PROJECT SUMMARY Families seeking evaluation for autism spectrum disorder (ASD) often face barriers such as low availability of specialists, lengthy waitlists, and long distances to tertiary care diagnostic centers. This is especially true for children from traditionally underserved groups and communities. Without innovative approaches for enhanced identification of ASD, families and clinicians will continue to struggle with accessing and providing care. Telemedicine offers tremendous potential for addressing this need, but there are few psychometrically sound, validated tools that can be administered remotely, via telehealth platforms, in order to guide service and action. Our team developed and conducted a preliminary evaluation of a novel parent-administered, clinician-guided tele-diagnostic tool, the TAP (TELE-ASD-PEDS), designed specifically for direct-to-home and community clinic use with toddlers. Remote administration of the TAP yielded a very high level of agreement with blinded comprehensive evaluation regarding ASD risk classification. Subsequently, the unanticipated broad dissemination of the TAP during COVID-19 demonstrated its value for traditionally underserved groups, spanning broad geographies. Although promising, this work was limited by its specific focus on toddlers with ASD concerns. A telemedicine tool designed for the unique context and population of preschool-aged children referred for diagnostic assessment could have tremendous value in terms of both accurate identification as well as family engagement with service. In the current work, we propose a computationally informed co-production in which we involve our targeted population as active partners in designing a new telemedicine tool, the TAP– Preschool, for ASD risk assessment in preschoolers. This approach will follow our innovative methodology for fusing advanced computational analyses with stakeholder expertise (1) by mining our large clinical registry to identify key ASD behavior targets and (2) rigorously translating these key behaviors to generate telehealth assessment techniques. With input from our computational experts, clinical scientists, and end-users, we will then evaluate the performance, usability, and utility of the TAP–Preschool. We will gather critical data not only regarding its structure and accuracy, but also its potential deployment across systems responsible for engaging children and families from underserved groups in meaningful service. This work has potential to transform the ASD evaluation process and dramatically improve care access for traditionally underserved groups.