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Practical Monte Carlo Simulation in GMP Manufacturing and Control

Quantitative Tools for Understanding Variability, Uncertainty, and Risk in Pharmaceutical Production and Testing
Artikelnummer: 978-1-041-36260-9
Einband: Kartonierter Einband (Kt)
Verfügbarkeit: Noch nicht erschienen, Dezember 2026
CHF 101.00
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Preface 1 Introduction to Monte Carlo in Pharma 2 Random Numbers vs. Random Variates 3 Simple Distributions 4 The Transfer Equation 5 A Complete Monte Carlo Simulation in R 6 Analysis of Simulation Results 7 Case Study 1 - API Assay in Tablets 8 Case Study 2 - Dissolution with Noyes - Whitney Law 9 Case Study 3 - From 3 Batches to Continuous Confidence (Monte Carlo & Bootstrap) 10 Case Study 4 - Capability Indices in Pharma: When Few, Skewed Data Challenge Model Distributions 11 Case Study 5 - Predictive Stability Control with Monte Carlo 12 Case Study 6 - Monte Carlo Sampling Plans and Empirical OC Curves 13 Case Study 7 - Microbiological Counts: Overdispersion via Monte Carlo Simulation 14 Case Study 8 - Monte Carlo Percentile-Based Capability for Non-Normal Data 15 Case Study 9 - Monte Carlo Measurement Uncertainty & Risk of Non-Compliance 16 Understanding Uncertainty Analysis in GMP Models 17 Case Study 10 - Decision Under Uncertainty: Expected Loss and Regulatory Trade-offs via Monte Carlo Simulation 18 Case Study 11 - From CPV Data to Predictive Control 19 Decision and Risk 20 Toward Probabilistic GMP Systems 21 Conclusions References

Preface 1 Introduction to Monte Carlo in Pharma 2 Random Numbers vs. Random Variates 3 Simple Distributions 4 The Transfer Equation 5 A Complete Monte Carlo Simulation in R 6 Analysis of Simulation Results 7 Case Study 1 - API Assay in Tablets 8 Case Study 2 - Dissolution with Noyes - Whitney Law 9 Case Study 3 - From 3 Batches to Continuous Confidence (Monte Carlo & Bootstrap) 10 Case Study 4 - Capability Indices in Pharma: When Few, Skewed Data Challenge Model Distributions 11 Case Study 5 - Predictive Stability Control with Monte Carlo 12 Case Study 6 - Monte Carlo Sampling Plans and Empirical OC Curves 13 Case Study 7 - Microbiological Counts: Overdispersion via Monte Carlo Simulation 14 Case Study 8 - Monte Carlo Percentile-Based Capability for Non-Normal Data 15 Case Study 9 - Monte Carlo Measurement Uncertainty & Risk of Non-Compliance 16 Understanding Uncertainty Analysis in GMP Models 17 Case Study 10 - Decision Under Uncertainty: Expected Loss and Regulatory Trade-offs via Monte Carlo Simulation 18 Case Study 11 - From CPV Data to Predictive Control 19 Decision and Risk 20 Toward Probabilistic GMP Systems 21 Conclusions References

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VerlagTaylor & Francis Ltd
EinbandKartonierter Einband (Kt)
Erscheinungsjahr2026
Seitenangabe280 S.
AusgabekennzeichenEnglisch
MasseH23.4 cm x B15.6 cm
AutorBonfichi, Riccardo

Über den Autor Riccardo Bonfichi

Riccardo Bonfichi is an independent consultant specializing in the application of statistical methods to pharmaceutical manufacturing and control, with over 35 years of experience in GMP-regulated environments across Italy and abroad, including roles at Sandoz Pharma AG in Basel. Over his career he progressed from analytical scientist to senior quality roles - Head of Quality Control, Head of Quality Assurance, and Qualified Person - responsible for the batch release of sterile active ingredients and medicinal products. He now supports pharmaceutical companies in Italy and internationally as a freelance consultant and trainer, focusing on Monte Carlo simulation, resampling methods, and statistical decision-making in QA/QC, and he regularly delivers webinars and courses on these topics for industry associations and regulatory bodies.

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