When Roche bought Genentech last month, speculation was rife about where the newly enriched leadership of this biotech behemoth would end up. For president of product development Susan Desmond-Hellmann, it didn’t take long to settle the issue.
Last Friday, Mark Yudof, president of the University of California, announced that Desmond-Hellmann is his nominee for the chancellor of UC San Francisco–subject to approval by the UC Board of Regents. Her arrival could mean a substantial boost for personalized medicine–the tailoring of treatments and diagnostic tests according to an individual patient’s genes and physiology. She oversaw the development of Herceptin, the Genentech blockbuster to treat breast cancer that only works for patients who overexpress a gene called HER2. She also oversaw the development of the blockbusters Rituxin and Avastin.
Unfortunately, other examples of truly personalized medicine have been scarce in the drug industry, despite an explosion of research data produced by molecular biologists in recent years. Most of this data, however, has not been translated into either new drugs or diagnostics. Many reasons are given, including the complexity of the science and a research infrastructure that still values discovery more than the development and application of those discoveries.
Efforts are under way at the National Institutes of Health and at some universities to develop new and better methods to shift basic research in genetics, proteomics, and other fields into useful products and protocols, but no national leader has emerged to spearhead the effort.
Desmond-Hellmann has not yet revealed her plans or focus should she be approved as chancellor of UCSF, but she is uniquely poised to perhaps take on this role as a bridge between research and development.
Hopefully, she will keep the two in proper balance, remembering her first career as a full-time oncologist who joined pharma out of frustration at being able to do so little for her patients.
The big new idea for making self-driving cars that can go anywhere
The mainstream approach to driverless cars is slow and difficult. These startups think going all-in on AI will get there faster.
Inside Charm Industrial’s big bet on corn stalks for carbon removal
The startup used plant matter and bio-oil to sequester thousands of tons of carbon. The question now is how reliable, scalable, and economical this approach will prove.
The hype around DeepMind’s new AI model misses what’s actually cool about it
Some worry that the chatter about these tools is doing the whole field a disservice.
The dark secret behind those cute AI-generated animal images
Google Brain has revealed its own image-making AI, called Imagen. But don't expect to see anything that isn't wholesome.
Get the latest updates from
MIT Technology Review
Discover special offers, top stories, upcoming events, and more.