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Chapter 5 Drug manufacturing and quality control with artificial intelligence

  • Rishabha Malviya , Shristy Verma , Sonali Sundram und Harshil Shah
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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.

Kapitel in diesem Buch

  1. Frontmatter I
  2. Preface V
  3. Foreword VII
  4. Contents IX
  5. Chapter 1 Introduction to smart pharma: foundation of AI and big data 1
  6. Chapter 2 Emerging technology in pharma and the role of AI and blockchain 19
  7. Chapter 3 Partnership and collaboration in the pharmaceutical industry 37
  8. Chapter 4 Education and training in smart pharma 55
  9. Chapter 5 Drug manufacturing and quality control with artificial intelligence 77
  10. Chapter 6 Drug development and clinical trial via artificial intelligence 97
  11. Chapter 7 AI-driven clinical decision support systems for pharma executives 121
  12. Chapter 8 AI-based pharmacovigilance and drug safety 143
  13. Chapter 9 Intellectual property and data privacy in the pharmaceutical sector 163
  14. Chapter 10 Regulatory affairs and compliance in the pharmaceutical sector 183
  15. Chapter 11 AI and big data in post-marketing surveillance 201
  16. Chapter 12 Challenges and ethical considerations 219
  17. Chapter 13 Future trends and innovations of AI in healthcare 237
  18. Index 253
https://doi.org/10.1515/9783111574288-005

Kapitel in diesem Buch

  1. Frontmatter I
  2. Preface V
  3. Foreword VII
  4. Contents IX
  5. Chapter 1 Introduction to smart pharma: foundation of AI and big data 1
  6. Chapter 2 Emerging technology in pharma and the role of AI and blockchain 19
  7. Chapter 3 Partnership and collaboration in the pharmaceutical industry 37
  8. Chapter 4 Education and training in smart pharma 55
  9. Chapter 5 Drug manufacturing and quality control with artificial intelligence 77
  10. Chapter 6 Drug development and clinical trial via artificial intelligence 97
  11. Chapter 7 AI-driven clinical decision support systems for pharma executives 121
  12. Chapter 8 AI-based pharmacovigilance and drug safety 143
  13. Chapter 9 Intellectual property and data privacy in the pharmaceutical sector 163
  14. Chapter 10 Regulatory affairs and compliance in the pharmaceutical sector 183
  15. Chapter 11 AI and big data in post-marketing surveillance 201
  16. Chapter 12 Challenges and ethical considerations 219
  17. Chapter 13 Future trends and innovations of AI in healthcare 237
  18. Index 253
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Heruntergeladen am 23.12.2025 von https://www.degruyterbrill.com/document/doi/10.1515/9783111574288-005/html
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