Validating Automated Photoreceptor Analytics Software For Degenerative Eye Disease Research and Biopharma Clinical Trials.

ABSTRACT Neurodegeneration is implicated in almost all major causes of retinal vision loss and specifically in inherited degenerative eye disease. While visual function tests and major imaging modalities, such optical coherence tomography, are favored diagnostic and treatment management tools for symptomatic patients, these clinical tools are unsatisfactory as prognostic indicators or as endpoints for judging clinical efficacy of new preventative and restorative therapies (e.g., neuro-protectives, gene therapies, or stem cell therapies) that operate at the cellular level in the retina. Adaptive optics (AO) ophthalmoscopy has emerged as a sensitive marker of the presence and viability of photoreceptors; however, there are no validated algorithms or objective quantitative measures based on AO fundus images and there are no representative image databases upon which to base screening judgements. In this Direct-to-Phase II SBIR, Translational Imaging Innovations (TII) and Prof. Joseph Carroll, Director of the Advanced Ocular Imaging Program (AOIP), Medical College of Wisconsin (MCW), will validate and commercialize an Automated Photoreceptor Analytics Software for Degenerative Eye Disease. This platform will leverage Mosaic Analytics (MOSAIC), an automated photoreceptor analysis package developed at MCW, and the AOIP Image Bank, which houses images and data on 1578 subjects - 336 normals and the remainder afflicted with one or more of 100 retinal diseases. MOSAIC will unlock the latent value of AO-enhanced ophthalmoscopy to provide a reliable, objective, direct measure of photoreceptor health, and provide quantitative endpoints for assessing the clinical efficacy of cellular therapies. To achieve this goal, we will propose four aims: (a) Strengthen the Photoreceptor Processing Algorithm(s) through a priori image Quality Metrics and a posteriori Confidence Metrics, adoption of Subtractive Regions of Interest, and algorithm tuning to retinal Domains of Interest; (b) Validate the Algorithm(s) for Computing an array of Objective Quantitative Biomarkers; (c) Establish a Proper Context of Use for Qualifying an Objective Clinical Trial Endpoint within the FDA MDDT program; and (d) Publish the first Normative Reference Database for Quantitative Photoreceptor Biomarkers in healthy/diseased eyes. Our proposal fills an important technology gap in the field of retinal imaging. While the number and type of imaging devices continues to grow, the analytical tools to assess and manage images from these devices have not developed in parallel. As such, the diagnostic potential of these exquisite imaging devices remains unrealized. The validation of quantitative adaptive optics biomarkers will increase confidence in the outcome of clinical trials and reduce time to market for new cellular therapies. The reliability, reproducibility, and ease of use of MOSAIC will catalyze the adoption of adaptive optics fundus imaging and accelerated the development of therapies for blinding degenerative diseases.PROJECT NARRATIVE Neurodegeneration is implicated in almost all major causes of retinal vision loss and specifically in inherited degenerative eye disease; however, current clinical tools cannot effectively be used to judging efficacy of new preventative and restorative therapies. Translational Imaging Innovations (TII) will validate and commercialize a new software tool that combines an automated photoreceptor analysis package with comparative interrogation of an Image Bank that houses images obtained from a diverse set of patients, affected by over 100 retinal diseases. If successful, our innovative platform will provide a new class of biomarker that can used to evaluate disease progression and efficacy of therapeutics.