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A Modeling and Simulation Method for Preliminary Design of an Electro-Variable Displacement Pump
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Proposed best practice for projects that involve modelling and simulation.

Michael O'Kelly1, Vladimir Anisimov2, Chris Campbell3

  • 1Quintiles, Dublin, Ireland.

Pharmaceutical Statistics
|November 4, 2016
PubMed
Summary

This document outlines best practices for statistical modelling and simulation in drug development. It emphasizes justifying the level of detail in project specifications based on complexity and importance.

Keywords:
Monte Carlo techniquebest practicemodelling and simulationpre-specificationquality control

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Area of Science:

  • Pharmaceutical Statistics
  • Computational Science

Background:

  • Modelling and simulation are integral to developing new pharmaceutical treatments.
  • Ensuring the credibility of these methods requires adherence to best practices.
  • Previous suggestions for best practice include pre-specifying goals, assumptions, methods, and outputs.

Purpose of the Study:

  • To describe the essential elements for specifying a modelling and simulation project.
  • To advocate for a flexible approach to pre-specification based on project complexity and importance.
  • To provide guidance on justifying the omission or level of detail for specified elements.

Main Methods:

  • This document outlines a framework for project specification, not a guide to statistical model development.
  • It requires practitioners to justify any omitted elements and the level of detail for included elements.
  • Appendices provide examples of both detailed and less detailed specifications.

Main Results:

  • The core recommendation is to tailor the rigor of pre-specification to the project's complexity and significance.
  • Practitioners must document and justify their specification choices.
  • The document serves as a best practice guide developed by a Special Interest Group.

Conclusions:

  • A flexible, justified approach to pre-specification enhances the utility and credibility of modelling and simulation in pharmaceutical research.
  • This framework promotes transparency and rigor in statistical project planning.
  • The initiative is supported by the Special Interest Group for modelling and simulation.