If David Patterson has his way, legions of computer scientists like him will rise up and join the battle against cancer. In an essay for The New York Times published Dec. 5, Patterson, a professor of computer science at the University of California-Berkeley, makes a case for why people in his field have the skills to tackle some of the major hurdles to achieving cancer treatments tailored to attack tumors based on the molecular drivers of each patients' cancer.
The computer scientist has done more on this front than write. In the spirit of getting more computer whizzes enlisted in the cancer battle, he and his colleagues at Cal have started the AMP Lab, and one of its initial efforts is to create crowd-sourcing methods to recruit people outside their lab to help solve Big Data problems such as those faced in modern cancer research. The group has also set out to develop new algorithms and tap computing resources in the cloud to tackle such problems. Fittingly, "AMP" stands for "algorithms, machines and people."
Part of the computing challenge in the cancer fight, according to Patterson, is that researchers have amassed incredible amounts of digital data on the genetics of tumors stemming from DNA sequencing methods, but there's a lack of algorithms and machines to efficiently match patients with targeted treatments. Patterson writes that "... finding a personalized, targeted therapy for each tumor among myriad possible combinations of drugs is like finding a very small needle in a very large haystack. Researchers are exploring the engagement of people when traditional hardware and software are not up to the task."
Patterson appears to be on the leading edge of his field, yet many cancer patients in this country get treatment without first getting their tumors sequenced. As Patterson points out, even though the costs of sequencing have fallen a hundredfold over the past three years, the computing required to assemble the sequencing data and analyze it hasn't shrunk as quickly. Clearly, there's lots of work for computer scientists and others to do before personalized cancer treatment becomes a reality.
- check out Patterson's NYT essay