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UCSF and Optivia collaborate to predict liver toxicity in drugs development process
11-17-2010
by Jeffrey Bouley  |  Email the author
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MENLO PARK, Calif.—Optivia Biotechnology Inc., a provider of in vitro transporter assay services and the University of California, San Francisco (UCSF), have received a $430,000 Small Business Innovation Research (SBIR) grant from the National Institutes of Health (NIH) to develop what they call "an innovative system for characterizing the role transporter proteins play in the disposition of drugs by the liver."

The goal of the two collaborators is to develop a transporter-based assay system that is capable of predicting the absorption, distribution, metabolism and excretion (ADME) of drug candidates, which is a key step to optimizing a drug's safety and efficacy. Liver toxicity in particular is a notable cause of failure of potential drugs to make it to market—the primary cause of clinical failures, in fact, and one of the most common reasons for marketed drugs to be withdrawn.

Such failures have translated into increasing costs of drug discovery and development, with the U.S. Food and Drug Administration's 2004 Critical Path Initiative white paper estimating that clinical failures based on liver toxicity alone have cost one major pharmaceutical company more than $2 billion in the last decade.

Optivia and UCSF add that some 86 percent or more of all compounds and about 40 percent of clinical-stage drugs fail due to unsatisfactory ADME, toxicity and clinical safety properties. Drug-induced hepatotoxicity is estimated to be responsible for as many as five percent of all hospital admissions and 50 percent of all acute liver failures, they note, adding "It is well-established that transporters greatly influence the hepatic disposition of a number of commonly used drugs (e.g. antibiotics, statins, and hypoglycemic agents) and others that were subsequently removed from the market (e.g. the antidepressant nefazodone)."

"The grant will allow us to build on UCSF's previous work suggesting that we can predict how drugs will behave in the body, specifically the liver, based on transporter biology," says Dr. Leslie Z. Benet, of the university's Department of Bioengineering and Therapeutic Sciences and a member of the International Transporter Consortium. "We intend to provide a body of systematic data based on the in vitro profiling of a large number of drugs against a panel of key human transporters as the first step toward building transporter-based predictive models for the assessment of ADME and drug-drug interactions (DDIs)."

"This collaboration reflects our response to the specific call from the pharmaceutical industry and regulatory agencies for systematic data, both in vitro and in vivo, with respect to how drugs interact with multiple transporters expressed in various human organs, and how such interactions alter drug pharmacokinetics in the human body," says Dr. Yong Huang, president and CEO of Optivia Biotechnology. "Integrating analysis of drug transporters is increasingly becoming a core requirement in ADME assessments and is anticipated to become a regulatory standard for new drug applications."

In the Phase I study, Optivia Biotechnology and UCSF will systematically test 40 marketed drugs against ten major hepatic transporters, then correlate the in vitro drug-transporter interaction data with in vivo information on the disposition of drugs in the liver, with the aim of building a more definitive, earlier-stage model for predicting actions of drugs in humans. The Phase I study will also address the interplay between transporters and drug metabolizing enzymes.

"The industry has long observed discrepancies between measuring drug metabolism in existing experimental systems," says Huang, "Transporters likely contribute to the observed discrepancies. Considering transporters when assessing metabolism will result in the generation of better in vitro models."

"A model that correlates in vitro data to in vivo results would be of incalculable value to the pharmaceutical industry, since it will allow drug developers to make better decisions on the ADME properties of drug candidates prior to performing in vivo studies, most likely reducing development costs and decreasing the number of failures related to the ADME properties of drugs," adds Benet. "The unique capabilities of the Optivia platform will allow us to move forward on this critical step in building transporter-based predictive models for ADME."
 
 
Code: E11161001

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