A Closer Look at a New Yale Pathology Outreach Venture
Posted Aug 16 2012 12:00am
I have been noticing a trend in the evolution of lab outreach among academic pathology departments and some large hospital-based labs. They are moving away from, or adding to, traditional outreach activities and rolling out tumor genomic profiling labs. These enterprises are often established in collaboration with for-profit genomics labs. Here's an excerpt about what's going on at Yale (see: A Diagnostics Startup Relies On Yale Professors ):
Four pathologists on the staff of Yale's medical school analyze cancer test results for Precipio Diagnostics , a New Haven company that was founded less than a year ago. These doctors, unlike at giant competitors such as LabCorp, are not employees of the startup, but they are its reason for being. "The competitive advantage that we have is that the larger labs aren't able to attract the caliber of pathologists we have at Yale," founder Ilan Danieli said. Danieli struck a deal with the Yale School of Medicine pathology department, under which the school is paid by Precipio for each case the doctors examine. Some of the lab's appeal is access to personalized medicine — its sales people send approximately 25 percent of the samples to Yale's tumor profiling lab, and some of the tests run in Precipio's lab also use DNA to determine which treatments would be most effective. But Yale's reputation is a selling point even where there is no possibility of personalized medicine....Danieli founded the company after running a New Jersey diagnostics lab for about a year. He had been hired there as a turnaround specialist, and, after discussing the idea of starting a lab from scratch, several of that lab's leaders joined him to launch Precipio. His background was in finance, and he said it's a challenge to lead a science-based company.
I have been thinking that we need a new name for this type of outreach with a focus on tumor profiling. Thin sections of tumor biopsies are submitted to the lab to determine its genetic makeup. On this basis, therapy is selected for the patient to take advantage of the tumor's genetic weaknesses. By the way, many tumors change their genetic profile over time so this process often needs to be repeated if and when current therapy ceases to be effective (see: One Tumor Biopsy May Be Insufficient to Reveal Genetic Landscape ).
As to a new name for this type of lab outreach on steroids, I am leaning toward "precision medicine lab outreach" (PMLO). The term precision medicine seems to be taking hold as a substitute for the previous, imprecise term personalized medicine. Precision medicine is defined in the following way (see: Improving Diagnosis Through Precision Medicine ):
[A National Academy of Science; NAS] report calls for "precision medicine," — the use of genomic, epigenomic, exposure, and other data to define individual patterns of disease, potentially leading to better individual treatment. If this sounds like personalized medicine, it is — but more so. With the over-use of 'personalized medicine' in a wide variety of contexts, "precision medicine" conveys a more accurate image of diagnosis that is person-centered and multifaceted.
This same NAS report goes on to describe the roadmap to personalized medicine:
The NAS report calls for development of a knowledge management system, or information commons, similar to the geographical information system used for applications like Google Maps. This multi-layered system would collect a broad range of health data through a vast information network...integrated into our current health care settings. Rather than considering research efforts as separate from health care, the report suggests we collect standardized molecular, exposure, and clinical data useful for research as part of routine health care. The individual patterns emerging from this multi-layered health data could define diagnosis just as multi-layered geographical data can define position. The long-term vision builds on information technology to provide new maps that guide patients and clinicians.
This new collaboration between Yale and Precipio is only one example of the development of laboratory and IT resources that will ultimately serve as nodes on this national diagnostic information network. This network will drive an extra-hospital IT strategy for labs that will differ greatly from the current intra-hospital EMR installation strategy that is in vogue. I will extend this idea soon in another note.