📘 Monte Carlo Methods for GMP & Pharma Operations

Statistical Simulation Tools for Pharmaceutical Quality and GMP Decision-Making

📖 Introduction

This project is a practical, industry-focused eBook introducing Monte Carlo methods for professionals working in pharmaceutical manufacturing, quality control, and GMP operations.

It is not a purely theoretical treatise — the emphasis is on real-world applications where Monte Carlo simulation can support decision-making, process understanding, and risk assessment.

A distinctive feature of this eBook is the inclusion of real-world case studies (e.g., assay, dissolution, process validation, CPV).
These case studies are progressively expanded, illustrating how Monte Carlo and related methods can be applied to typical GMP scenarios.

The book also provides historical and regulatory context (e.g., ICH Q9(R1), USP <1210>, FDA/EMA guidance),
ensuring that statistical methods are presented in a way that is both scientifically rigorous and inspection-ready.

The goal is to provide practical statistical tools that can be applied immediately in GMP decision-making contexts.

Chapters

1. Chapter 1 – Introduction

2. Chapter 2 – Random Numbers vs. Random Variates

3. Chapter 3 – Simple Distributions

4. Chapter 4 – The Transfer Equation

5. Chapter 5 – A Complete Simulation in R

6. Chapter 6 – Analysis of Results

7. Chapter 7 – Case Study 1: API Assay in Tablets

8. Chapter 8 – Case Study 2: Dissolution with Noyes-Whitney Law

9. Chapter 9 – Case Study 3: From 3 Batches to Continuous Confidence

10. Chapter 10 – Case Study 4: Capability Indices in Pharma

11. Chapter 11 – Case Study 5: Predictive Stability with Monte Carlo

12. Chapter 12 – Case Study 6: Monte Carlo Sampling Plans and Empirical OC Curves

13. Chapter 13 – Case Study 7: Microbiological Counts – Quantifying Overdispersion via Monte Carlo Simulation

14. Chapter 14 – Case Study 8: Percentile-Based Capability Indices for Non-Normal Data

15. Chapter 15 — Case Study 9: Monte Carlo Measurement Uncertainty & Risk of Non-Compliance

16. Chapter 16 – Decision and Risk

17. Chapter 17 – Conclusions and Next Steps

18. Chapter 18 – References

19. Chapter 19 – Glossary

🚀 Next Steps

This eBook is a living project and will continue to evolve over time. Future improvements may include:

• Refine and expand chapters with clearer explanations, figures, and diagrams
• Add new pharmaceutical case studies to illustrate practical applications
• Introducing advanced statistical tools (e.g., Resampling, Bootstrap, Bayesian methods)
• Exploring integration with quality standards (ICH Q2(R2), USP <1210>, ISO 3951-1, etc.)
• Translating into additional languages for wider accessibility
• Providing ready-to-use R scripts and templates for QA/QC teams
• Collecting feedback from readers to guide future improvements

💡 How to Use This eBook

• Start with the Introduction for context.
• Navigate through chapters progressively.
• Run the included R scripts locally to replicate results, and adapt them to your own datasets.
• Apply the methodology to your own GMP-related problems.

👤 Author

Riccardo Bonfichi
Statistical Consultant for Pharma Operations
Specializing in Quality Control, Quality Assurance, and Statistical Methods applied to GMP manufacturing and laboratory processes.

📖 How to Cite

If you use or reference this work, please cite it as follows:

APA 7th:
Bonfichi, R. (2025). Monte Carlo Methods for GMP & Pharma Operations (eBook).
Zenodo. https://doi.org/10.5281/zenodo.17265550

Vancouver:
Bonfichi R. Monte Carlo Methods for GMP & Pharma Operations (eBook) [Internet]. 2025.
Zenodo. Available from: https://doi.org/10.5281/zenodo.17265550

⚖️ License

© 2025 Riccardo Bonfichi.

This work is licensed under CC BY-NC-ND 4.0.