- Neu
A New Era of Drug Discovery
Buch, Englisch, 261 Seiten, Format (B × H): 155 mm x 235 mm
ISBN: 978-981-9208-74-6
Verlag: Springer
This book explores the transformative convergence of AI and phytochemistry. The book shows how AI is revolutionizing the discovery, design, and development of plant-based bioactive compounds by providing tools for structure identification, pharmacological prediction, compound optimization, and synthesis planning. Through machine learning, data analytics, and computational modeling, it demonstrates how AI accelerates and advances traditional phytochemical research.
Phytochemistry—the study of natural plant compounds—has long been foundational to drug discovery. Historically reliant on labor-intensive experiments, the field now faces a paradigm shift. AI offers scalable, data-driven methods that boost speed and accuracy, bridging classical phytochemistry with modern pharmaceutical innovation.
The book begins with foundational chapters on traditional phytochemistry and AI integration, including data sourcing and supply chain challenges. It then covers AI-assisted techniques for synthesis, extraction, isolation, and structural elucidation of bioactives. Later sections focus on simulation and optimization of drug candidates—such as property prediction, docking, virtual screening, and optimization algorithms. The final chapters explore pharmacological applications, collaborative models, ethical and legal considerations, and AI’s global impact in democratizing drug discovery.
This book is ideal for researchers, academicians, and professionals in pharmaceutical sciences, biotechnology, and phytochemistry. It also serves students, trainees, and policymakers interested in the intersection of AI and natural product-based drug discovery.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
- Naturwissenschaften Chemie Organische Chemie
- Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Pharmakologie, Toxikologie
- Naturwissenschaften Biowissenschaften Botanik
- Mathematik | Informatik EDV | Informatik Angewandte Informatik Bioinformatik
- Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie
- Mathematik | Informatik EDV | Informatik Informatik Künstliche Intelligenz
- Naturwissenschaften Biowissenschaften Angewandte Biologie Bioinformatik
- Naturwissenschaften Chemie Physikalische Chemie Quantenchemie, Theoretische Chemie
Weitere Infos & Material
Part I. Phytochemistry and drug discovery.- Chapter 1. Foundation of Phytochemistry and AI-Driven Innovations in Drug Discovery.- Part II. AI Simulation Techniques in phytochemistry.- Chapter 2. AI-Powered Prediction of Molecular Properties of Phytochemicals.- Chapter 3. Simulation of Drug-Phytochemical Interactions Using Artificial Intelligence (AI).- Chapter 4. AI-Driven Optimization of Phytochemical Drug Candidates.- Part III. Pharmacological Applications of AI in phytopharmacology.- Chapter 5. AI Tools for Designing Phytopharmacological Agents.- Chapter 6. Predicting Efficacy And Toxicity Of Phytochemical Drugs With Ai Models.- Chapter 7. Case Studies: AI in preclinical and Clinical phytopharmacology.- Part IV. Integration of AI in phytopharmacological Research.- Chapter 8. AI Techniques in the Discovery of Novel Phytochemical Compounds.- Chapter 9. AI-Assisted Development of Personalized phytopharmacological Therapies.- Chapter 10. Collaborative Strategies For Pharma Companies Using Ai In Phytopharmacology.- Part V. Challenges of artificial intelligence in the phytochemistry and drug discovery.- Chapter 11. Ethical Concerns in Leveraging AI for Phytochemistry.- Chapter 12. Legal and Regulatory Implications of AI Utilization in Drug Development. Chapter 13. Managing Security Risks in AI Deployment.- Chapter 14. Strategic Solutions for Overcoming Challenges in AI Adoption.




