Information systems used by biomedical researchers and healthcare providers need to be modernised and re-oriented to drive more accurate classification of disease and a shift towards ‘precision medicine’, a new report argues.

A new data network that integrates emerging molecular research with clinical data on individual patients could lead to a “new taxonomy” that would define diseases by their underlying molecular causes and other factors as well as traditional physical signs and symptoms, suggests the report from the US National Research Council (NRC).  

At the same time, this “knowledge network of disease” would enable scientists to access patients’ information during treatment (without trespassing on their rights), allowing for “the marriage of molecular research and clinical data at the point of care, as opposed to research information continuing to reside primarily in academia”, the NRC says.  

As things stand, there is a “disconnect” between “the wealth of scientific advances in research and the incorporation of this information into the clinic”, commented Susan Desmond-Hellmann, chancellor of the University of California, San Francisco and co-chair of the NRC’s Committee on the Framework for Developing a News Taxomony of Disease, which put together the report sponsored by the US National Institutes of Health.  

Trickle down

Often it takes years for biomedical research information to trickle down to doctors and patients. In the meantime healthcare expenditure is wasted on “treatments that are only effective in specific subgroups,” Desmond-Hellmann added.

Moreover, researchers do not have access to comprehensive and timely information from the clinic, so “opportunities are being missed to understand, diagnose, and treat diseases more precisely, and to better inform healthcare decisions”.  

Typically, disease taxonomy refers to the International Classification of Diseases (ICD), a system established more than 100 years ago that is used to track and diagnose disease and to determine reimbursement for care, the NRC notes.

Under the ICD, though, disease classifications are primarily based on signs and symptoms. They rarely incorporate rapidly emerging molecular data, incidental patient characteristics or socio-environmental influences on disease.

The first stage in developing a knowledge network of disease, the committee suggested, would be to create an “information commons” linking layers of molecular data, medical histories and health outcomes to individual patients.  

The second stage would involve constructing the network and data-mining the information commons to highlight interconnectivity of the data and to integrate them with evolving research.  

“Fundamentally, data would be continuously deposited by the research community and extracted directly from the medical records of participating patients,” the NRC explains.

To acquire information for the knowledge network, the committee recommended:

-     designing strategies to collect and integrate disease-relevant information;

-     implementing pilot studies to assess the feasibility of integrating molecular parameters with medical histories in the ordinary course of care; and

-     gradually eliminating institutional, cultural and regulatory barriers to widespread sharing of individuals’ molecular profiles and health histories, while continuing to protect patients’ rights.  

Much of the initial work needed to develop the information commons should take the form of observational studies, which would collect molecular and other patient data during treatment, the NRC said.  

Having this access at point of care could reduce the cost of research, make scientific advances relevant to real-life medicine, and facilitate the use of electronic health records, it believes.