We support preclinical drug discovery by creating opportunities to screen in human disease-relevant platforms before or after animal studies. We explore the effects of drugs in preserving or improving the function and survival of iPSC-derived cells, such as cardiomyocytes, using strategies that could lead to "clinical trials in a dish," even down to the level of individual patients.
Shortening development times and assuring translatability by using human disease-relevant platforms.
Enabling exploration of therapeutic strategies tailored to individual patients.
We build our pipeline on human disease-relevant platforms rather than animal models. By running screens in human cells from the outset, we raise the predictive value of our preclinical data, select candidates with greater confidence, and shorten the path from hit to development candidate.
Our human-based platforms give our programs better translatability to clinical outcomes.
Early human-relevant data shortens our development timelines.
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Our platform combines human-relevant models with real-time readouts to forecast therapeutic efficacy and safety long before a compound reaches the clinic.
We use resonance energy transfer-based biosensors to interrogate large sections of the signaling signatures of specific G protein–coupled receptors (GPCRs). Deployed in adeno-associated viral formats in iPSC-derived cells, these biosensors let us determine which signaling pathways are modulated by dose-dependent activation of individual receptors, forming the basis for compound validation and new lead discovery across our programs.
By modeling disease progression in iPSC-derived cells, we track therapeutic response and examine how our compounds preserve or improve cell function and survival. This lets us test strategies that may work better in specific patient populations, an approach validated in clinical studies of cardiomyopathy patients.
Advanced imaging across cellular compartments gives us detailed analysis of compound effects on cellular function, generating the insight that guides candidate selection in our programs.
Predictive modeling lets us make informed decisions early in development, concentrating resources on the candidates most likely to succeed in the clinic.
Human-relevant models improve the predictive accuracy of our preclinical testing.
Facilitates the development of treatments tailored to individual patient profiles.
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