From understanding diseases to drug design: can artificial intelligence bridge the gap?
Abstract Artificial intelligence (AI) has emerged as a transformative technology with significant potential to revolutionize disease understanding and drug design in healthcare. AI serves as a remarkable accelerating tool that bridges the gap between understanding diseases and discovering drugs. Given its capacity in the analysis and interpretation of massive amounts of data, AI is tremendously boosting the power of predictions with impressive accuracies. This allowed AI to pave the way for advancing all key stages of drug development, with the advantage of expediting the drug discovery process and curbing its costs. This is a comprehensive review of the recent advances in AI and its applications in drug discovery and development, starting with disease identification and spanning through the various stages involved in the drug discovery pipeline, including target identification, screening, lead discovery, and clinical trials. In addition, this review discusses the challenges that arise during the implementation of AI at each stage of the discovery process and provides insights into the future prospects of this field..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:57 |
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| Enthalten in: |
Artificial intelligence review - 57(2024), 4 vom: 11. März |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Pushkaran, Anju Choorakottayil [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| BKL: | |
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| Themen: |
Artificial intelligence |
| Anmerkungen: |
© The Author(s) 2024 |
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| doi: |
10.1007/s10462-024-10714-5 |
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| funding: |
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| 520 | |a Abstract Artificial intelligence (AI) has emerged as a transformative technology with significant potential to revolutionize disease understanding and drug design in healthcare. AI serves as a remarkable accelerating tool that bridges the gap between understanding diseases and discovering drugs. Given its capacity in the analysis and interpretation of massive amounts of data, AI is tremendously boosting the power of predictions with impressive accuracies. This allowed AI to pave the way for advancing all key stages of drug development, with the advantage of expediting the drug discovery process and curbing its costs. This is a comprehensive review of the recent advances in AI and its applications in drug discovery and development, starting with disease identification and spanning through the various stages involved in the drug discovery pipeline, including target identification, screening, lead discovery, and clinical trials. In addition, this review discusses the challenges that arise during the implementation of AI at each stage of the discovery process and provides insights into the future prospects of this field. | ||
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