Chapter 5 Drug manufacturing and quality control with artificial intelligence
-
Rishabha Malviya
Abstract
Artificial intelligence (AI) uses advanced instruments and networks to mimic human intelligence. Artificial intelligence is increasingly used in the pharmaceutical industry to automate and manage large data sets. Quality by design (QbD) and AI can improve product quality, reduce waste, and speed up production in the pharmaceutical industry. The chapter provides information on drug manufacturing and quality control using AI in the pharma industry. The medical research sector must integrate technologies like blockchain and AI into its core competencies to thrive. The objective of the European Union’s AI-based manufacturing compliance regulations is examined, aiming to align technology with the EU’s core values, rights, and principles. The body of research on the Internet of Things privacy and security measures was reviewed, along with the myths surrounding widely used technologies that make extreme security promises. To raise the bar for pharmaceutical handling of data, sharing, processing, assessment, and classification based on outcomes, the chapter discusses cutting-edge blockchain and AI methods.
Abstract
Artificial intelligence (AI) uses advanced instruments and networks to mimic human intelligence. Artificial intelligence is increasingly used in the pharmaceutical industry to automate and manage large data sets. Quality by design (QbD) and AI can improve product quality, reduce waste, and speed up production in the pharmaceutical industry. The chapter provides information on drug manufacturing and quality control using AI in the pharma industry. The medical research sector must integrate technologies like blockchain and AI into its core competencies to thrive. The objective of the European Union’s AI-based manufacturing compliance regulations is examined, aiming to align technology with the EU’s core values, rights, and principles. The body of research on the Internet of Things privacy and security measures was reviewed, along with the myths surrounding widely used technologies that make extreme security promises. To raise the bar for pharmaceutical handling of data, sharing, processing, assessment, and classification based on outcomes, the chapter discusses cutting-edge blockchain and AI methods.
Chapters in this book
- Frontmatter I
- Preface V
- Foreword VII
- Contents IX
- Chapter 1 Introduction to smart pharma: foundation of AI and big data 1
- Chapter 2 Emerging technology in pharma and the role of AI and blockchain 19
- Chapter 3 Partnership and collaboration in the pharmaceutical industry 37
- Chapter 4 Education and training in smart pharma 55
- Chapter 5 Drug manufacturing and quality control with artificial intelligence 77
- Chapter 6 Drug development and clinical trial via artificial intelligence 97
- Chapter 7 AI-driven clinical decision support systems for pharma executives 121
- Chapter 8 AI-based pharmacovigilance and drug safety 143
- Chapter 9 Intellectual property and data privacy in the pharmaceutical sector 163
- Chapter 10 Regulatory affairs and compliance in the pharmaceutical sector 183
- Chapter 11 AI and big data in post-marketing surveillance 201
- Chapter 12 Challenges and ethical considerations 219
- Chapter 13 Future trends and innovations of AI in healthcare 237
- Index 253
Chapters in this book
- Frontmatter I
- Preface V
- Foreword VII
- Contents IX
- Chapter 1 Introduction to smart pharma: foundation of AI and big data 1
- Chapter 2 Emerging technology in pharma and the role of AI and blockchain 19
- Chapter 3 Partnership and collaboration in the pharmaceutical industry 37
- Chapter 4 Education and training in smart pharma 55
- Chapter 5 Drug manufacturing and quality control with artificial intelligence 77
- Chapter 6 Drug development and clinical trial via artificial intelligence 97
- Chapter 7 AI-driven clinical decision support systems for pharma executives 121
- Chapter 8 AI-based pharmacovigilance and drug safety 143
- Chapter 9 Intellectual property and data privacy in the pharmaceutical sector 163
- Chapter 10 Regulatory affairs and compliance in the pharmaceutical sector 183
- Chapter 11 AI and big data in post-marketing surveillance 201
- Chapter 12 Challenges and ethical considerations 219
- Chapter 13 Future trends and innovations of AI in healthcare 237
- Index 253
