Rationale: The rapidly evolving field of digital health has great potential to enhance biomedical research, education and clinical care. Development in this new space is largely being driven by the tech sector, where projects may lack proper clinical focus or scientific rigor and generally do not include health outcome measures to assess effectiveness or impact.

Rationale.  Problem: because of multiscale complexity, conceptual, mechanism-based, in vitro-to-in vivo mapping models are hard to falsify and can be flawed in ways that may not be obvious until challenged experimentally, which can be costly.  When the results of such experiments are equivocal or not supportive, the information needed to revise mechanistic hypotheses may be lacking.  Translation of in vitro phenomena to in vivo counterparts requires a mapping model.  Currently, mechanism-agnostic correlation models are common

Rationale: Developing efficient and effective methods to recruit and screen participants for clinical research remains a major challenge for clinical discovery.