Affymetrix Announces New Product for Standardising Drug Metabolism Studies
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Affymetrix, Inc. has announced the DMET™ Plus Premier Pack, a comprehensive method for standardisng drug metabolism studies. The DMET (Drug Metabolism Enzymes and Transporters) Plus Panel features biologically relevant content identified by key opinion leaders from industry and academia.
The DMET Plus Panel contains markers in all FDA-validated genes and covers more than 90 percent of the current ADME Core markers as defined by the PharmaADME group. It offers 1,936 high-value drug metabolism and transporter markers.
Researchers in the pharmacology of cancer therapies are already using the DMET Panel to better understand the toxicity of and response to chemotherapeutic agents. The DMET Panel enabled John Deeken, M.D., from the Lombardi Comprehensive Cancer Center at Georgetown University, to find numerous genes potentially involved in cancer treatment decisions, in collaboration with Affymetrix.
"The DMET Panel allowed us to characterize the pharmacogenetics of the chemotherapeutic agents docetaxel and thalidomide in patients treated for prostate cancer in a Phase II clinical trial, demonstrating that the DMET Panel can be readily incorporated into cancer clinical trials," said Dr. Deeken. "The breadth and depth of the DMET Panel provides a unique approach to determining genetic variations' relevance across a drug's metabolic pathway."
"Affymetrix is the first company to deliver a comprehensive drug metabolism solution," said Kevin King, president of Affymetrix. "In the U.S. alone, adverse drug reactions are the fourth most common cause of death, costing $100 billion. With the DMET Plus Premier Pack, we are enabling industry, academic, and government researchers to identify the high-quality biomarkers that will enable them to ask broader questions and make better go-no-go clinical trial decisions."
The DMET Plus Premier Pack also offers software which enables customers to look only at the markers they want to genotype, or those that are allowed by patient consent. Data is automatically interpreted into the commonly used star allele format which can be integrated into clinical trial workflows.
