Electronics and Communications Technology

Predictive Models in Biology
Charting the Future with AI

Editors: Barenya Bikash Hazarika, PhD
A. V. Senthil Kumar, DSc
Harjeet Singh, PhD
Hetalkumar J. Panchal, PhD

Predictive Models in Biology

In Production
Pub Date: Forthcoming April 2027
Hardback Price: $200 USD | £150 UK
Hard ISBN: 9781779647634
E-Book ISBN: 978-1-77964-764-1
Pages: Est 370 pp w index
Binding Type: Hardback / ebook
Notes: 11 color and 37 b/w illustrations

Once centered primarily on observation and explanation, the life sciences have now entered an era where forecasting, simulation, and intelligent decision-making are becoming essential to discovery. The rapid expansion of biological data—from genomics and imaging to clinical records and environmental monitoring—has empowered predictive models to move from helpful tools to central drivers of innovation. Today, artificial intelligence and machine learning are redefining how we diagnose diseases, design drugs, monitor public health, and even teach biology, marking a change toward a more anticipatory and precision-driven approach to understanding life.

This new book, Predictive Models in Biology: Charting the Future with AI, offers an integrative overview of how AI is influencing diverse biological domains. The chapters span four major themes: the foundations and applications of predictive modeling in healthcare, education, and food safety; essential AI and ML concepts tailored for biologists; transformative breakthroughs in computational drug discovery; and emerging intersections between AI, public health, occupational safety, and modern biological research.

Across these sections, the book accentuates both technological possibilities and human responsibilities. From precision medicine and smart healthcare systems to multi-omics integration and predictive microbiology, the book highlights how computational techniques accelerate discovery while raising important considerations regarding ethics, transparency, and equitable access. In drug development, AI-driven approaches are shown to reduce costs, shorten timelines, and improve therapeutic innovation. Meanwhile, global challenges such as pandemics, food safety, and workplace health are increasingly addressed through predictive analytics and real-time data-driven insights.

Chapters cover data-driven AI approaches for precision diagnosis and prognosis in modern healthcare; predictive microbiology for improving food safety; AI in drug discovery and development; AI in epidemiology and public health, occupational health, and environmental management; and more.

Bringing together different perspectives, methods, and examples that show how biology is moving toward greater accuracy and foresight by using AI, the volume shows that predictive models and AI are not stand-alone tools but agents of systemic change.

CONTENTS:
Preface

1. Data-Driven AI Approaches for Precision Diagnosis and Prognosis in Modern Healthcare
Zijian Zhao and Zihuai Lin

2. Artificial Intelligence in Disease Diagnosis and Prognosis
S Nandini, Nagalambika, Sabita Rani Lal, and S. Nalini

3. Predictive Models in Biology: Charting the Future with AI
Sonia Sharma and Piyali Sarkar

4. The Potential of Predictive Microbiology for Improving Food Safety in Developing Countries
Archana Kumari, Priya Sharma, Ravinesh Mishra, and Bhartendu Sharma

5. Beyond the Petri Dish: The Convergence of AI, Biology, and Human Insight
Sarvagya Jha

6. Future Directions of AI, Bioinformatics, and Beyond
Nehal Rami

7. Artificial Intelligence for Disease Diagnosis and Prognosis in Smart Healthcare
Nitumani Sarmah

8. AI in Drug Discovery and Development
Sweta Prasad and Hridoy R. Bairagya

9. Artificial Intelligence in Pharmacophore Modeling: Implications for Drug Repurposing
Ananyo Mazumdar, Aditya Das, and Semanti Ghosh

10. Significance of In-Silico Approaches in Modern Drug Discovery: A New Plan of Action for Pharmaceutical Industries
Sanjib Kumar Das, Suman Lamichhane, Bhargab Jyoti Sahariah, and Manoj Kumar Deka

11. AI in Epidemiology and Public Health: Revolutionizing Disease Surveillance and Intervention
Sapna Deshwal

12. Toward Zero Harm: The Role of Artificial Intelligence in Occupational Health, Safety, and Environmental Management
Pramod N. Nair

13. Emerging Trends at the Intersection of Artificial Intelligence and Biology: A New Frontier in Life Sciences
Kamna Sharma and Bhavana Sharma

14. Emerging Artificial Intelligence-Driven Innovations in Drug Development And Discovery
Veena Gayathri Krishnaswamy, P. Sankar, Haritha S., and Vaidehi A Nair

Index


About the Authors / Editors:
Editors: Barenya Bikash Hazarika, PhD
Assistant Professor of Computer Science and Engineering, Assam down town University, India

Barenya Bikash Hazarika, PhD, is an academic and researcher in the field of machine learning, deep learning, and data science. He received a PhD in Computer Science and Engineering from the National Institute of Technology, Arunachal Pradesh, India. He is currently serving as an Assistant Professor of Computer Science and Engineering at Assam down town University, India. His research interests include the class imbalance learning problem, predictive modeling, medical imaging, and applications of AI in biology and healthcare. Dr. Hazarika has over 30 journal publications, many indexed in SCIE/SCI and/or Scopus, in addition to several conference publications. He has over 1100 Google Scholar citations as of July 2025. He is an editorial board member and reviewer for many prestigious international journals, including IEEE Transactions and journals published by Springer, Elsevier, MDPI, and Taylor and Francis. He is also a committee member for various international conferences.

A. V. Senthil Kumar, DSc
Professor and Principal, Nehru Institute of Information Technology and Management, Coimbatore, Tamil Nadu, India

A. V. Senthil Kumar, DSc, is working as a Professor and Principal at the Nehru Institute of Information Technology and Management, Coimbatore, Tamil Nadu, India. He has worked as Professor and Director of the PG and Research Department of Computer Applications at Hindusthan College of Arts & Science, Coimbatore, Tamilnadu, for more than 15 years and as Senior Grade Lecturer at CMS College of Science and Commerce, India, for 14 years. To his credit, he has industrial experience of five years and teaching experience of 29 years. He has received his Doctor of Science (DSc in Computer Science). He has to his credit over 85 book chapters, over 230 papers in international and national journals, over 85 papers in international conferences and national conferences, and edited nearly 20 books and three textbooks. He is as Associate Editor of IEEE Access, editor-in-chief for many journals, and a key member for Machine Intelligence Research Labs (MIR Labs), India. He is an editorial board member and reviewer for various international journals and is a committee member for various international conferences.

Harjeet Singh, PhD
Assistant Professor, NSIT-IFSCS (affiliated with the National Forensic Science University), Ahmedabad, India

Harjeet Singh, PhD, an accomplished biotechnologist, serves as an Assistant Professor at NSIT-IFSCS, Ahmedabad, India, which is affiliated with the National Forensic Science University. Holding a PhD in Botany with a specialization in Clinical Mycology, his multidisciplinary expertise spans forensic mycology, environmental microbiology, and clinical mycology. Dr. Singh is renowned for his innovative contributions, including the trademarked “Myco-Fingerprinting™,” a novel forensic methodology that has enhanced crime scene investigations through fungal evidence analysis. Dr. Singh’s research portfolio is extensive, encompassing advancements in fungal enzymes, molecular markers, and nanotechnology applications. His government-funded project (GSBTM-DST) has led to significant breakthroughs, notably in optimizing cellulase activity in fungal strains for biomass saccharification. A prolific scholar, Dr. Singh has authored numerous high-impact publications in Scopus-indexed journals, contributed chapters to acclaimed scientific books, and authored and edited books and laboratory manuals. He also mentors PhD and MSc students.

Hetalkumar J. Panchal, PhD
Professor, P.G. Department of Biosciences, Sardar Patel University (SPU), Vallabh Vidyanagar, Gujarat, India

Hetalkumar J. Panchal, PhD, is a Professor in the P.G. Department of Biosciences, Sardar Patel University (SPU), Vallabh Vidyanagar, Gujarat, India. He has worked as biochemist for two years at Makupa Chemists Ltd., Kenya. He was the first PhD guide in the subject of bioinformatics in the state of Gujarat. He has published more than 60 papers in national journals and international journals and also presented more than 50 papers at national and international conferences and seminars. He has attended many conferences outside India, lastly in Chicago USA, with the funding of the Department of Biotechnology (DBT), Govt. of India. He is a member of the Indian Science Congress Association and a life member of the Computer Society of India and other reputed scientific society. He has acted as an invited speaker and judge at more than 50 conferences, seminars, and workshops. He is acting as an associate editor and member of the editorial boards of more than 25 journals and international magazines. He is member of the course design committee for graduate level under Choice Based Credit System (CBCS). Dr. Panchal completed his graduate, postgraduate, and doctorate studies in Biochemistry at the P.G. Department of Biosciences at SPU. He also has a Post-BSc Diploma in Computer Science and Applications (PGDCA) from SPU, Post Graduate Diploma in Bioinformatics (PGDBI) from BII New Delhi, Diploma in Naturopathy and Yogic Science (NYS), and Bachelor of Legislative Law (LLB) from SPU.




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