Biotech Values

[spartex]

FDA Advisory Panel, Au naturel

Doing What Comes Natural. I read with interest the transcript and viewed the slides from the FDA CBER advisory panel to which dwmcdonald2003 and jersey posted links.

The purpose of convening this panel was to discuss what measures can be used to determine if biologic therapies are working. In other words, is there a measurable data that correlates with effectiveness? Why is the FDA doing this? The new leaders at the FDA have started a push to get effective drugs/therapies through the regulatory process. The push is for drugs that have a measurable value that correlate with clinical effectiveness. An example would be the drug Herceptin. Patients’ breast cancers are tested for Her-2/neu status. If the tumors are found to be Her-2/neu positive, the patients respond better to the drug, herceptin. Patients that are Her-2/neu negative usually don’t respond and therefore do not receive the drug saving the expense and side-effects from the drugs. Drugs that have a clear, measurable value that help predict which patients will respond to the treatment will have an easier time during the regulatory process.


DNDN is too late in the game to totally gain from the paradigm shift at the FDA since DNDN has a late stage product but the FDA wanted their expertise concerning measurable values. DNDN’s Nicole Provost was testifying. She presented data for DNDN’s lead product, Provenge (sipuleucel-T). She was discussing CD54 and CD54 upregulation as a measure of potency for Provenge. She showed slides that clearly showed that CD54 upregulation correlated with survival.

After seeing the data, the members of the panel did what would come natural to any in the medical field. They started asking about the trials. At times they seem to lose focus on what they were there for, a discussion of how to obtain measurable data to determine a biological’s effective, and discussed the striking results of the Provenge trial. For example: Dr. Harlan: The Kaplan-Meier curves are compelling. I just wonder if the studies are large enough for those curves to be statistically significantly different… and Dr. Tomford: What is the time line on the survial curves, and have you looked at something beyond the time - -you know, long time. What happens over a long period of time?


This prompted the moderator, Dr. Mule, to have to make the following statement: Dr. Mule: I think these questions are important but, again, our mission here is to really work with the speakers and others as far as the potency release criteria of the product.


You can see why if a group from CBER gets to be on Provenge’s advisory panel, Provenge’s chances for approval greatly increase. These people seem to recognize a good thing when they see it.


Read it for yourself. Look at the slides with data for CD54 upregulation and compare the p-11 and D9902b results with the D9901 and D9902a results. The p-11 CD54 upregulation data is as good as or better than D9901. The D9902a CD54 upregulation data was slightly lower. We all know that the D9902a survival data was slightly lower than D9901. Is this a coincidence?

http://www.fda.gov/ohrms/dockets/ac/cber06.html#CellularTissueGeneTherapies
Go to: Transcript for Feb. 9, 2006
Potency Testing for Autologus Cellular Therapy
Nicole Provost PhD.
P. 131

Go to: Slides February 9,2006

From DNDN yahoo MB posted by zurdoc1

http://finance.messages.yahoo.com/bbs?.mm=FN&action=m&board=1600905258&tid=dndn&sid=...