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Produktbild: Pharmacogenomics Using Artificial Intelligence
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Pharmacogenomics Using Artificial Intelligence Optimizing Drug Response Through Personalized Genomic Analysis

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Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

27.07.2026

Herausgeber

Umesh Kumar Lilhore + weitere

Verlag

WILEY

Seitenzahl

352

Sprache

Englisch

ISBN

978-1-394-40443-8

Beschreibung

Portrait

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.

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

27.07.2026

Herausgeber

Verlag

WILEY

Seitenzahl

352

Sprache

Englisch

ISBN

978-1-394-40443-8

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: GPSR Kontakt

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  • Produktbild: Pharmacogenomics Using Artificial Intelligence

  • Preface xv

    1 Foundations of Pharmacogenomics: Understanding the Genetic Basis of Drug Response 1
    Dhanesh Kumar, Thangiah Sathishkumar, Sarangam Kodati, Venkata Praveen Kumar Vuppala, Rasmi A. and Rajakumar Perumal

    1.1 Introduction 2
    1.2 Genetics of Drug Response Mechanisms 5
    1.3 Clinically Actionable Examples 7
    1.4 Implementation Frameworks and Clinical Integration 14
    1.5 New Technologies and Emerging Trends 19
    1.6 Conclusion 20

    2 From Data to Therapy: Artificial Intelligence Applications in Pharmacogenomics 23
    Yuvaraj Velusamy, L. Gandhimathi, Shaziya Islam, P. Jyothi, Saranya P. and S. Suresh

    2.1 Introduction 24
    2.2 Data Foundations in AI-Driven Pharmacogenomics 28
    2.3 AI Methodologies in PGx 32
    2.4 Translating Data to Therapy: Key AI-Driven PGx Applications 36
    2.5 Challenges and Limitations 39
    2.6 Future Perspectives 42
    2.7 Conclusion 45

    3 Machine Learning Approaches for Genomic Data Analysis in Pharmacogenomics 49
    Ashwin M., Sreenivas Mekala, V. Arun, Ashish, S. Mathumohan and K. Kaliraj

    3.1 Introduction 50Contents vii
    3.2 Related Works 51
    3.3 Methodology 58
    3.4 Results and Discussions 65
    3.5 Conclusion 71

    4 Deep Learning and Neural Networks: Unlocking Complex Patterns in Genomic Medicine 75
    M. Sudharsan, K. Maithili, T. Ravi, Margaret Mary T., M. Rajesh Khanna and P. Eswaran

    4.1 Introduction 76
    4.2 Related Works 78
    4.3 Methodology 81
    4.4 Results and Discussions 89
    4.5 Conclusion 96
    4.6 Future Directions of the Study 96

    5 AI-Driven Drug Discovery: Accelerating Therapeutic Innovation through Genomics 101
    K. Prakash, Phani Kumar Solleti, Tarak Hussain, Chilukala Mahender Reddy, Margaret Mary T. and P. Arumugam

    5.1 Introduction 102
    5.2 Related Works 104
    5.3 Methodology 107
    5.4 Results and Discussions 113
    5.5 Conclusion 119
    5.6 Future Directions 120

    6 Personalized Medicine Through Pharmacogenomics and AI: A Precision Therapeutics Approach 125
    Dafik, Anto Lourdu Xavier Raj Arockia Selvarathinam, Priya K. V., Sreeram Indraneel, C. Ambhika and Ruth Ramya Kalangi

    6.1 Introduction 126
    6.2 Related Works 128
    6.3 Methodology 133
    6.4 Results and Discussions 139
    6.5 Discussion 143
    6.6 Conclusion 145
    6.7 Future Directions 146

    7 Real-World Use Cases of AI in Pharmacogenomic Decision Support Systems 149
    Kayal Padmanandam, IsaiVani Mariyappan, Anitha D., Sachin Chandravadan Karad, Pooja P. Raj and Umesh Kumar Lihore

    7.1 Introduction 150
    7.2 Background and Rationale 153
    7.3 Methodology 155
    7.5 Discussion 165
    7.6 Challenges and Barriers to Implementation 167
    7.7 Future Directions 168
    7.8 Conclusion 169

    8 AI Algorithms for Predicting Drug Response in Diverse Populations: Bridging Pharmacogenomics and Precision Medicine 173
    Fathimathul Rajeena P.P., Rahoof P. P. and Sunder R.

    8.1 Introduction 174x Contents
    8.2 Background 177
    8.3 Methodology 180
    8.4 Results and Findings 184
    8.5 Conclusion 193

    9 Artificial Intelligence for Genetic Variant Detection and Interpretation 197
    Lokendra Singh Songare, Narendra B. Mustare, Kamepalli Sujatha, Albin Kurian, Aparajita Mukherjee and Umesh Kumar Lilhore

    9.1 Introduction 198
    9.2 Related Works 200
    9.3 Methodology 204
    9.4 Results and Findings 208
    9.5 Conclusion 215
    9.6 Future Directions 216

    10 Cardiovascular Pharmacogenomics: Genetic Predictors of Drug Response and Toxicity 219
    Sunder R., Shanimol Shajan, S. Anupkant, Donamol Joseph, D. Vetrithangam and Rasmi A.

    10.1 Introduction 220
    10.2 Related Works 222
    10.3 Methodology 225Contents xi
    10.4 Results and Findings 227
    10.5 Conclusion 236
    10.6 Future Directions 236

    11 Wearable Devices and Real-Time Pharmacogenomic Monitoring 239
    P. Kavitha, Sruthy Sukumaran, Kavya Clare P. Shaji, S. Chinnapparaj, Veeraiyah Thangasamy and Sunder R.

    11.1 Introduction 240
    11.2 Related Works 242
    11.3 Methodology 246
    11.4 Results and Findings 248
    11.5 General Discussion 253
    11.6 Conclusions 254
    11.7 Future Directions 255

    12 Challenges and Limitations of Applying Artificial Intelligence in Pharmacogenomic Pipelines: Technical, Clinical, and Operational Perspectives 259
    Yagyesh Godiyal, Maharani Abu Bakar, S. Madhusudhanan, Kochumol Abraham, Aparajita Mukherjee and Sunder R.

    12.1 Introduction 260
    12.2 Thematic Analysis of Challenges 262
    12.3 Identification of Repeated Patterns, Bottlenecks 269
    12.4 Strategies to Minimize these Challenges 272
    12.5 Real-World AI Applications in Pharmacogenomics 277
    12.6 Conclusion 280
    12.7 Future Research Directions 280

    13 Ethical Frameworks for Integrating AI in Pharmacogenomics: A Focus on Equity and Justice 285
    Ika Hesti Agustin, R. Kannamma, Nallametti Nagarjuna, Sheela S., D. Vetrithangam and Thilagavathi K.

    13.1 Introduction 286
    13.2 Related Works 288
    13.3 Research Design 292
    13.4 Results and Findings 295
    13.5 Conclusion and Future Work 303

    14 The Future of AI in Pharmacogenomics: Trends, Innovations, and Global Perspectives 307
    Sanaj M.S., Minnuja Shelly, Asha S., Nor Asilah Wati Abdul Hamid, S. Mathumohan and Sudhir Ramadass

    14.1 Introduction 308
    14.2 Foundations of AI in Pharmacogenomics 311
    14.3 Present Developments in Pharmacogenomics Using AI 313
    14.4 Innovations and Emerging Technologies 317
    14.5 Global Perspectives and Trends 320
    14.6 Challenges and Limitations 322
    14.7 Future Directions 323
    14.8 Conclusion 324

    References 325
    Index 329