Wyeth's recently expanded agreement with Expression Analysis should help the drugmaker more smoothly prepare electronic submissions of pharmacogenomic clinical data to the FDA.
Under the agreement, which was first developed in 2003 and implemented in July 2004, Expression Analysis provides Wyeth with contract pharmacogenomic testing services using the Affymetrix GeneChip platform, said Andrew Dorner, senior director for biological technologies at Wyeth. Pharmacogenomic data could lead to the development of personalized therapies based on patients' genetic profiles.
"Our relationship with Expression Analysis is an agreement by which our clinical pharmacogenomics samples are run on Affymetrix GeneChips," he said. "The data are transferred to Wyeth, where we do statistical analyses and data analyses of these baseline profiles and blood profiles, correlating them with patient symptoms."
"We certainly can submit data to the FDA in electronic format -- we were the first company to follow the voluntary genomic data [VGD] submission guidelines," Dorner continued. But in practice, "it's not all electronic -- we tend to supply them with PDF files of reports, but when they want to see the data we submit it to them electronically," he said.
The VGD guidelines are part of an FDA initiative to obtain as much clinical pharmacogenomic data as possible "to see what is going on with this new technology," Dorner said. Wyeth is cooperating closely with both the agency and Expression Analysis on pharmacogenomics, which has been the subject of three recent FDA workshops. "They are working with industry. Draft comments were floated. It's a continuing interactive process. The FDA has shown a lot of initiative in this area," he said.
"The main thing is the potential for pharmacogenomics using transcriptional profiling. The clinical outcomes are being explored heavily by industry and the FDA," Dorner said. For now, he added, "there is a lot of laboratory-to-laboratory variation" in transcriptional profiling -- a genetic technique used to identify patients for clinical trial, predict the onset of disease and customize treatment regimens for individual patients. Expression Analysis is helping to bring standardization into this area, Dorner said.