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2000
Volume 3, Issue 1
  • ISSN: 2950-3752
  • E-ISSN: 2950-3760

Abstract

The revolution of Artificial Intelligence has created a greater change with accelerated change in Pharmaceutical product development. Artificial intelligence reduces the workload of humans, improves the target and thereby increases the productivity of pharmaceutical products. The large volume of data can be integration with automation. Artificial intelligence-based drugs have entered clinical trials and, in a few instances, came to market recently. AI utilizes systems and software that can interpret and learn from the input data to make independent decisions for accomplishing specific objectives. Artificial intelligence assists in rational drug design, decision-making, right therapy, personalized medicine, clinical data management, . In pharmaceutical formulation development artificial intelligence supports in deciding a suitable excipient for the pharmaceutical formulation development, closely monitoring and modifying a pharmaceutical development process, and ensures in-process specification compliances. Artificial intelligence predicts the development process, toxicity, and biological activity of a desired compound. Overall, the hit and lead drug molecules can be identified by artificial intelligence. This study highlights the impactful use of artificial intelligence in diverse areas of the pharmaceutical sectors ., drug discovery and development, drug repurposing, improving pharmaceutical productivity, clinical trials, . The ongoing challenge, and ways to overcome them, along with the future of AI in the pharmaceutical industry, is also discussed.

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2025-08-18

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/content/journals/cai/10.2174/0129503752359512250325061847
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Artificial Intelligence in Pharmaceutical Drug Development-challenges and the Way Forward
Curr Arti Intell 3, E29503752359512 (2025); https://doi.org/10.2174/0129503752359512250325061847
/content/journals/cai/10.2174/0129503752359512250325061847
/content/journals/cai/10.2174/0129503752359512250325061847
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  • Article Type:     Review Article
Keyword(s): Artificial intelligence; clinical trials; drug discovery; personalized medicine; product development; quality assurance

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