Proposed best practice for projects that involve modelling and simulation.

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.