Artificial Intelligence in the Biomedical Field

Artificial Intelligence (AI) has profoundly transformed the healthcare and pharmaceutical industries, markedly influencing clinical decision support, disease diagnostics, and process automation.AI technologies like machine learning (ML), natural language processing (NLP), and deep learning (DL) have broadened the scope of AI applications, facilitating advancements in personalized medicine. In the pharmaceutical industry, AI is employed throughout multiple phases, spanning from drug discovery to product lifecycle management. AI technologies such as ML, DL, AI-based quantitative structure-activity relationship (QSAR), virtual screening (VS), support vector machines (SVMs), and neural networks are utilized in drug screening and design processes. AI also plays a pivotal role in pharmaceutical product development, encompassing tasks such as excipient selection, process optimization, and quality control. The AlphaFold2 system, leveraging AI, demonstrated superior performance in accurately predicting the three-dimensional structures of proteins. AI has revolutionized drug discovery, traditionally a time-consuming and costly process, by accelerating the identification of potential drug candidates and minimizing the reliance on extensive laboratory testing. In pharmacy practice, AI shows significant potential for applications such as clinical decision support systems, automated medication dispensing, inventory management, adverse drug reaction detection, and personalized medication regimens. However, the integration of AI into pharmacy practice is still nascent. AI has the capability to discern patterns within extensive biomedical datasets, presenting both new opportunities and challenges for the pharmaceutical sciences and industries.

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Publication Details

Journal
Research Journal of Pharmacy and Technology
Published
2025-02-27
DOI
https://doi.org/10.52711/0974-4150.2025.00006
Citations
1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.65
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article

Artificial Intelligence in the Biomedical Field

Vijay Patil, Amol R. Pawar, Animesh. D. Ahire, Chetna. R. Mahajan et al.
1 citations
Research Journal of Pharmacy and Technology
Artificial Intelligence in Healthcare and Education
0.65
article

Artificial Intelligence in the Biomedical Field

Vijay Patil, Amol R. Pawar, Animesh. D. Ahire, Chetna. R. Mahajan, Ranvijay. G. Girase
article en
1 citations

Abstract

Artificial Intelligence (AI) has profoundly transformed the healthcare and pharmaceutical industries, markedly influencing clinical decision support, disease diagnostics, and process automation.AI technologies like machine learning (ML), natural language processing (NLP), and deep learning (DL) have broadened the scope of AI applications, facilitating advancements in personalized medicine. In the pharmaceutical industry, AI is employed throughout multiple phases, spanning from drug discovery to product lifecycle management. AI technologies such as ML, DL, AI-based quantitative structure-activity relationship (QSAR), virtual screening (VS), support vector machines (SVMs), and neural networks are utilized in drug screening and design processes. AI also plays a pivotal role in pharmaceutical product development, encompassing tasks such as excipient selection, process optimization, and quality control. The AlphaFold2 system, leveraging AI, demonstrated superior performance in accurately predicting the three-dimensional structures of proteins. AI has revolutionized drug discovery, traditionally a time-consuming and costly process, by accelerating the identification of potential drug candidates and minimizing the reliance on extensive laboratory testing. In pharmacy practice, AI shows significant potential for applications such as clinical decision support systems, automated medication dispensing, inventory management, adverse drug reaction detection, and personalized medication regimens. However, the integration of AI into pharmacy practice is still nascent. AI has the capability to discern patterns within extensive biomedical datasets, presenting both new opportunities and challenges for the pharmaceutical sciences and industries.

Research Journal of Pharmacy and Technology
Kavayitri Bahinabai Chaudhari North Maharashtra University (IN)
Openalex Percentile: Top 26%
Artificial Intelligence in Healthcare and Education
0.65
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