The purpose of in-silico models in the industry is unclear. Are they for research, aiding clinicians, regulatory compliance, marketing, or speeding up new device market entry? This raises questions about who benefits from these models: the broader industry or specific small and medium enterprises bridging academia and industry? Additionally, determining a realistic complexity level for these models is crucial to balance practical applicability and scientific rigor.

Computational models (CM) are key in predicting physical properties and medical device performance. The aim is to use CM in in-silico trials (ISCT) to foresee safety and performance before clinical trials, like predicting thrombosis from flow markers. However, linking clinical outcomes to engineering metrics remains challenging. Our framework will address this, discussing its limitations and potential solutions.

The potential of in-silico technologies in bolstering the development and evaluation of medical devices is widely acknowledged. Yet, there exists a gap in accurately quantifying the socioeconomic impacts these technologies pose on various stakeholders and society at large. This session will explore both the open challenges and the potential impacts of in-silico technologies. It will culminate in an interactive discussion, where we will introduce a comprehensive framework designed to facilitate the effective quantification of their impact, encouraging collaborative insights and shared expertise.