Going MAD: Development of a “Matrix Academic Division” to Facilitate Translating Research to Personalized Medicine

Personalized medicine—deciphering disease mechanisms in individual patients to predict the effect of interventions—is an exciting futuristic concept for which few successful examples of systematic approaches and implementation exist. In this article, I describe a unique and highly effective academic program created at the University of Pittsburgh School of Medicine and the University of Pittsburgh Medical Center (UPMC) in the Division of Gastroenterology, Hepatology, and Nutrition to rapidly develop personalized medicine for digestive diseases. The program has required a paradigm shift away from traditional biomedical approaches that are based on the germ theory of communicable infectious diseases and scientific approaches designed to identifying a single factor responsible for a complex disease, as articulated in Koch’s postulates (stated in List 1). The need for this shift is predicated on the view that the current bed-to-bench-to bed process for developing effective treatments for patients with complex inflammatory diseases is comparatively inefficient, ineffective, time consuming and expensive 1,2. List 1 Koch’s Postulates* As an alternative to traditional statistical approaches to understand complex diseases, we have taken a reverse engineering approach to subdivide complex chronic inflammatory syndromes into scientific disciplines (where statistics are applied to test mechanistic models) and then integrate the findings into predictive disease models. Similar chronic inflammatory diseases in different organs (i.e., pancreas, intestine, liver) require similar scientific approaches, and for these types of diseases, detailed patient disease information and outcomes are organized in parallel. We approached this conceptually by aligning the names of the organ systems into rows and the names of the scientific disciplines into columns, which produces a grid. We reasoned that when phenotypic and biomarker information corresponding to each cell of a grid is collected on a patient, and the information from many patients are combined, it becomes a matrix. The advantage of the matrix is that it allows for highly organized patient information to be evaluated from multiple perspectives. This is invaluable for higher-level analysis of the interactions between genes, genes and environment, and disease modifiers linked to systemic processes instead of only the specialized cells of an organ. This level of information and organization is required for the development and implementation of personalized medicine for complex disorders. I developed this matrix strategy in 1999 while negotiating to become division chief based on a long-term vision of personalized medicine for complex inflammatory disease, a recognition that academic physicians and scientists need specific niches for recognition and promotion, and a conviction that an academic medical center had a responsibility to solve complex medical problems. Based on the scientific strengths of the University of Pittsburgh and the patient populations served by UPMC we proposed the recruitment of a series of faculty members who had specific disease interests and scientific expertise to fill in the cells of a grid defined by seven complex digestive disorders (rows) and seven scientific disciplines (columns). Each faculty member was to serve as a “translator” for specific types of medical problems within a complex disease and recommend data elements to be collected on patients within his or her domain. Working together, groups of faculty could provide all relevant medical and scientific perspectives on complex problems, and provide more comprehensive phenotyping of each patient. Phenotypes, genotypes and biomarkers could then be integrated into personalized predictive models designed to improve outcomes at much lower cost for each individual patient. In the rest of this article, I first review modern Western medicine, using examples to illustrate why applying methods designed to identify single factors responsible for a syndrome, as in an infection, is comparatively ineffective in resolving complex disorders, where the etiology and character of the disorder require the interaction of multiple factors. I then describe a new vision of addressing complex digestive disorders, using a matrix academic division (MAD), and conclude with an example of how our institution’s MAD approach to chronic pancreatitis is leading to the successful implementation of personalized medicine.