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SAN BRUNO, Calif.—Numerate Inc., a drug design company that harnesses artificial intelligence (AI) to further small-molecule drug discovery, recently announced that the National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH) has awarded them a Small Business Innovation Research Phase I grant. Numerate, working with members of the UCLA Cardiovascular Research Laboratory (CVRL), will use the funds to initiate a drug discovery program targeting cardiac arrhythmias. The project targets the discovery of small-molecule drug candidates that address the need for a novel, well-tolerated antiarrhythmic therapy for the treatment and prevention of ventricular tachycardias and fibrillation.
 
When Numerate, a computational drug design company applying AI at cloud scale to drug discovery, was approached by CVRL in  late 2016, an opportunity was immediately recognized, and the company submitted its application for the grant. Using this AI technology, the researchers are expected to able to use the funds more efficiently and effectively, as Numerate offers the ability to investigate an area that has few test studies but a large pool of data, unlocking a puzzle previously unreachable. By having the ability to look at the big picture, they can use old data, past failures and past successes in making future decisions. 
 
According to the Mayo Clinic, more than 4 million Americans, most over age 60, experience heart arrhythmias (abnormal heart rhythms). Arrhythmias are caused by problems with the electrical system that regulates the steady heartbeat. The heart rate may be too slow or too fast; it may stay steady or become irregular and disorganized. The most serious and life-threatening arrhythmia is ventricular fibrillation, which is an erratic disorganized firing of impulses in the lower chambers of the heart and the most common cause of sudden cardiac death, claiming the lives of about 300,000 adults in the United States alone each year.
 
Dr. Uwe Klein, vice president of biology at Numerate, will lead the discovery efforts and serve as principal investigator for the project titled, “Peripherally restricted α2/δ-1 subunit ligands that modulate CaV channel gating as novel antiarrhythmic drugs.” The co-investigators consist of members of the UCLA Cardiovascular Research Laboratory, including Dr. Hrayr S. Karagueuzian, professor of medicine at the David Geffen School of Medicine and director of the Translational Arrhythmias Research Section, and Dr. Riccardo Olcese, professor of anesthesiology and physiology at UCLA, Division of Molecular Medicine.
 
“We are pleased to receive this award from the NIH and thrilled to be working with Drs. Karagueuzian and Olcese at the CVRL to build upon their existing work and discover an important new medicine for treatment of life-threatening arrhythmias,” said Klein.
 
Dr. John Griffin, chief scientific officer of Numerate, added, “Our AI-based drug discovery platform has the potential to accelerate the rapid discovery and development of novel small-molecule therapeutics, and we are looking forward to collaborating with these two renowned cardiac pathobiology experts.”
 
According to Griffin, most existing classes of antiarrhythmia drugs function by blocking voltage-dependent ion channels that conduct sodium, calcium or potassium ions. These drugs offer limited efficacy and often come with risks of inducing arrhythmias or reducing cardiac contractility. In contrast, he says, the Numerate small-molecule-driven approach is based on research findings from their UCLA collaborators that indicate that specific modulation of the late component of the voltage-dependent calcium current prevents or resolves life-threatening arrhythmias without impact on cardiac contractility.
 
“The NHLBI funding will expand upon our innovative research to manage cardiac arrhythmias with novel small-molecule drugs that specifically block the arrhythmogenic late inward calcium current without altering other cardiac ionic currents,” remarked Karagueuzian. “I look forward to working with the scientists at Numerate who have developed highly sophisticated approaches using data-driven machine learning and cloud computing to discover and develop a new antiarrhythmic drug therapy.”
 
“It’s a very exciting time for the fight against cardiac arrhythmias as my laboratory, which uses the quantitative rigor of biophysics to understand aberrant cardiac excitability, will benefit greatly from the application of artificial intelligence that Numerate brings to the table,” added Olcese. “Numerate is the ideal partner to complement my laboratory’s expertise and with the generous support from the NHLBI, we are ready to evaluate the capabilities of rationally designed next-generation antiarrhythmics.”
 
The project is in the early discovery phase, but reportedly the Phase 1 grant is sufficient to fund this first exploratory project to discover and identify a new class of drug compounds, which researchers estimate will take about six months. In this time, they will use the AI to begin running biochemical tests to compare them to observations made by the UCLA Cardiovascular Research Laboratory. From there the team will assay these compounds in simulated situations. Their hope is that these studies will lead to a novel oral treatment that will not cross the blood-brain barrier and thus adversely affect the central nervous system.
 
While it would be several years before human trials could begin, the AI-enabled discovery is expected to allow for a much faster timeline than the traditional 15-year design and execution of a clinical development program. The program will initially focus on patients that, based on biomarkers and/or genetic profiling, are likely to have dysfunction in late calcium currents that will be ameliorated with the specific drug being designed. After establishing efficacy and safety in treating these populations, testing of the drug will move on to patients suffering from more diverse disorders of cardiac rhythm.

Reporting/writing provided by Jennifer Clifford and Rachel Flehinger, DDNews contributing editors

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Volume 13 - Issue 10 | October 2017

October 2017

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