Joe Nocera, "Why Doesn’t No Mean No?": Avastin and the Need to Find Meaningful New Therapeutics

In his New York Times op-ed entitled "Why Doesn’t No Mean No?" (http://www.nytimes.com/2011/11/22/opinion/why-doesnt-no-mean-no.html?_r=1&hp), Joe Nocera observes that Avastin, whose sales amount to some $7 billion annually, has failed as a breast cancer therapy, although it has extended life by several months on average for lung cancer and renal cancer patients:

"For lung cancer patients, Avastin plus chemotherapy extends life by an average of two months longer than chemotherapy alone. For renal cancer patients, Avastin gives the average patient an additional 4.8 months of what’s called 'progression-free survival' — meaning that the tumors don’t grow and the cancer doesn’t spread for that amount of time."

I find it disturbing that this "blockbuster" drug has been found to offer little hope for women suffering from breast cancer, and only minimally extends the lives of those suffering from other types of cancer. This phenomenon is indicative of what ails the pharma industry.

As I have stated in earlier blog entries, a decade ago, a tiny Israeli biotech company named Compugen predicted that Big Pharma would hit the wall in its drug discovery efforts, and undertook a long lonely effort to create discovery platforms which could accurately model biological processes at the molecular level and enable the computerized prediction and selection of therapeutic and diagnostic product candidates. Foreseeing that the era of trial and error in the world of drug discovery was yielding diminishing returns, Compugen sought to harness advanced mathematics and computer science to create the next generation of drugs addressing unmet medical needs.

Personally, I am convinced that the future development of meaningful new drugs, capable of extending life beyond a few months, will demand both an understanding of biological processes at the molecular level and the ability to intervene knowledgeably in these processes. Moreover, I also believe that Compugen is now demonstrating that this can be done.

Given the proof that Compugen has recently offered with respect to its ability to predict in silico (by computer) significant new therapeutic candidates addressing unmet medical needs (see, for example: http://www.cgen.com/Content.aspx?Page=press_releases&NewsId=571), I think that the NIH, Big Pharma and charitable organizations raising funds to support medical research need to reassess current research methodology and to learn from Compugen's pioneering efforts.

[As noted in prior blog entries, I am a Compugen shareholder, this blog entry is not a recommendation to buy or sell Compugen shares, and in September 2009 I began work as a part-time external consultant to Compugen. The opinions expressed herein are mine and are based on publicly available information. This blog entry has not been authorized or approved by Compugen.]