In Silico Methods For Drug Discovery Highlighted

November 3, 2000

NEWS BRIEFS

San Diego, CALIF. — The trend towards in silico (computer-based) design and selection of new molecules to improve the efficiency and reduce the cost of drug discovery and development will be a major theme at the American Association of Pharmaceutical Scientists (AAPS) meeting in Indianapolis from October 29 – November 2. At the largest annual gathering of pharmaceutical scientists in the world, Trega Biosciences, Inc., an innovator in modeling systems to simulate how drug candidates will be processed in the body, is presenting data on its absorption model, and “sneak previewing” the capability of its second model to predict metabolism. Absorption and metabolism are the first two modules of Trega’s iDEA Predictive ADME (absorption, distribution, metabolism and excretion) Simulation System.

“We are witnessing a paradigm shift in the pharmaceutical industry concerning the process of making smart decisions about which drugs to develop, and more and more software is becoming available to discovery scientists to enable such decisions earlier in the process,” said Patrick Sinko, Ph.D. Dr. Sinko, Trega’s Chief Scientist of Discovery Technologies, and Professor and Chairman, Department of Pharmaceutics, College of Pharmacy, Rutgers University, is a featured speaker at the AAPS Symposium on “Enabling Technologies for Ensuring Developability.”

Dr. Sinko added: “Much of the estimated cost of $650 million to get a drug to market is not for developing the one successful drug, but for the 90+% of drugs that will fail prior to getting to market. Perhaps the most exciting area, therefore, is in ADME simulation, because an understanding of the bioavailability of a drug in humans is so critical to its downstream success in the clinic. The Trega iDEA Simulation System, for example, offers a tremendous amount of leverage because it can be applied so early in the discovery process. Trega’s initial iDEA absorption module is designed to enable a scientist to use in vitro data to predict drug impact in humans.

Dr. Carleton Sage, Senior Computational Scientist, of Trega Biosciences, et.al., will present a poster on “In silico prediction of Caco-2 permeability from molecular structure.” Caco-2 is an established in vitro method for estimating permeability and an input to the iDEA absorption module. Trega set out to show that if Caco-2 permeability could be predicted using molecular structure, then human absorption properties could be incorporated much earlier in the drug discovery process, thereby eliminating wasteful and expensive testing of poorly absorbed compounds. After generating data on 230 drugs, both marketed and failed, Trega constructed a number of models, the best of which accurately predicts Caco-2 permeability based solely on molecular structure as in input. The experiment validates the premise that synthesis or experimentation may not be necessary first steps to understanding absorption characteristics of compounds.

“Currently, Trega is demonstrating the ability to go from structural data to predict the in vitro outcome. Thus, for the first time ever, the next generation of Trega’s absorption model will provide the research scientist with a design continuum that goes directly and reliably from the molecular structure of a drug on the computer screen to a prediction of the bioavailability of that drug on humans,” Dr. Sinko concluded.

Dr. Glen Leesman, Principal Scientist, of Trega will be presenting data that further validates the premise that Trega’s absorption model accurately predicts drug absorption when applied in a “real-world” pharmaceutical research setting. The accuracy of the model had initially been demonstrated using data provided by a consortium of pharmaceutical companies. The rate and extent of absorption of eight additional drugs, provided by F. Hoffmann LaRoche for this experiment, were then evaluated. The selected drugs had diverse chemical and physical properties and were provided for evaluation with molecular weight as the only form of identity. The Trega model accurately predicted the relevant biopharmaceutical outcomes for all eight drugs. Dr. Leesman’s, et. al., poster is entitled, “Assessment of the physiologically-based iDEA predictive model using an external (blinded) data set.”

“Consistent with our modular design strategy, our scientists have developed the next generation model that uses chemical structure to predict Caco-2 permeability. This feature is particularly applicable in early discovery for in silico screening of large numbers of compounds and significantly expands the scope of solutions that can be addressed by predictive modeling,” said Michael G. Grey, Trega’s President and CEO. “Furthermore, external researchers have validated the utility and reliability of the commercially available physiologically-based iDEA absorption model.”

Trega is developing a predictive model to simulate how a compound is metabolized in the human body and plans to preview elements of the model during the conference. The metabolism model is being developed using in vitro data and human pharmacokinetic data to build predictive relationships. The data required for this model includes the output from the iDEA absorption module and data generated by performing an in vitro hepatocyte assay in the laboratory. The model then predicts the amount of drug that passes through the liver unchanged.

“The development of our metabolism model is representative of our strategy of developing each module with collaborators in pharmaceutical companies. As we recently announced, Janssen Research Foundation and The R.W. Johnson Pharmaceutical Research Institute, members of the Johnson & Johnson family of companies, will collaborate with Trega to further enhance the predictive capabilities of iDEA predictive model,” continued Mr. Grey. “We intend to complete development of the metabolism module by the end of this year with the next release of the iDEA Simulation System. Trega plans to enable the comprehensive in silico prediction of bioavailability with a suite of modules to simulate absorption, metabolism, distribution and excretion.”

Trega Biosciences, Inc. is a premier provider of products that accelerate and improve drug discovery through its iDiscovery technologies linking biology and chemistry with information technologies. Trega’s iDEA Predictive ADME Simulation System of information-based models simulate, in silico, how drug candidates will be processed in the body, thereby enabling selection of those with optimal characteristics for clinical development. Together with its iDEA products, Trega’s Chem.Folio libraries of information-enhanced small molecules are designed to facilitate the identification and optimization of drug candidates. For additional information on Trega, please visit our Web site at http://www.trega.com .

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