Pharmacogenomics Using Artificial Intelligence

Umesh Kumar Lilhore, PhD is a Professor at Galgotias University, Greater Noida, India with more than 20 years of experience. He has authored ten books and more than 100 research articles in international journals and filed 50 patents across India and the United Kingdom. His research focuses on network security, computer networking, and the Internet of Things. Kaamran Raahemifar, PhD is a Professor in the College of Information Sciences and Technology at Penn State University. He has authored and co-authored numerous highly cited publications and books in reputed international journals and conferences. His research focuses on AI-driven healthcare systems, machine learning, optimization, medical image processing, and intelligent smart systems. Sarita Simaiya, PhD is a Professor at Galgotias University, Greater Noida, India with more than 18 years of experience. She has co-authored several peer-reviewed publications in reputed international journals and conferences, with a focus on integrating emerging AI technologies into healthcare and biomedical research. Her research interests include AI-driven healthcare systems, deep learning models, and intelligent data analytics for biomedical applications. R. Sunder, PhD is an academician and researcher with expertise in artificial intelligence, machine learning, data analytics, and intelligent healthcare systems. His research interests include AI-driven biomedical applications, computational intelligence, and advanced data processing techniques for healthcare and pharmaceutical domains. He has contributed to interdisciplinary research projects and scholarly publications focused on emerging technologies and digital healthcare innovation. R. Lotus, PhD is a researcher and academician specializing in artificial intelligence, computational biology, and healthcare technologies. She has contributed to multidisciplinary research initiatives and scholarly publications focused on advancing digital healthcare, precision medicine, and emerging computational technologies. She is actively engaged in promoting innovative AI solutions for healthcare and biomedical research.

• Preface xv1 Foundations of Pharmacogenomics: Understanding the Genetic Basis of Drug Response 1Dhanesh Kumar, Thangiah Sathishkumar, Sarangam Kodati, Venkata Praveen Kumar Vuppala, Rasmi A. and Rajakumar Perumal1.1 Introduction 21.2 Genetics of Drug Response Mechanisms 51.3 Clinically Actionable Examples 71.4 Implementation Frameworks and Clinical Integration 141.5 New Technologies and Emerging Trends 191.6 Conclusion 202 From Data to Therapy: Artificial Intelligence Applications in Pharmacogenomics 23Yuvaraj Velusamy, L. Gandhimathi, Shaziya Islam, P. Jyothi, Saranya P. and S. Suresh2.1 Introduction 242.2 Data Foundations in AI-Driven Pharmacogenomics 282.3 AI Methodologies in PGx 322.4 Translating Data to Therapy: Key AI-Driven PGx Applications 362.5 Challenges and Limitations 392.6 Future Perspectives 422.7 Conclusion 453 Machine Learning Approaches for Genomic Data Analysis in Pharmacogenomics 49Ashwin M., Sreenivas Mekala, V. Arun, Ashish, S. Mathumohan and K. Kaliraj3.1 Introduction 50Contents vii3.2 Related Works 513.3 Methodology 583.4 Results and Discussions 653.5 Conclusion 714 Deep Learning and Neural Networks: Unlocking Complex Patterns in Genomic Medicine 75M. Sudharsan, K. Maithili, T. Ravi, Margaret Mary T., M. Rajesh Khanna and P. Eswaran4.1 Introduction 764.2 Related Works 784.3 Methodology 814.4 Results and Discussions 894.5 Conclusion 964.6 Future Directions of the Study 965 AI-Driven Drug Discovery: Accelerating Therapeutic Innovation through Genomics 101K. Prakash, Phani Kumar Solleti, Tarak Hussain, Chilukala Mahender Reddy, Margaret Mary T. and P. Arumugam5.1 Introduction 1025.2 Related Works 1045.3 Methodology 1075.4 Results and Discussions 1135.5 Conclusion 1195.6 Future Directions 1206 Personalized Medicine Through Pharmacogenomics and AI: A Precision Therapeutics Approach 125Dafik, Anto Lourdu Xavier Raj Arockia Selvarathinam, Priya K. V., Sreeram Indraneel, C. Ambhika and Ruth Ramya Kalangi6.1 Introduction 1266.2 Related Works 1286.3 Methodology 1336.4 Results and Discussions 1396.5 Discussion 1436.6 Conclusion 1456.7 Future Directions 1467 Real-World Use Cases of AI in Pharmacogenomic Decision Support Systems 149Kayal Padmanandam, IsaiVani Mariyappan, Anitha D., Sachin Chandravadan Karad, Pooja P. Raj and Umesh Kumar Lihore7.1 Introduction 1507.2 Background and Rationale 1537.3 Methodology 1557.5 Discussion 1657.6 Challenges and Barriers to Implementation 1677.7 Future Directions 1687.8 Conclusion 1698 AI Algorithms for Predicting Drug Response in Diverse Populations: Bridging Pharmacogenomics and Precision Medicine 173Fathimathul Rajeena P.P., Rahoof P. P. and Sunder R.8.1 Introduction 174x Contents8.2 Background 1778.3 Methodology 1808.4 Results and Findings 1848.5 Conclusion 1939 Artificial Intelligence for Genetic Variant Detection and Interpretation 197Lokendra Singh Songare, Narendra B. Mustare, Kamepalli Sujatha, Albin Kurian, Aparajita Mukherjee and Umesh Kumar Lilhore9.1 Introduction 1989.2 Related Works 2009.3 Methodology 2049.4 Results and Findings 2089.5 Conclusion 2159.6 Future Directions 21610 Cardiovascular Pharmacogenomics: Genetic Predictors of Drug Response and Toxicity 219Sunder R., Shanimol Shajan, S. Anupkant, Donamol Joseph, D. Vetrithangam and Rasmi A.10.1 Introduction 22010.2 Related Works 22210.3 Methodology 225Contents xi10.4 Results and Findings 22710.5 Conclusion 23610.6 Future Directions 23611 Wearable Devices and Real-Time Pharmacogenomic Monitoring 239P. Kavitha, Sruthy Sukumaran, Kavya Clare P. Shaji, S. Chinnapparaj, Veeraiyah Thangasamy and Sunder R.11.1 Introduction 24011.2 Related Works 24211.3 Methodology 24611.4 Results and Findings 24811.5 General Discussion 25311.6 Conclusions 25411.7 Future Directions 25512 Challenges and Limitations of Applying Artificial Intelligence in Pharmacogenomic Pipelines: Technical, Clinical, and Operational Perspectives 259Yagyesh Godiyal, Maharani Abu Bakar, S. Madhusudhanan, Kochumol Abraham, Aparajita Mukherjee and Sunder R.12.1 Introduction 26012.2 Thematic Analysis of Challenges 26212.3 Identification of Repeated Patterns, Bottlenecks 26912.4 Strategies to Minimize these Challenges 27212.5 Real-World AI Applications in Pharmacogenomics 27712.6 Conclusion 28012.7 Future Research Directions 28013 Ethical Frameworks for Integrating AI in Pharmacogenomics: A Focus on Equity and Justice 285Ika Hesti Agustin, R. Kannamma, Nallametti Nagarjuna, Sheela S., D. Vetrithangam and Thilagavathi K.13.1 Introduction 28613.2 Related Works 28813.3 Research Design 29213.4 Results and Findings 29513.5 Conclusion and Future Work 30314 The Future of AI in Pharmacogenomics: Trends, Innovations, and Global Perspectives 307Sanaj M.S., Minnuja Shelly, Asha S., Nor Asilah Wati Abdul Hamid, S. Mathumohan and Sudhir Ramadass14.1 Introduction 30814.2 Foundations of AI in Pharmacogenomics 31114.3 Present Developments in Pharmacogenomics Using AI 31314.4 Innovations and Emerging Technologies 31714.5 Global Perspectives and Trends 32014.6 Challenges and Limitations 32214.7 Future Directions 32314.8 Conclusion 324References 325Index 329