Ai-Driven Pharmaceutical Manufacturing

Regulatory Innovation for Industry 5.0
Erscheinungsjahr 2027
ISBN: 978-0-443-44954-3
Verlag: Elsevier Science

Buch, Englisch, 400 Seiten, Format (B × H): 191 mm x 235 mm, Gewicht: 449 g

AI-Driven Pharmaceutical Manufacturing: Regulatory Innovation for Industry 5.0 addresses the critical intersection of artificial intelligence, regulatory compliance, and human-centric innovation in drug product manufacturing. This reference responds to the growing need for advanced technological integration in pharmaceutical production, focusing on how AI and machine learning can optimize manufacturing processes while meeting stringent regulatory demands globally. It fills the knowledge gap for professionals navigating the complex landscape of Industry 5.0 in pharma. The book is structured into five key sections covering digital and regulatory foundations, pharmaceutical manufacturing practices, AI applications in drug development, regulatory compliance challenges, and future trends including cybersecurity and supply chain optimization. Each chapter provides foundational concepts, detailed methodologies, case studies, and practical implementation strategies, ensuring readers gain a thorough understanding of AI's role in pharmaceutical manufacturing. "AI-Driven Pharmaceutical Manufacturing" benefits professionals in manufacturing, regulatory affairs, quality assurance, and technology leadership by delivering actionable knowledge to implement AI/ML responsibly. It equips readers to overcome regulatory challenges, optimize production workflows, and foster sustainable human-machine collaboration, making it an indispensable resource for advancing pharmaceutical manufacturing into the Industry 5.0 era.

Autoren/Hrsg.

Chavda, Vivek P.

T, Muthu Kumar

Ashoka, Hadagali

Desai, Usha

Fachgebiete

• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Pharmakologie, Toxikologie
• Wirtschaftswissenschaften Wirtschaftssektoren & Branchen Fertigungsindustrie

Inhaltsverzeichnis

Section 1: Digital and Regulatory Foundations for Pharma Manufacturing
1. The Evolution of Industry 4.0 to Industry 5.0
2. AI/ML Fundamentals and Data Applications in Pharma
3. Global Regulatory Expectations and Case Insights

Section 2: Pharmaceutical Manufacturing Practices
4. Upstream and Downstream Manufacturing Processes
5. Process Validation and Technology Transfer
6. Facility Design, GMP, and Environmental Controls
7. Automation and MES in Manufacturing Execution

Section 3: Applications in Drug Development
8. AI-Driven Formulation Development
9. Human-Robot Collaboration and AI Integration in Drug Manufacturing
10. Real-Time Monitoring and Control Systems
11. Ethical and Safety Considerations in AI-Driven Drug Manufacturing
12. Cost-Benefit and ROI Analysis of AI/ML Integration

Section 4: Regulatory Compliance and Challenges
13. RegTech Case: Using AI for Automated Compliance Reporting
14. Addressing Data Integrity and Security Concerns
15. Case Studies: Global Implementations of AI/ML

Section 5: Future Trends and Innovations
16. AI and Industry 5.0 in Western Pharmaceutical Manufacturing and COBOTS
17. AI-Driven Supply Chain and Logistics Optimization
18. Data Governance and Explainable AI (XAI)
19. Cybersecurity in Pharmaceutical Manufacturing — Protecting Industry 5.0 Digital Ecosystems

Über Autor(innen)

Chavda, Vivek P.
Vivek P. Chavda is an Assistant Professor (Selection Grade) in the Department of Pharmaceutics and Pharmaceutical Technology at L. M. College of Pharmacy, Ahmedabad, Gujarat, India. He earned Bachelor and Master of Pharmacy degrees and was a Gold Medallist at Gujarat Technological University. Before entering academia, he spent several years in the Biologics industry, contributing to R&D and regulatory filings for biologics. His scholarly output includes numerous peer-reviewed articles, several books and book chapters, and ongoing writings in newsletters. His research spans the development of biologics processes and formulations, medical device development, nano diagnostics and noncarrier formulations, long-acting parenteral formulations, and nano vaccines. He also has patent assets in development and a record of industry-focused publications.

Ashoka, Hadagali
Hadagali Ashoka is an accomplished academic, researcher, and author with over 17 years of expertise in biotechnology, metabolic engineering, and systems biology. Currently an Assistant Professor at BMS College of Engineering in Bengaluru, India, Dr. Ashoka has made significant contributions to green chemistry and sustainable nanotechnology through his interdisciplinary research. His work bridges the gap between environmental sustainability and advanced material science, making him a sought-after voice in the field. Dr. Ashoka earned his Ph.D. in Chemical Engineering from the prestigious Indian Institute of Technology Bombay, where his research focused on modelling glucose-insulin dynamics and developing innovative therapeutic solutions for diabetes. His work has been published in high-impact journals and recognized for its innovative approach to complex biological and chemical systems.

Desai, Usha
Usha Desai is presently working as a Professor in Computer Science & Engineering (IoT & Cybersecurity including Blockchain Technology) and Dean (Research & Development) for S.E.A. College of Engineering & Technology, Bengaluru. She received her PhD in Biomedical Signal Processing from REVA University, Bengaluru, and M. Tech and BE from Visvesvaraya Technological University, Belagavi, Karnataka. She received the DST International Travel Grant to present her research paper at 39th IEEE EMBS International Annual Conference held at South Korea. She served as Session Chair at the reputed IEEE International Conferences. Also, she has presented papers in many reputed conferences and authored more than 40 research publications. She has authored five books on biomedical healthcare. She has six patents. She is presently a Senior Member of IEEE and Life Member of ISTE.

Dr. Desai integrates digital technologies into pharmaceutical manufacturing, focusing on applications of IoT, cybersecurity, and blockchain to enhance process integrity, traceability, and data security. Her work supports smart pharmaceutical systems and Industry 4.0 transitions within regulated manufacturing environments.

T, Muthu Kumar
Muthu Kumar T is an Assistant Professor at School of Sciences and Humanities, SR University, Warangal. He has experience in computational drug discovery using advanced learning models. He recently developed model for biological activity prediction.

Dr. Muthu Kumar contributes to pharmaceutical manufacturing through his computational expertise in drug development pipelines. His predictive models for bioactivity and pharmacological profiling streamline early-phase formulation design, ultimately enhancing the efficiency of preclinical pharmaceutical research.