October 1, 2006 (Vol. 26, No. 17)
Companies Can’t Afford Not to Use Genomic Tools in their Clinical Studies
Biomarkers are capable of bridging the distance between basic research and late-stage clinical trials and can even shorten it. Many pharmaceutical and biotech companies are investing additional resources to bring biomarkers into the clinic. They hope that these efforts to practice pharmacogenomic research both in the preclinical and clinical stages will increase the odds of finding a successful drug.
At one of the industry’s largest annual gatherings, IBC’s “Drug Discovery Technology and Development (DDT)”, several industry leaders presented the results of using pharmacogenomics in their clinical programs.
Andrew Dorner, Ph.D., senior director at Wyeth Research (www.wyeth.com), gave a description of Wyeth’s work in translational medicine. The definition of translational medicine is rapidly evolving, but most would agree that it is an effort to remove barriers between new discoveries in scientific research and advances in the treatment of disease or care of patients. Historically, these barriers have been huge, and new treatments were selected on a hit-or-miss basis.
Wyeth is using transcriptional profiling to streamline its drug discovery program. The company is focusing on the molecular mechanisms of disease and using that information at every stage of discovery, including the clinic. “At the preclinical level, we employ transcriptional profiling to establish a gold standard of a drug hitting its target in animal models. We compare our compounds to that gold standard and use that molecular information to help select lead compounds going forward,” said Dr. Dorner. “What we’ve identified through our translational medicine initiative is that this kind of exploratory work for biomarkers in the clinic has to start early in the drug discovery process.”
Most of Wyeth’s biomarker discovery programs utilize the Affymetrix (www.affymetrix.com) microarrays for RNA analysis. However, the company also employs protein and small molecule profiling. Some of Wyeth’s successes include the identification of RNA transcripts in the blood samples of renal cancer patients that correlate with exposure to Wyeth drug candidate CCI-779 and one of its metabolites and the description of new candidate biomarkers associated with risk for meningoencephalitis and the outcome of IgG treatment.
Celera (www.celera.com) develops genetically based diagnostic tests. Ellen Beasley, Ph.D., senior director of therapeutics alliances, spoke about ongoing studies to understand the underlying genetic risk factors for disease.
According to Dr. Beasley, there are two ways that the genetic risk of disease can be applied to pharmacogenomics. One is by clinical trial enrichment, using genetic markers that predict the likelihood of a disease event or more rapid disease progression. For therapeutic areas focusing on spontaneous events, such as cardiovascular disease, clinical trial enrichment increases the likelihood of detecting therapeutic benefit.
“For some of these diseases, like cardiovascular risk or autoimmune disease, when a pharmaceutical company sets up a clinical trial, they are often pulling blindly from the deck to identify the right individuals,” noted Dr. Beasley. Since most people who are enrolled in a trial for a cardiovascular drug will not have an MI or a stroke, money is spent collecting data that will not be useful in demonstrating therapeutic benefit. “To the extent you can enrich for individuals at higher risk, the more effective and powerful your clinical trial will be.”
The second way that Celera is using genetic risk markers is as a source for therapeutic response markers. “What is surprising is that a number of genetic risk markers are also disease risk markers. We have an example of a marker in cardiovascular disease—the gene variant is a risk marker for repeat myocardial infarction and is also a response marker for the drug Pravastatin. We expect that the disease risk markers that we’re finding are going to be enriched for drug response markers. They are excellent candidates to test for drug response.”
It is advantageous to identify drug-response biomarkers well in advance of Phase III trials. One reason is that the FDA will not approve biomarkers identified retrospectively during Phase III trials. Another is that Phase III trials are not large enough to provide the data. A better way to identify these markers is by deriving them from the biological mechanism, or by testing biomarkers already known to be related to the drug or target. By selecting the right candidates, “You’re stacking the deck for yourself,” noted Dr. Beasley.
“Incorporating Pharmacogenetics in Clinical Studies”, an upcoming conference sponsored by the Institute for International Research (IIR), will focus specifically on using pharmacogenomics in the clinic.
Applications in the Clinic
Steve Anderson, Ph.D., will represent Labcorp (www.labcorp.com) and its subsidiary Viromed (www.viromed.com). One of the most famous success stories for a pharmacogenomic application in the clinic is the tale of Her2 and herceptin.
Her2 is a protein secreted by a subset of highly aggressive breast cancers. Genentech (www.genentech.com) developed a monoclonal antibody that binds to the receptors on the surface of the cells and results in the death of the cell. Labcorp was the primary testing laboratory that completed the studies necessary for Herceptin to be cleared as a cancer therapy.
“In a clinical trial, you could try to give the antibody to all women with metastatic breast cancer,” says Dr. Anderson. “You may or may not see a benefit because only a subset expresses that protein. What they decided to do was screen all potential individuals for levels of protein overexpression. This is a prime example of a targeted therapy where a diagnostic test is necessary to enrich the population.”
Additional studies on the Her2 gene showed that it was possible to do a genetic screen on the cancer cells. Multiple copies of Her2 on chromosome 17 were associated with aggressive cancers and a poorer prognosis.
Ginette Serrero, Ph.D., CEO of A&G Pharmaceuticals (www.agrx.net), has built her company around another breast cancer gene, GP88. She will be presenting at the IIR meeting the story of the development of a theranostic (biomarkers that have both therapeutic and diagnostic utility) that addresses the GP88 gene.
“In the case of GP88, I built up a cellular model system of tumorigenesis, starting from normal cells. From the normal cells, I developed cells that had increasingly higher tumorigenic properties. I compared these cells at the biological level and demonstrated that the tumorigenic cells were becoming dependent on their own conditioned culture medium to proliferate. If the cells become dependent on their own culture system, they are making what they need in contrast to the normal cells. From the culture medium of the tumorigenic cells, I purified and cloned GP88.”
According to Dr. Serrero, in fact, this approach, which worked with GP88, could work for the discovery of other cell surface biomarkers of cancer cells, a task that A&G is undertaking. “These proteins have the potential to be excellent diagnostic targets. Moreover, a diagnostic target can be converted to a therapeutic target by hooking up a toxin, for example.”
Oncology is one of the most common therapeutic areas for pharmacogenomics, but there are programs across a wide diversity of therapeutic areas. Gene Logic (www.genelogic.com) presented a case study of biomarkers discovered in patients with liver fibrosis and cirrhosis. The gene Fetuin-B was identified using in silico data mining with data from Affymetrix gene-expression arrays, and the results were presented at DDT.
The goal of the program was to find a biomarker that could be used in preclinical studies, and carry over into clinical studies. “At Gene Logic, we have built large genomic databases,” says Donna Mendrick, Ph.D., scientific fellow and vp of toxicogenomics. “Bioexpress® has 20,000 samples on Affymetrix arrays. The focus of Bioexpress is looking at normal and diseased human tissue. The second database is called the Toxexpress System, with over 14,000 samples. With it we are looking at control and toxicant compounds in rat tissues, primary hepatocytes, for example. That is where I started looking at toxic and treated rat tissues.”
These studies marry bioinformatics to pharmacogenomics, thereby leveraging two new technologies. “I am enthusiastic about this gene protein and this approach in general. When you have large databases, you can have large discoveries.”
One of the most important questions going forward with respect to pharmacogenomics in clinical drug trials is—what will the regulatory pathway be? Expression Analysis (www.expressionanalysis.com) blazed the trail by becoming the first company to submit electronic microarray data to the FDA in 2003, according to Steve McPhail, CEO.
“The reason that the FDA wanted to enter into this collaboration with us is that they had three overriding questions. What should be the format of this data in a regulatory submission? What should the content of the data be in a regulatory submission? What should the context of the data be? The FDA was comfortable with us because we were providing microarray data to a variety of clients in a variety of formats. Most of what you see in the voluntary genomic data submission draft guidance released in 2003 and the guidance released in 2005 came from work that we did with the FDA.”
At the upcoming IIR meeting, McPhail will present on a recent study. “In collaboration with Millennium Pharmaceuticals (www.millennium.com), we looked at the use of Velcade in patients with multiple myeloma. Only a couple of companies had looked at this data collected prospectively,” says McPhail. Bone marrow aspirates were taken from patients at more than a dozen clinical sites spread throughout the U.S. Clinical response was noted, and samples analyzed on Affymetrix microarrays. Out of this data, Millennium obtained 30 gene markers that predicted response.
There is no question that applying pharmacogenomics to clinical trials increases the cost. There is added cost in the preclinical stages, where biomarkers must be identified and validated. Then there is extra cost in the clinic, where study design needs to take genetics into consideration.
Additionally, using a pharmacogenomic approach could even slow down clinical trials if you must seek out a patient population that is enriched for your trial. But there is a general consensus that these costs are completely justified and the return on investment very much worthwhile. In fact, with a dearth of drugs coming out of the pipeline under the more conventional methods, one could argue that no pharma company can afford not to use genomic tools in their clinical studies.