Adapting modeling and simulation credibility standards to computational systems biology.

Area of Science:

• Computational modeling and simulation across science, engineering, and medicine.
• Application of computational models in high-stakes decision-making processes.
• Development of credibility standards for scientific models.

Background:

• Computational models are increasingly utilized by organizations like NASA, FDA, and EMA for complex experiments and regulatory approvals.
• Existing credibility standards for computational models are often qualitative due to the broad scope of assessment.
• Systems biology modeling is a specialized domain with existing standards, facing growing complexity and influence.

Purpose of the Study:

• To review existing credibility standards within systems biology.
• To examine credibility standards employed in other scientific, engineering, and medical fields.
• To propose the development of a specific credibility assessment system for systems biology models.

Main Methods:

• Literature review of current systems biology modeling standards.
• Analysis of credibility assessment frameworks used by NASA, FDA, and EMA.
• Comparative study of qualitative and quantitative approaches to model credibility.

Main Results:

• Identification of existing, albeit qualitative, credibility standards in systems biology.
• Recognition of diverse, often qualitative, credibility standards in broader scientific and regulatory fields.
• Highlighting the need for a more defined credibility assessment system tailored to systems biology.

Conclusions:

• Credibility assessment is crucial for the reliable use of computational models in high-stakes decision-making.
• Existing qualitative standards necessitate the development of a more specific and robust system for systems biology.
• A dedicated credibility standard for systems biology models is proposed to enhance their trustworthiness and impact.