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非洲药物研发中心人工智能/机器学习工具的持续实施与前瞻性验证

Ongoing Implementation and Prospective Validation of Artificial Intelligence/Machine Learning Tools at an African Drug Discovery Center.

作者信息

Hlozek Jason, Chibale Kelly, Woodland John G

机构信息

Department of Chemistry and Holistic Drug Discovery and Development (H3D) Center, University of Cape Town, Cape Town 7701, South Africa.

South African Medical Research Council Drug Discovery and Development Research Unit, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town 7925, South Africa.

出版信息

ACS Med Chem Lett. 2024 Jun 21;15(7):989-993. doi: 10.1021/acsmedchemlett.4c00243. eCollection 2024 Jul 11.

Abstract

Artificial intelligence (AI) and machine learning (ML) are anticipated to accelerate drug discovery programs. Following our development of an end-to-end virtual screening cascade at the University of Cape Town (UCT) Holistic Drug Discovery and Development (H3D) Center, we report the ongoing implementation of open-source AI/ML tools for use in resource-constrained settings.

摘要

人工智能(AI)和机器学习(ML)有望加速药物研发项目。在开普敦大学(UCT)整体药物发现与开发(H3D)中心开发了端到端虚拟筛选级联之后,我们报告了用于资源受限环境的开源AI/ML工具的持续实施情况。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5bf9/11247640/bc38672e7df6/ml4c00243_0001.jpg

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