PMDedu: Assessing the educational needs of startups and academic investigators focused on pediatric medical device development.

Background: The pediatric medical device development (PMDD) process is highly complex, beset by a variety of financial, technical, medical, and regulatory barriers. Startup company innovators and academic investigators often struggle with accessing specialized knowledge relating to regulatory requirements, product development, research, and marketing strategies. Objectives: The West Coast Consortium for Technology & Innovation in Pediatrics (CTIP) conducted an educational needs assessment to understand knowledge gaps and inform our educational strategy. Methods: We surveyed a total of 49 medical device startups and 52 academic investigators. Electronic surveys were developed for each group on Qualtrics and focused on manufacturing, regulatory, research, commercialization, and funding. Descriptive statistics were used. Results: A larger proportion of academic investigator respondents had a clinical background compared to the startup respondents (45% vs. 22%). The biggest barriers for academic investigators were understanding regulatory and safety requirements testing (52%) and finding and obtaining non-dilutive funding was the most difficult (54%). Among startups, understanding clinical research methods and requirements was the biggest barrier (79%). Conclusion: Startup companies and academic investigators have similar, but not identical, educational needs to better understand the PMD development process. Investigators need more support in identifying funding sources, while startup companies identified an increased need for education on research regulatory topics. These findings can help guide curriculum development as well as opportunities for partnerships between academia and startups.

Bringing FAIRness to FDA data through visualization.

Improving representation and inclusion in clinical trials for new medicinal products has been a high priority for federal agencies for over 2 decades, but data to evaluate progress have been difficult to access. In this issue of Patterns, Carmeli et al. provide a novel approach to aggregating and visualizing existing data to improve transparency and research.