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स्क्रिनमा देखिने चुरोट: सुर्तीजन्य हानि न्यूनीकरण नीतिमा दक्षिण एसियाले अझै के छुटाइरहेको छनेपालमा पिसाब नलीको संक्रमण र एन्टिबायोटिक प्रतिरोधको बढ्दो संकटFrontline Perspectives on Nursing Leadership in NepalProtecting the Smallest Lungs from the Hidden Grip of RSV in KathmanduThe Heavy Burden of Bullying on Student Wellbeing in NepalThe Emerging Landscape of Thyroid Health in Central NepalHow a Recent Western Nepal Study is Redefining Anemia DiagnosisHow H. Pylori is Impacting the Health of Karnali’s High-Altitude CommunitiesSweet Poison, Bitter Reality: The Unseen Diabetes Epidemic Among Nepal’s YouthHow Missing Checklists and Protocols are Costing Lives in Nepal’s ERsस्क्रिनमा देखिने चुरोट: सुर्तीजन्य हानि न्यूनीकरण नीतिमा दक्षिण एसियाले अझै के छुटाइरहेको छनेपालमा पिसाब नलीको संक्रमण र एन्टिबायोटिक प्रतिरोधको बढ्दो संकटFrontline Perspectives on Nursing Leadership in NepalProtecting the Smallest Lungs from the Hidden Grip of RSV in KathmanduThe Heavy Burden of Bullying on Student Wellbeing in NepalThe Emerging Landscape of Thyroid Health in Central NepalHow a Recent Western Nepal Study is Redefining Anemia DiagnosisHow H. Pylori is Impacting the Health of Karnali’s High-Altitude CommunitiesSweet Poison, Bitter Reality: The Unseen Diabetes Epidemic Among Nepal’s YouthHow Missing Checklists and Protocols are Costing Lives in Nepal’s ERs

The AI Revolution: Shaping the Present and Future of Pharmaceutical Research and Development.

Researchers

Krishna Chandra Panda, B V V Ravi Kumar, Jammula Sruti, Ch Niranjan Patro, Bimalendu Chowdhury, H K Sundeep Kumar

Abstract

The transformative role of artificial intelligence (AI) in the pharmaceutical industry is examined, with a focus on its significant contributions to drug discovery, development, and clinical trial processes. It highlights the inefficiencies and high costs associated with traditional drug development and explores how AI and machine learning (ML) can enhance these processes by analyzing extensive biological datasets. The historical context of AI in pharmaceutical development is examined, noting how advances in computational power and data accessibility have facilitated innovative methodologies, such as predictive analytics and natural language processing. Contemporary trends reveal the integration of AI technologies in drug design, repurposing, and patient response forecasting. This study also addresses the challenges of participant recruitment for clinical trials and proposes AI-driven solutions to optimize patient selection and data management. Furthermore, it discusses AI's role in tailored medicine, emphasizing its potential for advancing precision therapy through targeted drug development and personalized treatment strategies. The importance of digital tools, genomic data analysis, and AI-driven imaging technologies for customizing therapeutic approaches is underscored, along with the regulatory and ethical challenges posed by AI deployment in healthcare. This study illustrates the complexities of AI applications in the pharmaceutical sector, offering insights into both successful and unsuccessful initiatives. The findings suggest that the digitalization of the pharmaceutical industry and enhanced AI integration hold promise for developing safer and more effective therapeutic strategies, while also identifying obstacles to their widespread adoption and optimal functionality.
Source: PubMed (PMID: 42706967)View Original on PubMed