Combined Computational and Cardiac Microphysiological System Approach for Drug-Induced Proarrhythmia Screening

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Project Summary / Abstract Barely a day goes by when the urgent need for new medicines is not highlighted despite record levels of investments into R&D. But the poison chalice of drug attrition remains, stagnating the flow of new medicines to those that need them. Whilst this is not a new problem, there is a strong belief that the ability to optimally mitigate safety risk in efficacious drug candidates will come from a greater refinement of safety margin estimates together with a greater understanding of translation from in silico, in vitro and in vivo models to humans. Within the last decade we have seen the emergence of induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) as important tools for translational understanding of cardiac disease biology and prediction of cardiotoxicity. Despite their considerable advantages, hiPSC-CMs are typically structurally and functionally immature, reducing their predictive potential. Accordingly, greater understanding of the underlying mechanisms and processes for maturation such as physiological hypertrophy, metabolic and structural changes will improve this situation as they are incorporated into in vitro tissue models. Here, Organos Inc. proposes a solution to these challenges in the realm of cardiovascular drug liability through the commercial development of an in vitro cardiac microphysiological system (MPS), a microtissue construct based on hiPSC-CMs, combined with novel in silico computational methods to provide early, accurate information on drug proarrhythmia liabilities. At the heart of this system are frameworks for maturation, preliminary data indicates that hiPSC-CM maturation is improved biologically in the MPS model, but we also have the potential to computationally mature cells through our novel algorithms, offering considerable time and cost reduction opportunities whilst maintaining physiological relevance. In this proposal, we will validate our integrated cardiac MPS testing and in silico computational analysis system across a range of drugs with known cardiac effects. The two specific aims will first refine the hardware form factor and computational methodology to improve prediction, speed and scalability of the system, and second validate the combined computational/MPS system to rank compounds with known drug-induced proarrhythmia risk according to their clinical risk of Torsade de Pointes (i.e., ventricular tachycardia) for a patient population of cardiac MPS devices.