Evaluating the effect of artificial intelligence on pharmaceutical product and drug discovery in China
Abstract The pharmaceutical sector has recently witnessed a transformative improvement and shift toward artificial intelligence (AI) in its drug and pharmaceutical delivery process and procedures. Hence, this research delves into the benefits and obstacles pharmaceutical firms face in utilizing AI in China. Globally, China is recognized as a dominant pillar in research and development in the pharmaceutical industry. The country has incorporated AI approaches and technologies to improve the drug industry’s cost, efficiency and development. Therefore, this study applies the case study method and evaluation of prior studies to assess AI’s potential benefits and challenges in the drug and pharmaceutical enterprises. The research provided an in-depth evaluation of AI in the various phases of the drug discovery process. The research outcome indicated that AI’s benefits include drug repurposing, target identification, clinical trial optimization, quality assurance, and control and efficient drug distribution method. However, the analysis revealed that China faces several challenges that impact the pace and extent of integration of AI in its pharmaceutical industry. These challenges include a lack of standardized data, a shortage of skilled labor or professionals, and data and privacy concerns. In addition, the research provides three case studies that focused on f XtalPi-AI-Enhanced Drug Discover, BioMap: Accelerating Drug Development Through AI and iCarbonX: AI-Driven Precision Medicine and provided a comprehensive analysis of how these firms have used AI to stimulate their drug discovery process. The study also provides policies that can help improve the integration of AI in the pharmaceutical and drug delivery process..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2024 |
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| Erschienen: |
2024 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:10 |
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| Enthalten in: |
Future Journal of Pharmaceutical Sciences - 10(2024), 1 vom: 08. Apr. |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Sampene, Agyemang Kwasi [VerfasserIn] |
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| Links: |
Volltext [kostenfrei] |
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| Themen: |
Artificial intelligence |
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| Anmerkungen: |
© The Author(s) 2024 |
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| doi: |
10.1186/s43094-024-00632-2 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
SPR055449875 |
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| 520 | |a Abstract The pharmaceutical sector has recently witnessed a transformative improvement and shift toward artificial intelligence (AI) in its drug and pharmaceutical delivery process and procedures. Hence, this research delves into the benefits and obstacles pharmaceutical firms face in utilizing AI in China. Globally, China is recognized as a dominant pillar in research and development in the pharmaceutical industry. The country has incorporated AI approaches and technologies to improve the drug industry’s cost, efficiency and development. Therefore, this study applies the case study method and evaluation of prior studies to assess AI’s potential benefits and challenges in the drug and pharmaceutical enterprises. The research provided an in-depth evaluation of AI in the various phases of the drug discovery process. The research outcome indicated that AI’s benefits include drug repurposing, target identification, clinical trial optimization, quality assurance, and control and efficient drug distribution method. However, the analysis revealed that China faces several challenges that impact the pace and extent of integration of AI in its pharmaceutical industry. These challenges include a lack of standardized data, a shortage of skilled labor or professionals, and data and privacy concerns. In addition, the research provides three case studies that focused on f XtalPi-AI-Enhanced Drug Discover, BioMap: Accelerating Drug Development Through AI and iCarbonX: AI-Driven Precision Medicine and provided a comprehensive analysis of how these firms have used AI to stimulate their drug discovery process. The study also provides policies that can help improve the integration of AI in the pharmaceutical and drug delivery process. | ||
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