Numerate and Boehringer Ingelheim (Canada) Form Drug Discovery Collaboration

Our business and technology momentum continues to grow, as evidenced by our new collaboration with Boehringer Ingelheim (Canada).  Under the agreement, we plan to speed the process of delivering active lead compounds against an important infectious disease target

Numerate and Boehringer Ingelheim (Canada) Form Research Collaboration Based on In Silico Drug Design Technology; Drug Discovery Research to Focus on Infectious Disease Target

SAN BRUNO, CA – December 6, 2011Numerate, Inc., a technology platform company that is leveraging the power of cloud computing and novel computational methods to transform the drug design process, announced today that it has entered into a research collaboration with Boehringer Ingelheim (Canada) Ltd. The collaboration will utilize Numerate’s proprietary in silico drug design technology to generate novel small molecule drug leads for an undisclosed infectious disease target.

“Using our large-scale computational drug design methods, we expect to greatly reduce the time and cost of delivering new lead-stage, small molecule drug candidates in this important program for Boehringer Ingelheim,” stated Numerate chief executive officer Guido Lanza. “This collaboration is the latest in our growing number of partnerships with pharmaceutical companies that are looking to Numerate’s comprehensive in silico drug design technology to help them increase their success rate in generating novel, patentable small molecule leads.”

Numerate’s drug design platform features a set of proprietary algorithms that provide predictive models for molecular properties with accuracies comparable to laboratory testing.  Used in conjunction with cloud computing, these algorithms enable Numerate scientists to search through spaces of billions of compounds to rapidly and efficiently identify those with the highest probability of activity against a specific target.

Recent Numerate Publications

Two papers were recently published reporting results obtained in projects carried out in collaboration with Prof. Chaitan Khosla of Stanford University and with Prof. Carl Nathan of Weill Cornell Medical College.  This work illustrates our ability to rapidly advance early stage projects to hit-to-lead and lead optimization, even when starting from only a couple dozen, non-diverse active compounds.  The work with Prof. Khosla on inhibitors of transglutaminase 2 (TG2) as potential therapies for celiac disease and metastatic cancer has resulted in the identification of multiple new and proprietary lead series.  The work with Prof. Nathan on inhibitors of protein kinase R (PKR) as therapies for tuberculosis resulted in the identification of a valuable probe compound, NMRT-2862, which inhibits PKR within macrophages without overt cytotoxicity and recapitulates the effects of genetic inactivation of PKR.

Full References:

Acylideneoxoindoles:  A new class of reversible inhibitors of human transglutaminase 2.”  C. Klöck, X. Jin, K. Choi, C. Khosla, P.B. Madrid, A. Spencer, B.C. Raimundo, P. Boardman, G. Lanza and J.H. Griffin. Bioorg. Med. Chem. Lett. 2011, 21, 2692-2696.

Identification of new inhibitors of protein kinase R guided by statistical modeling.”  R. Bryk, K. Wu, B.C. Raimundo, P.E. Boardman, P. Chao, G.L. Conn, E. Anderson, J.L. Cole, N.P. Duffy, C. Nathan and J.H. Griffin. Bioorg. Med. Chem. Lett. 2011, 21, 4108-4114.

Numerate receives Red Herring’s Top 100 Award

We were pleased to receive Red Herring’s Top 100 award in June, which is given to selected North American tech start-ups in recognition of their vision, drive and innovation, as well as their strong potential for success. Hundreds of companies competed for this recognition, which was granted based on both quantitative and qualitative criteria, such as financial performance, technology innovation, management quality, corporate strategy and market penetration. According to the Red Herring editorial staff, the Top 100 list is “a valuable instrument of discovery and advocacy for the most promising new business models in North America.”

Numerate awarded patent

Numerate was recently awarded U.S. Patent 7,856,321 B2, covering the development of models based on phenotypic data. Specifically, it captures the idea that predictions of binding may provide a suitable representation for developing models of phenotypic effects thought to relate to binding events, but where the particular binding interactions underlying the effect may be unknown. We have validated this approach in the laboratory and used it to identify novel anti-bacterial compounds. The results of this work will be presented at the upcoming American Chemical Society meeting in Anaheim.

Congresswoman Jackie Speier joins Numerate for contract announcement

speierWe were pleased to welcome Congresswoman Jackie Speier to Numerate today, who joined us in announcing our three-year DTRA contract for speeding the design of biowarfare countermeasures.  Also speaking at the press conference were Jeremy Leffler, Bay Bio Chief Operating Officer, along with our CEO Guido Lanza and our CTO, Nigel Duffy.  The event, which highlighted Numerate’s achievements and potential contributions to both the biodefense and healthcare industries, was covered by members of the local TV and print media.

Four recent press articles

We’re excited about our recent press coverage, which reflects our increasing momentum and progress in developing our technology as well as advancing our partnering business. In fact, there are four recent articles that we wanted to bring to your attention:

The first, from the San Francisco Business Times, paints a high-level picture of the parallels between our approach to ranking molecules and strategies such as Google’s PageRank. We are particularly excited that the article highlighted what we believe to be our most compelling competitive advantage — our ability to deliver white powder in vials that performs as predicted in the lab.

http://www.portfolio.com/industry-news/health-care/2010/08/25/numerate-uses-technology-to-choose-which-drugs-to-advance

This article from FierceBiotech IT, expands on the Business Times piece and discusses the patent we were granted covering our novel application of machine-learning technology to challenges in drug discovery.

http://www.fiercebiotechit.com/story/report-google-code-tackles-drug-development/2010-08-20

We were pleased that BioCentury chose to feature Numerate in an “Emerging Company Profile,” which provides an in-depth look at our technology and describes the progress we’ve made since founding the company in 2007.

http://www.biocentury.com/biotech-pharma-news/emergingcompany/2010-08-23/numerate-believes-its-in-silico-drug-design-produces-less-risky-small-molecules-a13

Finally, BioWorld ran an item announcing the successful completion of our collaboration with Intellikine, noting that we were able to deliver backups for Intellikine’s already impressive lead series for PI3K–alpha inhibitors.

We will keep you apprised of similar articles in the future as we continue to grow our business, build our technology, and meet significant milestones, both for us and for our partners.

Numerate’s ranking technology for pharmaceutical R&D gains U.S. patent

We’re excited to have been awarded this significant patent. Modern machine learning methods are starting to produce remarkable results in a number of fields. Typically this requires a combination of deep domain expertise and the machine learning expertise to adapt and develop techniques to fit the idiosyncratic challenges of the particular domain. It’s exciting to lead such an effort in drug design, and demonstrate that truly modern machine learning techniques can have a significant impact on the quality and cost of healthcare.

Numerate’s ranking technology for pharmaceutical R&D gains U.S. patent; Pioneering Use of Machine-Learning Technique to Speed Drug Discovery

San Bruno, CA, May 27, 2010 — Numerate, Inc. announced today the grant of U.S. Patent No. 7,702,467 B2, which provides patent protection for methods of using biological assay data to develop predictive models. These models have accuracies comparable to laboratory testing.

The patent, titled “Molecular Property Modeling Using Ranking,” describes methods for using advanced machine-learning technology to design novel small molecule compounds in silico that meet specific candidate drug profiles. This “ranking technology” enables the use of new kinds of experimental data beyond those accessible by any other statistical techniques.

Numerate’s ranking algorithms represent the first successful effort to apply these modern machine-learning techniques to problems in drug design. In recent years, related advanced machine-learning algorithms have emerged from academia and been adopted in a number of fields, most notably in finance, web-search, ad placement (at Google), and product recommendations (at Amazon and Netflix).

“The machine learning challenges in drug design are substantially different from those in other fields, such as product recommendation,” said Nigel Duffy, Ph.D., Numerate’s Chief Technology Officer. “To make accurate predictions, we have developed ways to address key issues, including the bias inherent in biological data, and the experimental noise typical in assay results. As a result, we are able to deliver novel compounds that meet pre-specified objectives and perform in the laboratory as we predict they will.”

“The traditional approach to drug design is a process of discovery, and is driven by intuition and, often, serendipity,” stated Guido Lanza, Numerate’s Chief Executive Officer. “By definition, it is limited by human’s ability to make complex design decisions against competing objectives in enormous spaces of chemistry. The only way to improve the efficiency of drug discovery significantly is with a new approach that lets the data drive the design and addresses these multiple objectives simultaneously. Numerate’s platform provides the basis for just such a paradigm shift. We are using it today to substantially reduce the time and cost of designing and delivering lead-stage, small molecule drug candidates to our partners.

“This patent significantly extends our leadership position in technology for predicting the properties of small molecule drug candidates,” added Mr. Lanza.

Numerate’s drug design platform represents an investment of $30 million and ten years of work. The foundation of this platform is a set of proprietary algorithms – including those using modern ranking methods – that provide accurate predictive models for molecular properties, long a holy grail of drug design.

To make their discoveries, Numerate scientists run their platform on Amazon’s Elastic Compute Cloud (EC2), allowing them to search through spaces of hundreds of millions of compounds to identify those with the highest probability of activity against a specific target. The compounds are then synthesized and their properties verified in the laboratory.

Numerate’s achievements in HIV illustrate the strength of the company’s platform. In six months, with only 21 compounds made, Numerate designed, synthesized, and tested novel compounds that demonstrated greater potency and spectrum than the market-leading drug in the class. In addition, these compounds had significantly improved pharmaceutical properties.

“These results are remarkable, given that a typical program could require 10 years and $20 million to achieve similar results. In contrast, our accomplishment took one-tenth of the time and one-hundredth of the cost,” said John Griffin, Ph.D., Numerate’s Chief Scientific Officer.

The platform company: Product or partner?

I was recently invited by Bioentrepreneur to outline my thoughts on developing a platform company in light of Numerate’s focus on establishing partnerships to both expand our therapeutic reach and build a self-sustaining business model.

In a nutshell: The early stage of business development presents a chicken-and-egg problem: you need to build and validate the platform to attract investors or partners, but building and validating the platform actually requires funding from investors or partners.

My recommendation: Your first few deals should emphasize science and validation, not economics.

Link: Building today’s platform company, Bioentrepreneur, 6/30/09