Machine Learning Approaches for Enhancing Drug Discovery and Development in Healthcare
Cover
PDF

Keywords

Drug Discovery
Healthcare
Pharmaceutical Research
Clinical Trials
Surgical Robotics

How to Cite

[1]
Dr. Helena Santos, “Machine Learning Approaches for Enhancing Drug Discovery and Development in Healthcare: AI Models for Accelerating Pharmaceutical Research and Clinical Trials”, Journal of Bioinformatics and Artificial Intelligence, vol. 3, no. 2, pp. 277–291, Sep. 2023, Accessed: Nov. 22, 2024. [Online]. Available: https://biotechjournal.org/index.php/jbai/article/view/108

Abstract

Drug discovery and development underpin the healthcare system and have a significant impact on the modern world. A wide range of complex diseases and symptoms arising from genetic traits and multi-omics interactions raises the bar for supervised pharmaceutical research and development. Usually, it takes over 12 to 15 years to introduce new drugs from early development to the commercial market, with luck to gain market approval. As a result of implementing guidelines and global pharmaceutical standard practices, the R&D process to access innovation between large companies, start-ups, and research centers is systematic, which involves launching drug-related R&D projects, biological systems, compound libraries, high-throughput and high-content screening, hit-to-lead and lead optimization, in vitro and in vivo evaluation, clinical trials, pharmacokinetics, absorption, and pharmacodynamics, toxicity testing, scientific advisory review, and market approval. Despite this, obtaining market approval remains a significant challenge for drug developers. Innovative approaches such as phenotypic screening and authorized therapy in healthcare are required. Therefore, to cope with these healthcare challenges, it is essential for pharmaceutical researchers and manufacturers to introduce high-throughput screening and early identification approaches that can accelerate new and helpful innovations by developing effective and safe drugs.

PDF

References

Prabhod, Kummaragunta Joel. "Deep Learning Models for Predictive Maintenance in Healthcare Equipment." Asian Journal of Multidisciplinary Research & Review 1.2 (2020): 170-214.

Pushadapu, Navajeevan. "AI and Seamless Data Flow to Health Information Exchanges (HIE): Advanced Techniques and Real-World Applications." Journal of Machine Learning in Pharmaceutical Research 2.1 (2022): 10-55.

Bao, Y.; Qiao, Y.; Choi, J.E.; Zhang, Y.; Mannan, R.; Cheng, C.; He, T.; Zheng, Y.; Yu, J.; Gondal, M.; et al. Targeting the lipid kinase PIKfyve upregulates surface expression of MHC class I to augment cancer immunotherapy. Proc. Natl. Acad. Sci. USA 2023, 120, e2314416120.

Gayam, Swaroop Reddy. "AI for Supply Chain Visibility in E-Commerce: Techniques for Real-Time Tracking, Inventory Management, and Demand Forecasting." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 218-251.

Nimmagadda, Venkata Siva Prakash. "AI-Powered Risk Management and Mitigation Strategies in Finance: Advanced Models, Techniques, and Real-World Applications." Journal of Science & Technology 1.1 (2020): 338-383.

Putha, Sudharshan. "AI-Driven Metabolomics: Uncovering Metabolic Pathways and Biomarkers for Disease Diagnosis and Treatment." Distributed Learning and Broad Applications in Scientific Research 6 (2020): 354-391.

Sahu, Mohit Kumar. "Machine Learning Algorithms for Enhancing Supplier Relationship Management in Retail: Techniques, Tools, and Real-World Case Studies." Distributed Learning and Broad Applications in Scientific Research 6 (2020): 227-271.

Kasaraneni, Bhavani Prasad. "Advanced Machine Learning Algorithms for Loss Prediction in Property Insurance: Techniques and Real-World Applications." Journal of Science & Technology 1.1 (2020): 553-597.

Kondapaka, Krishna Kanth. "Advanced AI Techniques for Optimizing Claims Management in Insurance: Models, Applications, and Real-World Case Studies." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 637-668.

Kasaraneni, Ramana Kumar. "AI-Enhanced Cybersecurity in Smart Manufacturing: Protecting Industrial Control Systems from Cyber Threats." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 747-784.

Pattyam, Sandeep Pushyamitra. "AI in Data Science for Healthcare: Advanced Techniques for Disease Prediction, Treatment Optimization, and Patient Management." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 417-455.

Kuna, Siva Sarana. "AI-Powered Techniques for Claims Triage in Property Insurance: Models, Tools, and Real-World Applications." Australian Journal of Machine Learning Research & Applications 1.1 (2021): 208-245.

Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence for Automated Loan Underwriting in Banking: Advanced Models, Techniques, and Real-World Applications." Journal of Artificial Intelligence Research and Applications 2.1 (2022): 174-218.

Prabhod, Kummaragunta Joel. "Leveraging Generative AI for Personalized Medicine: Applications in Drug Discovery and Development." Journal of AI-Assisted Scientific Discovery 3.1 (2023): 392-434.

Pushadapu, Navajeevan. "AI-Enhanced Techniques for Pattern Recognition in Radiology Imaging: Applications, Models, and Case Studies." Journal of Bioinformatics and Artificial Intelligence 2.1 (2022): 153-190.

Gayam, Swaroop Reddy. "AI-Driven Customer Support in E-Commerce: Advanced Techniques for Chatbots, Virtual Assistants, and Sentiment Analysis." Distributed Learning and Broad Applications in Scientific Research 6 (2020): 92-123.

Nimmagadda, Venkata Siva Prakash. "Artificial Intelligence and Blockchain Integration for Enhanced Security in Insurance: Techniques, Models, and Real-World Applications." African Journal of Artificial Intelligence and Sustainable Development 1.2 (2021): 187-224.

Putha, Sudharshan. "AI-Driven Molecular Docking Simulations: Enhancing the Precision of Drug-Target Interactions in Computational Chemistry." African Journal of Artificial Intelligence and Sustainable Development 1.2 (2021): 260-300.

Sahu, Mohit Kumar. "Machine Learning for Anti-Money Laundering (AML) in Banking: Advanced Techniques, Models, and Real-World Case Studies." Journal of Science & Technology 1.1 (2020): 384-424.

Kasaraneni, Bhavani Prasad. "Advanced Artificial Intelligence Techniques for Predictive Analytics in Life Insurance: Enhancing Risk Assessment and Pricing Accuracy." Distributed Learning and Broad Applications in Scientific Research 5 (2019): 547-588.

Kondapaka, Krishna Kanth. "Advanced AI Techniques for Retail Supply Chain Sustainability: Models, Applications, and Real-World Case Studies." Journal of Science & Technology 1.1 (2020): 636-669.

Kasaraneni, Ramana Kumar. "AI-Enhanced Energy Management Systems for Electric Vehicles: Optimizing Battery Performance and Longevity." Journal of Science & Technology 1.1 (2020): 670-708.

Pattyam, Sandeep Pushyamitra. "AI in Data Science for Predictive Analytics: Techniques for Model Development, Validation, and Deployment." Journal of Science & Technology 1.1 (2020): 511-552.

Kuna, Siva Sarana. "AI-Powered Solutions for Automated Underwriting in Auto Insurance: Techniques, Tools, and Best Practices." Journal of Science & Technology 1.1 (2020): 597-636.

Downloads

Download data is not yet available.