OUR APPROACH - Preclinical Network Measures
A key reason why neuroscience drug development has seen limited success in recent years is the inadequacy of preclinical animal models of behavior. Simply put, measuring the effects of compounds on rodent behaviors has proven to be a poor predictor of efficacy in humans. However, our hypothesis is that the brain activities underlying behaviors are better conserved between animals and humans than the behaviors themselves. An important emergent feature of both human and animal brain networks is their ability to synchronize and undergo oscillations at a broad range of frequencies. Critically, these oscillations are altered in numerous CNS disorders, as well as in animal models of these diseases, demonstrating their functional relevance and utility for investigating human disease in preclinical animal models. To capitalize on these conserved brain activities, we have developed sophisticated assay systems for measuring the effects of compounds on network oscillations in vitro and in vivo. This added dimension of brain network analysis improves the predictability of animal behavioral assays for guiding preclinical drug discovery and translating basic preclinical discoveries into effective therapeutics in the clinic.
Brain slice network assays
The in vitro component of the system measures electroencephalogram (EEG) activities in rodent brain slices. Using perforated multi-electrode array (MEA) technology, we record robust network oscillations generated from local synaptic circuitry in the slice. With support from NIMH, we have developed a medium-throughput version of this assay with which we perform multiple assays of network activity in parallel to screen for compound efficacy.
In vivo EEG-based behavioral assays
The in vivo component of the system measures EEG activity in awake and behaving rodents performing a variety of tasks. Developed with support from NIMH, the system integrates brain activity recordings with digitized rodent behavioral analysis to precisely correlate brain activity with behavior and to determine the effects of compounds on these processes. Using this assay system, we have identified in vivo EEG signatures of mouse disease models and are applying specific EEG measures to advance compounds in our drug discovery programs. To create an effective path for clinical development, we are translating these disease-relevant preclinical network measures into human EEG-based biomarkers (see Clinical Network Biomarkers).