Artificial Intelligence in the Production of Biotherapeutics

Principles, Practices and Standards
1. Auflage 2025
ISBN: 978-1-041-03635-7
Verlag: Taylor & Francis Ltd

Buch, Englisch, 304 Seiten, Format (B × H): 156 mm x 234 mm, Gewicht: 453 g

The transformative role of artificial intelligence (AI) in modern biomanufacturing, focusing on key areas such as Process Analytical Technology (PAT), Good Manufacturing Practice (GMP) compliance, predictive analytics, and AI-driven quality systems. It bridges cutting-edge AI applications with the complexities of biotherapeutic production, offering insights into automation, real-time monitoring, and process optimization.

Delving into the core of biomanufacturing, the book provides a structured journey through its critical phases. It begins with an introduction to modern biomanufacturing principles, quality-by-design approaches, and the integration of AI. Subsequent chapters examine raw material management, lean manufacturing practices, and the application of predictive analytics to optimize supply chains. Readers will explore advanced tools such as AI-enhanced data acquisition in PAT, automated standard operating procedures (SOPs), and AI-driven process controls for fermenters and chromatography systems. The text also addresses GMP essentials, including personnel management, hygienic facility design, and pharmaceutical water systems. Key chapters highlight AI's role in validation processes, sterile packaging, and regulatory compliance, referencing global guidelines from organizations such as the WHO, FDA, and ICH. Real-world case studies featuring therapeutic proteins, monoclonal antibodies, and vaccines underscore the practical applications of AI in scaling and maintaining biotherapeutic production.

This book equips readers with a comprehensive understanding of AI's potential to enhance efficiency, accuracy, and compliance in biomanufacturing. Whether you are a professional, researcher, or student, this guide offers actionable insights into leveraging AI to revolutionize biotherapeutic production while adhering to the highest industry standards.

What You Will Learn

· Understand how AI enhances every phase of biotherapeutic production, from raw material management to regulatory compliance, optimizing efficiency, accuracy, and quality.

· Explore the role of AI in advanced data acquisition, process control, and continuous improvement, including applications in fermenters, flow filtration, and chromatography systems.

· Gain insights into leveraging AI for automating standard operating procedures (SOPs), predictive maintenance, quality assurance, and adhering to global GMP standards like WHO and FDA guidelines.

· Learn how AI transforms upstream and downstream processes, ensures sterility in packaging, and supports case studies on therapeutic proteins, monoclonal antibodies, and human vaccines.

· Discover the potential of AI in shaping the future of biomanufacturing, including challenges, data security, and the ethical implications of AI-driven automation.

Zielgruppe

Academic, Postgraduate, Professional Practice & Development, and Professional Reference

Autoren/Hrsg.

Srivastav, Alok Kumar

Das, Priyanka

Fachgebiete

• Technische Wissenschaften Verfahrenstechnik | Chemieingenieurwesen | Biotechnologie Biotechnologie Medizinische Biotechnologie
• Naturwissenschaften Chemie Chemie Allgemein Chemometrik, Chemoinformatik
• Medizin | Veterinärmedizin Medizin | Public Health | Pharmazie | Zahnmedizin Medizinische Fachgebiete Pharmakologie, Toxikologie

Inhaltsverzeichnis

CHAPTER 1: INTRODUCTION TO BIOMANUFACTURING

1.1 Overview of Modern Biomanufacturing Principles

1.2 Overview of Biomanufacturing

1.3 The Quality by Design Approach

1.4 Technical Considerations in Biomanufacturing

1.5 Phases and Scale-Up in Biomanufacturing

1.6 Lifecycle of Manufacturing

1.7 Integration of Artificial Intelligence in Biomanufacturing

CHAPTER 2: RAW MATERIAL AND COMPLIANCE IN BIOMANUFACTURING

2.1 Raw Material Considerations in Biomanufacturing

2.2 Compliance and Quality in Biomanufacturing

2.3 Lean Biomanufacturing

2.4 Artificial Intelligence in Raw Material Management

2.5 Predictive Analytics for Raw Material Quality and Supply Chain Optimization

2.6 Advanced Technologies and Future Directions in Biomanufacturing

CHAPTER 3: PROCESS ANALYTICAL TECHNOLOGY (PAT)

3.1 Background and Need for PAT

3.2 Tools for Data Acquisitions

3.3 Software in Fermenters, Flow Filtrations, Chromatography

3.4 Analysis and Design Process Analyzers

3.5 Process Control Tools

3.6 Continuous Improvement and Knowledge Management

3.7 Artificial Intelligence in Process Analytical Technology

3.8 Enhancing data acquisition and process control through machine learning algorithms

CHAPTER 4: STANDARD OPERATING PROCEDURES IN BIOTECHNOLOGY

4.1 Upstream Processing of Proteins

4.2 Downstream Processing of Proteins

4.3 Quality Control of Protein Production

4.4 Final Fill and Finish of Product

4.5 Case Studies: Therapeutic Proteins, Monoclonal Antibodies, Human Vaccines

4.6 Artificial Intelligence for Standard Operating Procedures Optimization

4.7 Automating and optimizing SOPs using AI technologies

CHAPTER 5: INTRODUCTION TO QUALITY SYSTEMS

5.1 Main Elements of a Quality System

5.2 Essentials of a Quality System

5.3 Practical Implementation of a Quality System

5.4 Structure of a Quality Manual

5.5 Correlation between GMP Requirements (WHO) and ISO 9001:2000

5.6 Artificial Intelligence in Quality Systems

5.7 Leveraging AI to ensure continuous compliance and improvement in quality systems

CHAPTER 6: PRINCIPLES AND PRACTICE OF GMP: PERSONNEL AND PREMISES

6.1 Principles of Human Resource Management

6.2 Duties of Senior Management

6.3 Organizational Structures

6.4 Qualification and Profiles Requirement

6.5 Workplace and Job Descriptions

6.6 Health Monitoring and Occupational Health Safety

6.7 Training and Functions Owners Subject to Public Law

6.8 Official Requirements for Premises

6.9 Material & Personnel Flow and Layout

6.10 Air Cleanliness Classes and Grades

6.11 Construction Elements and Barrier Systems

6.12 Artificial Intelligence in Personnel Management and Premises

6.13 AI applications in optimizing HR functions and premises management

CHAPTER 7: FACILITIES, EQUIPMENT, AND PHARMACEUTICAL WATER

7.1 Facility Planning and Materials

7.2 Hygienic Design in Solids Handling

7.3 System Controllers and Process Control Systems

7.4 Technical Documentation, Calibration, and Maintenance

7.5 Cleaning of Facilities and Containment in Solids Handling

7.6 Pharmaceutical Water: Qualities, Generation, Distribution, and Storage

7.7 Qualification and Operation of Water Supplies

7.8 Pure Steam Systems

7.9 Artificial Intelligence in Facility Management

7.10 Using AI for predictive maintenance and efficient facility operations

CHAPTER 8: QUALIFICATION AND PROCESS VALIDATION

8.1 Official Requirements for Qualification

8.2 Preparation and Documentation of Qualification

8.3 Design Qualification (DQ), Installation Qualification (IQ), Operational Qualification (OQ), Performance Qualification (PQ)

8.4 Special Cases of Qualification

8.5 Official Requirements for Validation

8.6 Validation Planning and Procedure

8.7 Process Validation and Product Lifecycle

8.8 Cleaning Validation: Master Plan, Scope, Acceptance Criteria, Sampling, Analytical Procedures, Documentation

8.9 Artificial Intelligence in Validation Processes

8.10 Automating qualification and validation processes with AI tools

CHAPTER 9: PRODUCTION, SANITATION, AND STERILE PACKAGING

9.1 Sanitation and Personnel Hygiene

9.2 Production Hygiene and Environmental Monitoring

9.3 GMP in the Production Process

9.4 Weigh-In, Identification, and In-Process Control

9.5 Prevention of Cross-Contamination, Reworking, Warehouse, and Logistics

9.6 Sterile Production: Air Lock Concepts, Manufacture of Terminally Sterilized Products, Sterilization Processes

9.7 Aseptic Processing and Freeze-Drying

9.8 Testing for Sterility, Endotoxins, Leakage, and Particles

9.9 Microbiological Monitoring

9.10 Packaging Materials and Processes

9.11 Qualification of a Servo-Controlled Blister Packaging Line

9.12 Blow-Fill-Seal (BFS) Technology

9.13 Artificial Intelligence in Production and Packaging: AI for real-time monitoring and control in production and packaging environments

CHAPTER 10: GMP IN REGULATION

10.1 Information on National Bodies and Pharmaceutical Associations

10.2 Overview of Pharmacopeia

10.3 EU Directives and Guidelines

10.4 USA: CFR and FDA Guidelines

10.5 ICH-Guidelines

10.6 PIC/S Guidelines

10.7 GMP of Other Regions

10.8 WHO Guidelines

10.9 Artificial Intelligence in Regulatory Compliance: AI tools for ensuring adherence to regulatory guidelines and proactive compliance

.

Über Autor(innen)

Dr. Alok Kumar Srivastav is an accomplished Assistant Professor in the Department of Health Science at the University of the People, Pasadena, California, USA. His academic background includes a Ph.D., M.Tech, and M.Sc. in Bio-Technology, a Post-Doctoral Fellowship (Research) in Bio-Technology from Lincoln University College, Malaysia, and an MBA in Human Resource Management. He is a distinguished figure in Academia and Research, honored with the “International Pride of Educationist Award” at AIT, Thailand, in 2022 for pioneering contributions to advancing education in the digital era, and recipient of a prestigious “Innovative Academic Researcher Award” at HULT, France, UK, in 2024 for his exceptional creativity, innovation, and impact in academic research.

Dr. Priyanka Das serves as an Assistant Professor in the Department of Health Science at the University of the People in Pasadena, California, USA. She holds a Ph.D., M.Tech, and M.Sc. in Biotechnology along with an MBA in Human Resource Management. Prior to her current position, she was a Post-Doctoral Fellowship (Research) in Biotechnology at Lincoln University College, Malaysia. Dr. Priyanka Das is a dedicated scholar, contributing significantly to the field of Biotechnology.