PROJECT SUMMARY Irreproducibility of biomedical and preclinical research is responsible for wasting 50% of the entire research budget and accounts for billions of wasted dollars. Issues with authenticity of key resources, such as cell lines, form a major contributor to this problem. An alarming increase in cell authenticity issues has prompted the NIH and some journals to take action by requiring grant applicants to discuss plans for authentication and requiring manuscript authors to report authentication results. However, the current gold standards for cell authentication are costly and time consuming. They present significant hurdles for researchers, leading to avoidance of testing. Other factors that exacerbate the problem of irreproducibility include a lack of systematic reporting on provenance details regarding passaging, maintenance protocols, chain-of-custody, and relational lineage information. The tools available nowadays are not specifically created for cell culture and lack interoperability. This increases the burden on reporting and reduces transparency. To address these unmet needs, FIND Genomics is developing FIND Cell, a comprehensive cell culture management platform. The primary innovation of this platform is the integration of three key components: 1) a collaborative, multidimensional data organization tool for cell culture work (e.g., graphical user interface designed to facilitate tracking of cell lines across lineages), 2) risk assessment capabilities, and 3) a computational method to assess cell quality (both genetic identity and stability) that provides users with the option of using low-coverage whole-genome sequencing. Use of our tool will save scientists time and costs associated with ensuring cell quality. We have developed a prototype that has been tested and graded as “Excellent” by cell experts. To bring FIND Cell to market, we aim to developing our software as outlined in this Direct-to-Phase II SBIR project proposal: AIM 1. Benchmark our low-cost, high- accuracy cell quality analysis through comparison with gold standards (STR typing and G-band karyotyping); AIM 2. Develop a cell line risk assessment and decision support tool; AIM 3. Refine our management platform’s user interface, and calculate operational savings based on user feedback. Successful completion of this project will result in a market-ready, user-friendly platform with a validated method for cell authentication. Additionally, our platform will include predictive risk analysis that will alert users. The early warning system, combined with cheap and easy authentication, will reduce waste of time, effort and money on experiments with faulty cell lines. The ease of record-keeping and -sharing in a single interface will enable transparency and rigor and improve reproducibility in biomedical/preclinical research.