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Missing: Adequate Enterprise IT for Translational Medicine

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Translational medicine links together life science discovery and healthcare organizations to speed discoveries from, as the saying goes, bench to bedside. From an IT perspective, discovery and clinical organizations have something in common — in general, they have both been slow to adopt enterprise-scale information systems. That's not the best situation when you are trying to integrate across these organizations.

Translational medicine has the potential to fuel the advance of genetic- and genomic-based personalized medicine by enabling physicians to leverage genetics and genomics to substantially improve patient care. However, this requires information to flow from discovery-based organizations to clinical organizations in an organized, structured format. Getting information to flow effectively within these organizations is a prerequisite to getting the information to flow between organizations.

Sure, there are many solutions out there that serve the needs of particular departments or particular functions. The problem is that most organizations have not made the substantial IT investments required to weave these solutions together into a unified enterprise IT infrastructure.

The manufacturing and financial service industries began to roll out serious enterprise IT more than a decade ago, but here in the biomedical realm we still find ourselves in a world where the vast majority of physicians do not have access to any kind of electronic medical record (EMR) system, let alone a truly robust one. Over on the life sciences side, organizations often have multiple, non-integrated laboratory information management systems (LIMS). You can argue that I'm overlooking major investments that have been made in enterprise healthcare billing systems and pharma's manufacturing systems, but if you look at the core discovery and care delivery functions, IT remains fragmented.

Building an Enterprise

The good news is that times are changing. My own organization, the Harvard Partners Center for Genetics and Genomics, has started an enterprise LIMS superstructure. This superstructure serves as an enterprise umbrella that sits over our individual LIMS, linking them together and integrating them with other systems in the enterprise environment, including results reporting systems and our EMR. We are integrating LIMS into it as quickly as we can. There are several biotech and pharmaceutical companies doing the same thing. Here at the center, we're also fortunate enough to have a robust EMR infrastructure that has been enhanced to securely handle genetic data. Other academic medical centers are also focusing on expanding their infrastructure support for genetic and genomic data. The question is, can our individual organizations — and the industry as a whole — move fast enough to ensure that the rollout of translational medicine is not constrained by inadequate IT infrastructure?

One of the key challenges for discovery organizations lies in breaking down data silos. Data relevant to an investigation may be collected in several different laboratories. If these laboratories are covered by different LIMS, it can be time-consuming to pull the information together. If the study is particularly large, it can also be difficult to track the location of all of the data that has been generated. Enterprise LIMS superstructures can help address this issue. They can also make it possible to transfer IT infrastructure to clinical users as breakthroughs occur.

On the clinical side, the challenge is making sure that patients can be tested cost effectively and that the information generated from those tests can be used optimally over time. Cost-effective testing depends on quickly establishing support for new, more efficient technologies as they are validated for clinical use. Ideally, the time required to establish LIMS support for these new technologies would not delay their introduction.

Enterprise IT can help this process in three ways. First, new technologies are usually used extensively in research before they ever see the light of day in a clinical setting. If both research and clinical environments are covered by the same enterprise IT umbrella, tested LIMS can be transitioned from research to clinical when a breakthrough occurs. Second, if a new LIMS must be constructed or purchased, an enterprise LIMS superstructure can perform many of the functions that each individual LIMS would normally have to perform. This means each LIMS becomes smaller, and therefore easier and faster to build, test, and implement. Third, the enterprise IT environment makes it easier to integrate with other systems in the enterprise environment including the EMR. This third point is critical to ensuring that test results can be optimally used.

The Clinical Environment

Genetic and genomic biomarkers are at the heart of many aspects of translational medicine. For discovery organizations, they represent potential drug targets and a means to stratify patients into groups that are more likely to benefit from a drug. For clinical organizations, they represent ways to gain a better understanding of the patient's diagnosis and prognosis. In the best case, they can also help predict which treatments a patient will respond to and how drugs should be dosed.

As genetic testing becomes more common, it will become increasingly difficult for clinicians to keep up to date on everything that has been learned about the genetic variants that have been found in their patients. This may sound like a far-off issue, but in fact, even though genetic testing is not currently widespread, this issue is already present. Our knowledge of the implications of variants is increasing, particularly on variants in stretches of DNA that have been shown to have clinical relevance and are therefore the most likely to be tested.

Clinical decision support systems could alert physicians if a decision they make is counter-indicated by a patient's genetic profile. Through these alerts and other means, these systems have the potential to help clinicians properly leverage the latest genetic information. However, these systems can only function if genetic test results are properly represented in a structured format in the EMR. Achieving this requires enterprise IT architecture, both to ensure that genetic results are transferred to the EMR and also to ensure the patient privacy and security issues are addressed consistently throughout the enterprise. It is extremely important to safeguard the privacy surrounding genetic test results, which can require substantial IT investment in authentication and authorization mechanisms as well as analysis of the clinical procedures that involve genetic data. The level of investment this requires is easier to sustain when it is focused on centralized enterprise resources.

While still small, the molecular diagnostic industry is growing rapidly as sequencing costs drop and translational medicine picks up. We have time to get ready for the large-scale adoption of these techniques — but not much time. Translational medicine may represent the killer application that many have been looking for to drive them into the mainstream. Let's hope so, because it is hard to imagine how clinicians and researchers will fully leverage translational medicine's potential without this kind of IT support.

Samuel (Sandy) Aronson is the Director of Information Technology for the Harvard Partners  Center for Genetics and Genomics.

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