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Updated: Feb 17, 2026

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薬剤発見のためのビッグデータ: 薬剤化学者のためのいくつかの歴史的景観,考察,およびアプリケーション

João A L de Lima1, Lucas Silva Franco1, Lídia M Lima1

  • 1Institute of Biomedical Science, Federal University of Rio de Janeiro, Avenue Carlos Chagas Filho 373, CCS, Block B Room B14 Rio de Janeiro, Rio de Janeiro 21941-902, Brazil.

ACS omega
|February 16, 2026
PubMed
まとめ

ビッグデータ (BD) は,標的の識別とリードの最適化のための多様なデータセットを統合することによって,薬物発見に革命を起こします. 開発を加速する一方で,AIやLLMと並行してその使用は,データ品質と科学的解釈に関する重要な疑問を提起しています.

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Drug discovery is a multifaceted process involving extensive screening, testing, and optimization of lead compounds to identify potential new drugs for therapeutic use. It combines several approaches, including screening large numbers of natural products, chemical modification of known active molecules, identification of new drug targets, and rational design based on biological mechanisms and drug-receptor structure. These approaches are carried out in both academic research laboratories and...
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Advances in genomics have profoundly influenced drug discovery by increasing both the speed and accuracy of pharmaceutical development. Pharmacogenomics, which examines how genetic variation influences drug response, facilitates the identification of novel therapeutic targets and enables patient stratification for personalized treatment. These strategies contribute to improved drug efficacy, minimized adverse effects, and more efficient clinical trial design.Mapping genetic differences...
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Pharmacodynamic methods provide insights into a drug's effects on physiological processes over time and play a crucial role in understanding bioavailability and therapeutic efficacy. These methods can be broadly classified into acute pharmacological and therapeutic response approaches, each with distinct mechanisms and applications.The acute pharmacological response method directly correlates a drug's physiological effects, such as ECG or pupil diameter changes, to its time course in the body.
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Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
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