AI-Driven Pharmaceutical Manufacturing

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. 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.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.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.

• Section 1: Digital and Regulatory Foundations for Pharma Manufacturing1. The Evolution of Industry 4.0 to Industry 5.02. AI/ML Fundamentals and Data Applications in Pharma3. Global Regulatory Expectations and Case InsightsSection 2: Pharmaceutical Manufacturing Practices4. Upstream and Downstream Manufacturing Processes5. Process Validation and Technology Transfer6. Facility Design, GMP, and Environmental Controls7. Automation and MES in Manufacturing ExecutionSection 3: Applications in Drug Development8. AI-Driven Formulation Development9. Human-Robot Collaboration and AI Integration in Drug Manufacturing10. Real-Time Monitoring and Control Systems11. Ethical and Safety Considerations in AI-Driven Drug Manufacturing12. Cost-Benefit and ROI Analysis of AI/ML IntegrationSection 4: Regulatory Compliance and Challenges13. RegTech Case: Using AI for Automated Compliance Reporting14. Addressing Data Integrity and Security Concerns15. Case Studies: Global Implementations of AI/MLSection 5: Future Trends and Innovations16. AI and Industry 5.0 in Western Pharmaceutical Manufacturing and COBOTS17. AI-Driven Supply Chain and Logistics Optimization18. Data Governance and Explainable AI (XAI)19. Cybersecurity in Pharmaceutical Manufacturing — Protecting Industry 5.0 Digital Ecosystems