The integration of experimental data into multiscale mathematical models can shed light on the mechanisms underlying infectious and immune-mediated diseases. The 2023 Society for Mathematical Biology (SMB) Annual Meeting provided an opportunity to convene leaders in multiscale mathematical modeling and quantitatively experimental biology, including both Ph.D. researchers and M.D. clinicians, to share their perspectives on opportunities and challenges for multiscale modeling for infectious, allergic, and immune-mediated diseases. During a five-hour event, presenters and participants sought to (1) highlight gaps, challenges, and opportunities around multiscale infectious disease (ID) models; (2) foster collaboration between mathematical modelers/statisticians and ID researchers/clinicians; (3) define what is required to incorporate multiscale models in biomedical ID applications; and (4) identify best practices and data capture conducive for multiscale modeling (booklet provided as Supplemental Information). Each of the six expert speakers were invited to share their clinical and biological outlooks on the most pressing challenges and opportunities for models to inform underlying mechanisms of and/or treatments for infectious diseases. Three sessions each featured two speakers focused on immunological, virological, and prokaryotic and eukaryotic data. The presenters defined ideal data types to answer key clinical questions and provided use-cases on ways to bring models from white-board to computer to biomedical application. After the presentations, a panel discussion featuring all speakers explored ways to initiate and achieve successful computational and biomedical collaborations.