactions. This comprehensive review outlines the cutting-edge advancements in the application of LLMs within the pharmaceutical industry, particularly in drug development. It offers a detailed exploration of the core mechanisms that drive these models and zeroes in on the practical applications of several models that show great promise in this domain. Additionally, this review delves into the pivotal technical and ethical challenges that arise with the practical implementation of LLMs. There is an expectation that LLMs will assume a more pivotal role in the development of innovative drugs and will ultimately contribute to the accelerated development of revolutionary pharmaceuticals.</p>","PeriodicalId":12491,"journal":{"name":"Frontiers in Pharmacology","volume":"15 ","pages":"1458739"},"PeriodicalIF":4.4000,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703923/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Frontiers in Pharmacology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.3389/fphar.2024.1458739","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"PHARMACOLOGY & PHARMACY","Score":null,"Total":0}
引用次数: 0
Abstract
The latest breakthroughs in information technology and biotechnology have catalyzed a revolutionary shift within the modern healthcare landscape, with notable impacts from artificial intelligence (AI) and deep learning (DL). Particularly noteworthy is the adept application of large language models (LLMs), which enable seamless and efficient communication between scientific researchers and AI systems. These models capitalize on neural network (NN) architectures that demonstrate proficiency in natural language processing, thereby enhancing interactions. This comprehensive review outlines the cutting-edge advancements in the application of LLMs within the pharmaceutical industry, particularly in drug development. It offers a detailed exploration of the core mechanisms that drive these models and zeroes in on the practical applications of several models that show great promise in this domain. Additionally, this review delves into the pivotal technical and ethical challenges that arise with the practical implementation of LLMs. There is an expectation that LLMs will assume a more pivotal role in the development of innovative drugs and will ultimately contribute to the accelerated development of revolutionary pharmaceuticals.
期刊介绍:
Frontiers in Pharmacology is a leading journal in its field, publishing rigorously peer-reviewed research across disciplines, including basic and clinical pharmacology, medicinal chemistry, pharmacy and toxicology. Field Chief Editor Heike Wulff at UC Davis is supported by an outstanding Editorial Board of international researchers. This multidisciplinary open-access journal is at the forefront of disseminating and communicating scientific knowledge and impactful discoveries to researchers, academics, clinicians and the public worldwide.