BullFrog AI Announces Strategic Partnership with The Lieber Institute for Brain Development to Improve Antipsychotic Drug Selection
February 15, 2018
Cutting-edge artificial intelligence platform to analyze antipsychotic drug use data from leading brain development institute to predict patient outcomes.
WASHINGTON DC, and BALTIMORE, MD – Feb. 15th, 2018 ― BullFrog AI, Inc, industry leaders in artificial intelligence and clinical data analytics services, and the Lieber Institute for Brain Development, an independent, not-for-profit medical research institute working to accelerate efforts to find new cures for developmental brain disorders, today announce a joint collaboration to apply BullFrog AI’s proprietary artificial intelligence platform to analyze anti-psychotic drug responses.
The prescription of antipsychotic drugs represents one of the most challenging areas for clinicians and patients alike, with patients experiencing wildly differing responses to the different drugs on the market, particularly when it comes to the side effects. The selection of the best drug for the particular patient then becomes a matter of trial and error, potentially causing distress and even harm to patients and those around them.
Under the terms of the agreement, BullFrog AI will utilize their proprietary artificial intelligence platform to analyze large multi-factorial clinical data sets from patients who received antipsychotic medication. BullFrog AI’s proven analytics engine (bfLEAP™) will help physicians predict which patients respond best to which medications, effectively eliminating the problem of trial and error prescriptions.
“We are excited to partner with BullFrog AI on this challenging clinical problem,” said Dr. Kristin Bigos, Investigator, Lieber Institute for Brain Development. “Until now there has been no effective alternative to the trial and error approach for matching patients to the best antipsychotic. Being able to understand and predict a priori which drugs will work best for which patients would be of tremendous benefit to both patients and the physicians that serve them”.
The bfLEAP™analytics engine is uniquely suited to solving this type of problem. The platform is purpose-built for analyzing extremely large and complex data sets, something that is a known limitation for other analytical platforms. Indeed, bfLEAP™ has demonstrated 99.9% accuracy in predicting the right targets across multiple data sets. The key to its success is the artificial learning, which requires no domain expertise. Instead, it uses unsupervised machine learning coupled with the world’s largest collection of analytical models, all operating in parallel.
“bfLEAP™ represents a true leap forward in terms of our ability to understand what is going on in a complex clinical setting,” said Vin Singh, CEO of BullFrog AI. “For the first time, we are able to analyze massive, multi-factorial clinical data-sets and determine the root cause of the observed clinical outcomes. Using our platform, we can examine clinical trial data and identify relationships between patient-specific factors and clinical response, which may aid in predicting clinical trial outcomes in the future. The potential impact of this type of information for the pharmaceutical industry in enormous both in terms of the reduced cost and increased revenue from failed drugs as well as the positive impact to patients.”
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