AI-based language models powering drug discovery and development

The discovery and development of new medicines is expensive, time-consuming, and often inefficient, with many failures along the way. Powered by artificial intelligence (AI), language models (LMs) have changed the landscape of natural language processing (NLP), offering possibilities to transform tr...

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Detalles Bibliográficos
Autores principales: Liu, Zhichao, Roberts, Ruth A., Lal-Nag, Madhu, Chen, Xi, Huang, Ruili, Tong, Weida
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Authors. Published by Elsevier Ltd. 2021
Materias:
Keynote (Green)
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8604259/
https://www.ncbi.nlm.nih.gov/pubmed/34216835
http://dx.doi.org/10.1016/j.drudis.2021.06.009
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author Liu, Zhichao
Roberts, Ruth A.
Lal-Nag, Madhu
Chen, Xi
Huang, Ruili
Tong, Weida
author_facet Liu, Zhichao
Roberts, Ruth A.
Lal-Nag, Madhu
Chen, Xi
Huang, Ruili
Tong, Weida
author_sort Liu, Zhichao
collection PubMed
description The discovery and development of new medicines is expensive, time-consuming, and often inefficient, with many failures along the way. Powered by artificial intelligence (AI), language models (LMs) have changed the landscape of natural language processing (NLP), offering possibilities to transform treatment development more effectively. Here, we summarize advances in AI-powered LMs and their potential to aid drug discovery and development. We highlight opportunities for AI-powered LMs in target identification, clinical design, regulatory decision-making, and pharmacovigilance. We specifically emphasize the potential role of AI-powered LMs for developing new treatments for Coronavirus 2019 (COVID-19) strategies, including drug repurposing, which can be extrapolated to other infectious diseases that have the potential to cause pandemics. Finally, we set out the remaining challenges and propose possible solutions for improvement.
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spelling pubmed-86042592021-11-22 AI-based language models powering drug discovery and development Liu, Zhichao Roberts, Ruth A. Lal-Nag, Madhu Chen, Xi Huang, Ruili Tong, Weida Drug Discov Today Keynote (Green) The discovery and development of new medicines is expensive, time-consuming, and often inefficient, with many failures along the way. Powered by artificial intelligence (AI), language models (LMs) have changed the landscape of natural language processing (NLP), offering possibilities to transform treatment development more effectively. Here, we summarize advances in AI-powered LMs and their potential to aid drug discovery and development. We highlight opportunities for AI-powered LMs in target identification, clinical design, regulatory decision-making, and pharmacovigilance. We specifically emphasize the potential role of AI-powered LMs for developing new treatments for Coronavirus 2019 (COVID-19) strategies, including drug repurposing, which can be extrapolated to other infectious diseases that have the potential to cause pandemics. Finally, we set out the remaining challenges and propose possible solutions for improvement. The Authors. Published by Elsevier Ltd. 2021-11 2021-06-30 /pmc/articles/PMC8604259/ /pubmed/34216835 http://dx.doi.org/10.1016/j.drudis.2021.06.009 Text en © 2021 The Authors Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active.
spellingShingle Keynote (Green)
Liu, Zhichao
Roberts, Ruth A.
Lal-Nag, Madhu
Chen, Xi
Huang, Ruili
Tong, Weida
AI-based language models powering drug discovery and development
title AI-based language models powering drug discovery and development
title_full AI-based language models powering drug discovery and development
title_fullStr AI-based language models powering drug discovery and development
title_full_unstemmed AI-based language models powering drug discovery and development
title_short AI-based language models powering drug discovery and development
title_sort ai-based language models powering drug discovery and development
topic Keynote (Green)
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8604259/
https://www.ncbi.nlm.nih.gov/pubmed/34216835
http://dx.doi.org/10.1016/j.drudis.2021.06.009
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