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Good Simulation Practice (GSP) is a set of “good practices” designed to ensure the quality and reliability of computational modeling and simulation (CM&S) in the assessment of medical products.

This concept draws parallels to established standards in biomedicine such as Good Clinical Practice (GCP) and Good Laboratory Practice (GLP), which are frameworks intended to ensure the safety, efficacy, and quality of medical products and interventions. While GCP and GLP are well-established under the guidance of international bodies like the Organisation for Economic Co-operation and Development (OECD) and the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH), GSP is an emerging standardset of guidelines.

GSP is aimed at leveraging CM&S for regulatory decision-making and supporting the development, optimization, and safety evaluation of medical products. GSP encompasses the use of "In Silico Methodologies", a term used to denote CM&S as tools in regulatory processes, particularly for medical devices and pharmaceuticals.

= History of Good Simulation Practice = Since 2002, CM&S has been increasingly incorporated into premarket approval applications for medical devices, as evidenced by its inclusion in at least 21% of such applications by 2019. (Morrison et al., 2019). This integration signifies a broader acceptance and recognition of the importance of CM&S within the regulatory framework.

The American Society of Mechanical Engineers (ASME) Verification & Validation (V&V)-40 standard, published initially in 2018 and specific to medical devices, marks a significant milestone in formalizing these practices. However, broader regulatory frameworks and guidance documents specific to the use of CM&S across various medical products were still underdeveloped as of the early 2020s.

In November 2022, FDA published a new report titled Successes and Opportunities in Modeling & Simulation for FDA, identifying opportunities to better harness M&S in upcoming years by embracing computational advances and new (and big) data streams to develop improved public health solutions. In this report it was indicated that "Lack of “Good Simulation Practices” guidelines may be one of the limiting factors for broader use and acceptance of M&S. Creating these guidelines is a key opportunity for the Agency to have an important leadership role", and that "(a key) opportunity is to consider the establishment of Good Simulation Practice to foster harmonization across the FDA, and where appropriate, with international regulatory bodies".

The push towards a standardized GSP was catalyzed by the collaborative efforts of communities like the Virtual Physiological Human Institute (VPHi) and the Avicenna Alliance, which represent academic and industrial stakeholders in in silico medicine, respectively. These groups have been instrumental in gathering consensus and fostering discussions around the best practices for CM&S.

The result was a position reported that emerged from the In Silico World project and its associated Community of Practice (ISW_CoP), which comprises over 500 experts. This position report titled Toward Good Simulation Practice: Best Practices For The Use Of Computational Modelling & Simulation In The Regulatory Process Of Biomedical Products proposed a systematic framework for using CM&S throughout the life cycle of medical products, focusing specifically on enhancing safety and efficacy assessments. It laid the groundwork for potential future standards and offered a structured approach to using in silico methodologies as alternatives or complements to traditional experimental methods.

The paper, non-binding yet influential, serves as a foundational text aiming to orient future policies and standardization efforts in this rapidly evolving field.

= Toward Good Simulation Practice overview = The Toward Good Simulation Practice position report contains nine chapters, each of them including essential recommendations:
 * 1) Introduction
 * 2) Theoretical Foundations of Good Simulation Practice
 * 3) Model Development
 * 4) Model Credibility
 * 5) Possible Qualification Pathways for In Silico Methodologies
 * 6) Possible Health Technology Assessment Pathways
 * 7) Ethical Review of In Silico Methodologies
 * 8) The Sponsor
 * 9) The Investigator: Modellers and Analysts