Revolutionizing Healthcare: AI-driven Innovations in Drug Development and Personalized Medicine

Abstract: The precision, speed, and efficiency of healthcare solutions are being improved by artificial intelligence (AI), which is drastically changing the pharmaceutical manufacturing and customized medicine industries. The many ways that AI is transforming drug development, optimization, diagnostics, and patient-specific therapy approaches are examined in this paper. In order to forecast medication responses, find new treatment targets, and reduce side effects, artificial intelligence (AI) systems examine enormous datasets, such as genetic profiles, electronic medical records, and empirical data. AI greatly cuts down on development time and expense in pharmaceutical research by enabling structure-based virtual screening, de novo drug discovery, and repurposing of already-approved medications. While systems like IBM Watson and in silico medicine improve clinical decision-making and predictive analytics, tools like AlphaFold and Deep Docking are leading the way in protein structure prediction and molecular interaction modelling. AI enables early illness identification, real-time wearable monitoring, and genomics-driven therapeutic customisation in personalized medicine. Through automation, quality control, and predictive maintenance, AI also improves pharmaceutical production, guaranteeing constant product quality and regulatory compliance. Notwithstanding its promise, issues, including algorithmic bias, data privacy, regulatory validation, and the requirement for explainable AI, still exist. To effectively utilize AI's disruptive potential in healthcare, these obstacles must be removed. Recent clinical trials and scientific advances are also highlighted in the paper, including virtual clinical simulations, AI-powered diagnostics, and COVID-19 drug development supported by AI. All things considered, artificial intelligence is not only simplifying pharmaceutical procedures but also opening the door to more efficient, individualized, and easily available healthcare. By making treatments safer, quicker, and more individualized for each patient, its ongoing integration holds the potential to completely transform international health systems.

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Publication Details

Journal
Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicine
Published
2025-09-19
DOI
https://doi.org/10.2174/0118756921395626250905121219
Primary Topic
Biomedical and Engineering Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Revolutionizing Healthcare: AI-driven Innovations in Drug Development and Personalized Medicine

Chirag Jain, Shikha Baghel Chauhan, Indu Singh, Dhruv Pratap SIngh Jaitawat
Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicine
Biomedical and Engineering Education
article

Revolutionizing Healthcare: AI-driven Innovations in Drug Development and Personalized Medicine

Chirag Jain, Shikha Baghel Chauhan, Indu Singh, Dhruv Pratap SIngh Jaitawat
article en

Abstract

Abstract: The precision, speed, and efficiency of healthcare solutions are being improved by artificial intelligence (AI), which is drastically changing the pharmaceutical manufacturing and customized medicine industries. The many ways that AI is transforming drug development, optimization, diagnostics, and patient-specific therapy approaches are examined in this paper. In order to forecast medication responses, find new treatment targets, and reduce side effects, artificial intelligence (AI) systems examine enormous datasets, such as genetic profiles, electronic medical records, and empirical data. AI greatly cuts down on development time and expense in pharmaceutical research by enabling structure-based virtual screening, de novo drug discovery, and repurposing of already-approved medications. While systems like IBM Watson and in silico medicine improve clinical decision-making and predictive analytics, tools like AlphaFold and Deep Docking are leading the way in protein structure prediction and molecular interaction modelling. AI enables early illness identification, real-time wearable monitoring, and genomics-driven therapeutic customisation in personalized medicine. Through automation, quality control, and predictive maintenance, AI also improves pharmaceutical production, guaranteeing constant product quality and regulatory compliance. Notwithstanding its promise, issues, including algorithmic bias, data privacy, regulatory validation, and the requirement for explainable AI, still exist. To effectively utilize AI's disruptive potential in healthcare, these obstacles must be removed. Recent clinical trials and scientific advances are also highlighted in the paper, including virtual clinical simulations, AI-powered diagnostics, and COVID-19 drug development supported by AI. All things considered, artificial intelligence is not only simplifying pharmaceutical procedures but also opening the door to more efficient, individualized, and easily available healthcare. By making treatments safer, quicker, and more individualized for each patient, its ongoing integration holds the potential to completely transform international health systems.

Current pharmacogenomics and personalized medicine (Online)/Current pharmacogenomics and personalized medicineVol. 22
Amity University (IN)
Openalex Percentile: Top 75%
Biomedical and Engineering Education
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