FREEMIND: Focused Research Education and Experience using Multimodal and Interdisciplinary NIH Datasets - PROJECT SUMMARY/ABSTRACT The overall objective of the R25 Focused Research Education and Experience using Multimodal and Interdisciplinary NIH Datasets (FREEMIND) Program is to develop a diverse workforce in biomedical research who will also be long-term users of datasets supported by the National Institutes of Health (NIH), including NIH Common Fund datasets. The proposed program is designed to expand and diversify the pipeline of new investigators in biomedical research. The program will include an intensive, two-week, in-person bootcamp course at UC San Diego designed around providing hands-on instructional guidance for using data from two Common Fund Programs, Bridge2AI and SPARC, as well as the NIH All of Us Research Program. Jointly, these datasets provide a multimodal set of data (e.g. electronic health records [EHRs], imaging data, waveform data, omics data) and offer great potential to train participants of the program in analyzing large complex datasets across multiple disciplines (diabetes research, neuromodulation, biology, etc.). This program will be led by an interdisciplinary team with a wide range of research expertise and a strong track record of training, education, and mentorship. Participants will be graduate students, medical students, postdoctoral fellows, and early career faculty (early stage investigators). They will engage in virtual didactic instruction both before and after the bootcamp. The program includes a strong mentoring component, with faculty mentors providing input on designing and executing projects using the NIH-supported datasets. During the bootcamp, participants will complete projects in small groups and deliver oral presentations to discuss their results. The educational program will include instruction on accessing and analyzing these datasets as well as in rigor and reproducibility, responsible conduct of research, team science principles, and the practical aspects of conducting large-scale, multi-disciplinary scientific collaborations. Innovations in this program include leveraging real-life datasets, emphasizing multimodal analyses, and providing intensive guidance in a focused format accessible to a broad array of participants, including clinician-scientists. The program will support participants as they pursue publication and presentation opportunities to advance their careers. Broad outreach will be conducted to enable diverse recruitment, and intensive program evaluation will be conducted to facilitate iterative improvements to the syllabus and program administration. Program faculty include leaders of the NIH-supported datasets being taught. By completing these aims, we will promote the broad and rigorous use of Common Fund and other NIH-supported data among diverse participants in the formative stages of their careers and help facilitate their advancement toward independent research careers and to becoming long-term users of NIH datasets.
