Artificial Intelligence in Drug Discovery for Neglected and Rare Diseases

Erscheinungsjahr 2026
ISBN: 978-981-9214-30-3
Verlag: Springer

Buch, Englisch, 323 Seiten, Format (B × H): 155 mm x 235 mm

This book offers a comprehensive exploration of how artificial intelligence (AI) is transforming the development of therapeutics for some of the world’s most overlooked infectious diseases, including tuberculosis, malaria, leishmaniasis, and Chagas disease. This book presents state-of-the-art advancements in AI-driven target identification, drug repurposing, and de novo drug design.

It delves into deep learning techniques such as CNNs, RNNs, VAEs, and GANs, for predicting drug-pathogen interactions, enhancing molecular docking, and integrating multi-omics data for biomarker discovery. Practical methodologies are outlined for leveraging AI in ADMET prediction and drug design, with accessible frameworks to support application in real-world research.

The book features case studies that demonstrate how AI addresses key challenges such as drug resistance, toxicity, and vaccine development, while also covering ethical and regulatory considerations critical to ensuring equitable access in low-resource settings.

Designed for scientists in drug discovery, computational biology, and pharmaceutical research, this book serves as an essential guide for applying AI technologies in neglected disease research. By bridging cutting-edge computational methods with practical drug development challenges, it offers a timely and valuable resource for accelerating innovation in global health.

Zielgruppe

Research

Autoren/Hrsg.

Deswal, Geeta

Singh Grewal, Ajmer

Singh Rawat, Manju

Fachgebiete

• Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
• Naturwissenschaften Biowissenschaften Biowissenschaften Genetik und Genomik (nichtmedizinisch)
• Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
• Naturwissenschaften Chemie Physikalische Chemie Quantenchemie, Theoretische Chemie
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Klinische und Innere Medizin
• Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz

Inhaltsverzeichnis

Chapter 1. Introduction to Computational Intelligence in Drug Discovery for Neglected and Rare Diseases.- Chapter 2. Machine Learning for Target Identification in Tuberculosis, Malaria, and Leishmaniasis.- Chapter 3. Deep Learning Approaches for Drug-Pathogen Interaction Prediction in Chagas Disease, African Trypanosomiasis and Tuberculosis.- Chapter 4. Drug Repurposing Using Knowledge Graphs and Transformer-Based Models for Chagas Disease, Schistosomiasis, and Filariasis.- Chapter 5. Generative Models for De Novo Drug Design Against Leishmaniasis and Dengue.- Chapter 6. AI-Enhanced Molecular Docking and Dynamics Simulation Pipelines for Tuberculosis and Leishmaniasis.- Chapter 7. In Silico ADMET and Toxicity Profiling Using QSAR and Deep Learning.- Chapter 8. Multi-Omics Integration and Biomarker Discovery for Tuberculosis and Visceral Leishmaniasis.- Chapter 9. Machine Learning-Driven Vaccine Candidate Identification for Malaria and Leishmaniasis.- Chapter 10. Optimizing Clinical Trials for Rare and Neglected Diseases Using AI.- Chapter 11. AI-Driven Natural Product Screening for Anti-parasitic Drug Discovery in Neglected Tropical Diseases.- Chapter 12. Artificial Intelligence in Epitope Mapping and Immunoinformatics for Rare Parasitic Infections.- Chapter 13. Regulatory, Ethical and Societal Implications of AI in Neglected Diseases Research.- Chapter 14. Future Directions: Explainable AI, Quantum Computing, and Collaborative Innovation.

Über Autor(innen)

Dr. Geeta Deswal, is currently serving as Professor (Pharmacognosy) at Guru Gobind Singh College of Pharmacy, Yamuna Nagar, Haryana, India. She completed her bachelor’s degree from Kurukshetra University, Kurukshetra, Haryana, India and obtained her master’s and Ph.D. degrees from M.M. University, Mullana, Haryana, India. Her research expertise lies in bioactivity-guided extraction, phytochemical screening, herbal formulation standardization, and plant tissue culture techniques, with notable contributions to in silico molecular docking and AI-driven screening of phytoconstituents for therapeutic applications. She owns to her credit 50 publications in national and international journals of repute, 20 book chapters and 15 books. She received the Young Achiever Award on Occasion of Pharma Vision 2K25 by Shree Balaji Books and Innovational Ambassador by MHRD Innovational Cell, AICTE, New Delhi.

Dr. Ajmer Singh Grewal, is currently serving as Professor (Pharmaceutical Chemistry) at Guru Gobind Singh College of Pharmacy, Yamuna Nagar, Haryana, India, is having academic and research experience of 13+ years in medicinal chemistry. He had completed PhD in Pharmaceutical Sciences in the subject area of Computational and Medicinal Chemistry from I.K. Gujral Punjab Technical University, Jalandhar, Punjab (India) in 2019. He is a leading expert in computational chemistry, molecular modeling, and computer-aided drug design (CADD). His research focuses on structure-based drug design, virtual screening, ligand docking, and QSAR studies, utilizing AI and ML-driven computational tools such as AutoDock Vina, MOE, PyMOL, SwissADME, pKCSM, and Schrodinger Suite. His applications in diabetes, cancer, inflammation, and antimicrobial resistance have significantly contributed to pharmaceutical sciences. He owns to his credit more than 120 publications in national and international journals of repute, 25 book chapters, 20 books, 6 patents and 3 designs.

Dr. Manju Singh Rawat, is currently working as Professor at the University Institute of Pharmacy, Pt. Ravishankar Shukla University, Raipur, Chhattisgarh, India. She is a distinguished researcher in pharmaceutical sciences, specializing in nanotechnology-based drug delivery, dermatokinetics, and computational formulation optimization. With over a decade of experience in academia and research, she has significantly contributed to the field of biopolymeric carriers, dermal and transdermal drug delivery systems, and AI-driven predictive modeling for pharmaceutical formulations. She has authored 127+ research papers, book chapters, and keynote presentations, with notable publications in Elsevier and CRC Press. She has successfully led multiple funded research projects focusing on novel drug delivery systems, particularly for psoriasis and protein therapeutics. Dr. Singh’s expertise extends to advanced computational tools like Design Expert software for formulation optimization, enhancing precision in pharmaceutical development. Her contributions to the field, including innovative patent applications and numerous international conference presentations, position her as a thought leader in modern drug delivery and pharmaceutical biotechnology.