Immuneering, Led by Young CEO and Mentor, Aims to Pick Which Cancer Drugs Should Work
Cancer drugs are notorious for offering slim odds of helping patients live longer, while guaranteeing they’ll suffer some unhappy side effects. Lots of scientists are searching for clues in the genome for how to select people most likely to benefit from a drug, while sparing everyone else. Boston-based Immuneering thinks there’s a better place to look—the immune system.
Immuneering popped on my radar at last week’s XSITE event at Boston University, where I met CEO and founder Ben Zeskind. He’s 27, with a list of accomplishments that puts him in boy wonder territory. He’s got a bachelor’s in electrical engineering and computer science from MIT, a Ph.D in bioengineering from the Whitehead Institute, and an MBA from Harvard Business School. Zeskind didn’t tell me about his background, but got my attention when he said he’s recruited Bob Carpenter to be his chairman and mentor. Carpenter is 64, a 30-year biotech entrepreneur who once sold a company to Genzyme (NASDAQ: GENZ) for $1 billion, and since then has spent 15 years on the Cambridge, MA-based biotech giant’s board of directors.
This mentor-and-protege team has its sights on making a fundamental change in cancer treatment. Immuneering wants to take blood and tumor biopsy samples, look at whether the patient has immune cells with the right characteristics to produce a powerful, long-lasting immune response against tumors, and run those readouts through a proprietary mathematical model to predict the odds that a patient will respond to a drug. This fundamental understanding should also offer suggestions for how to boost the odds of success, explain why some drugs work for individuals and not others, and do it for virtually every type of cancer with a few tweaks to the model, Carpenter says.
Since the global market for cancer drugs was worth $66 billion in 2008, and is expected to grow to $84 billion by 2012, governments and health insurers are going to continue putting a lot of pressure on drugmakers to justify all that cost, largely through tools that can predict … Next Page »