CSO Report: Collaborating with academic investigators to unlock emerging biology

A most distinctive and valuable application of our AI platform is to rapidly advance small molecule therapeutic programs that exploit exciting insights as they emerge from basic biomedical research.  Our ability to learn accurate, scaffold-hopping predictive models from small, non-diverse and noisy training sets enables us to initiate and accelerate work against new targets from an early stage, e.g., from the point where an academic group has identified a small number of tool compounds having an activity of interest in a complex high-content/low-throughput assay that exists only in that laboratory.  Many promising projects that have the potential to address major unmet medical needs and opportunities languish at just this point because they cannot be adapted to traditional pharmaceutical screening and lead design processes.  We are able to unlock these projects, leveraging our AI to bootstrap the limited information content of initial training sets into models that we then use to screen large (107-109) compound libraries in silico to quickly (and with high laboratory-validated accuracy) expand the number and diversity of active compounds.  This sets the stage for AI-driven Hit-to-Lead and Lead Optimization.

We have published some of the results we have obtained in collaboration with leading academic laboratories.  With Prof. Chaitan Khosla and his group at Stanford, we demonstrated our ability to identify and improve upon new inhibitors of transglutaminase 2 (TG2).  Here, we built useful predictive models from a small training set comprising two very different chemotypes that were later found to bind to different binding sites on, and different conformational states of, TG2.  With Prof. Carl Nathan and his colleagues at Weill Cornell Medical College, we highlighted the scaffold-hopping capabilities of our models to identify structurally distinct new inhibitors of protein kinase R, including a potent, non-cytotoxic inhibitor suitable for use as a biological probe of PKR function.

More recently, we applied our AI to identify new stabilizers of the cardiac ryanodine receptor (RYR2), and licensed them to Servier.  Our work on this project benefitted from a very productive interaction with Prof. Wayne Chen at University of Calgary.  We also enjoyed a very productive collaboration with Prof. Robert Mahley of the J. David Gladstone Institutes where, with financial support from a Seeding Drug Discovery Award from the Wellcome Trust, we designed multiple series of ApoE4 structure correctors as potential leads for treating Alzheimer’s disease.  These became core assets for E-Scape, the founding and financing of which was recently announced.

Applying advanced AI in conjunction with cutting-edge biomedical science to produce scarce, first-in-class therapeutic assets sits at the core of Numerate’s business.  We believe that recognition of the value of translating insights into assets for compelling yet challenging targets, by Pharma partners and venture investors, has validated our strategy.  We look forward to continuing and expanding work with investigators from leading research institutions, as in our recently announced, NIH-funded collaboration with UCLA’s Cardiovascular Research Laboratory, where we are seeking to unlock an exciting new approach to preventing fatal heart arrhythmias.

National Institutes of Health Awards Innovation Research Grant to Numerate to Accelerate Discovery of Novel Antiarrhythmic Drug Candidates

Numerate and the UCLA Cardiovascular Research Laboratory will focus efforts on identifying therapy for the treatment and prevention of ventricular tachycardias and fibrillation (VT/VF)

San Bruno, CA – Numerate, Inc., a computational drug design company applying artificial intelligence (AI) at cloud scale to transform small molecule drug discovery, announced that the National Heart, Lung, and Blood Institute (NHLBI) of the National Institutes of Health (NIH) has awarded Numerate a Small Business Innovation Research (SBIR) 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 (VT/VF). Uwe Klein, Ph.D., Vice President, 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 project is funded under Grant Number 1R43HL139143-01.

The co-investigators include esteemed members of the UCLA Cardiovascular Research Laboratory, including:

  • Hrayr S. Karagueuzian, Ph.D., Professor of Medicine at the David Geffen School of Medicine at UCLA, Director of Translational Arrhythmias Research Section
  • Riccardo Olcese, Ph.D., 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 Dr. Klein.

John Griffin, Ph.D., 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”.

“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,” said Dr. 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,” said Dr. Riccardo 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.”

About Cardiac Arrhythmias

According to the Mayo Clinic, more than 4 million Americans, most over age 60, experience heart arrhythmias (abnormal heart rhythms)[i]. 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[ii]. The most serious and life-threatening arrhythmia is ventricular fibrillation (VF), which is an erratic disorganized firing of impulses in the lower chambers of the heart, called the ventricles. VF result in the heart being unable to pump blood, and is the most common cause of sudden cardiac death, claiming the lives of about 300,000 adults in the United States each year[iii].

AI Pharma Summit Meeting

Guido Lanza (CEO) and Brandon Allgood (CTO) attended the AI Pharma Summit in Boston last week.  The meeting brought together both large and small companies pushing the boundaries of AI in Pharma R&D.  Overall the discussions were productive, but there is a lot of work to be done and that is exciting! Below is the technical keynote given by Brandon at the meeting.