Dr. Isaac S Kohane

HST Affiliated Faculty
Chair of the Department of Biomedical Informatics
Chair, Informatics Program
Lawrence J Henderson Professor of Pediatrics and Health Sciences and Technology

Primary DLC

Harvard-MIT Program in Health Sciences and Technology

MIT Room: CHLDRN_HOS-END624

Areas of Interest and Expertise

Computational Biology
Microarrays, Robustness, Noise and Reproducibility
Human Variation, Evolutionary History and Consequences
Gene Regulation and Reverse Engineering of Genetic Networks

Research Summary

One hundred years ago, the Flexner report provided damning evidence of the sad state of the medical education system, and its implications for the quality of care provided and the lack of quality in biomedical research. Following the publication of that report, half of the medical schools in the US closed. We may be at a similarly pregnant moment in our medical education, medical research, and medical care system. Over the past 30 years, I have focused on twin tracks of research applied to biomedical discovery and clinical care to address this growing challenge. A synthesis of these tracks can be found in our approach to using healthcare systems as translational research engines that generate genomic-scale knowledge in the routine course of clinical care. This same toolkit, adopted by over 50 academic health centers worldwide and a growing number of commercial organizations, has also allowed studies of drug safety, and quality of care. Along with several colleagues I have developed a system—The Informed Cohort—that makes patients partners in discovery, personally benefiting from breakthrough research while preserving privacy, autonomy, and yet maintaining the role of healthcare providers in filtering the potentially harmful noise inherent in genomic and other biomedical discovery enterprises. Our vision is to make every patient encounter an opportunity for all of biomedicine to progress—alas not the usual modus operandi of medical care.

Biomedical Discovery -- It is perhaps in the nature of the bioinformatics discipline that we tend to adopt the macrobiological perspective where systematic mechanisms underlying observed biological processes and diseases are of greater interest rather than ascribing mechanistic primacy to individual genes, gene mutations, or organs. I have found the macrobiological perspective particulary effective as applied to reclassifying disease, and in particular in investigating the processes of development and how they run askew in particular diseases such as cancer. Remarkably, this comprehensive, quantitative approach has served to rediscover, at the molecular scale the observations of more than a century ago of Virchow, Cohnheim and other luminaries of the 19th century. In this spirit, we are now investigating how far the macrobiological perspective will take us in understanding autism spectrum disorder (ASD). That is, to study the molecular and cellular perturbations that cut across classically conceived neurophysiological, developmental and immunological mechanisms.

Clinical Care -- Why is it easier to find out what experience shoppers worldwide have had with the latest digital camera than it is to determine what adverse events patients have had with a particular drug? Why are blood tests and X-rays repeated needlessly? Why can one replace an application on an iPhone with a mouse click and require a team of engineers to do it for an electronic health record system? Mirroring the systems approach taken in biology,we have attempted to answer (through design and implementation) these questions including the pioneering of personal health record systems, distributed clinical query systems, and privacy protection mechanisms and policies. Most recently, we have focused on how to re-engineer electronic health record systems so that they are as easy to manage and customize as other complex but consumer facing systems (e.g. the iPhone) which fundamentally support our notion of substitutability.

Recent Work