Cell-based assays are a promising tool for drug discovery, particularly in neuronal and cardiac diseases where molecular targets are often unknown. The key to an effective assay is the readout: how did the test compound affect the cell? Electrophysiology is considered the gold standard for characterizing electrically active cells; but conventional electrophysiology is not amenable to high-throughput studies needed for drug discovery.
Q-State Biosciences combines stem cell technology, optogenetics, and advanced optical imaging to create in vitro models of neuronal and cardiac diseases using genetically diverse human cells. The company leverages the stem cell-based disease models developed in the lab of Kevin Eggan and the voltage-indicating protein and advanced imaging platforms developed in the lab of Adam Cohen, both at Harvard University, to provide a new approach to preclinical drug development, patient stratification, and precision medicine.
Q-State technologies enable, for the first time, all-optical electrophysiological characterization of human disease models. This advance comes from three core technologies:
- Stem cell-based disease models. Recent advances in genome editing, stem cell protocols, and direct reprogramming enable creation of cell-based disease models with fully characterized genetic background and direct reference to clinical data from the human donor.
- Optogenetic reporters and actuators. QuasAr proteins derived from a Dead Sea microorganism convert action potentials into visible flashes of fluorescence that are readily detected in a microscope. Simultaneous optogenetic stimulation probes the activity of cells across their full dynamic range.
- Advanced instrumentation. Custom microscope systems optically stimulate and record electrical propagation in cells, in culture or in intact tissue, with unprecedented speed, sensitivity, and spatial resolution. Sophisticated bioinformatics algorithms automatically convert vast datasets into biologically meaningful data on cellular function and response to drugs.