Improving Data Liquidity in Clinical Research

Empowering Patients and Doctors

In my last post, I wrote about the need for data liquidity in clinical research – and the need for biopharmaceutical companies and healthcare institutions to take the lead by freeing up data about their studies, clinical trials and drugs.

To accelerate clinical research efforts for diseases like cancer, we need two things.  First, stakeholder institutions (like biopharmaceutical companies and healthcare institutions) need to free up their data.  Second, we need new systems and software that can share and manage that data – securely and at scale – across our complex healthcare ecosystem. 

Start-ups are being formed every day that are pushing the envelope on applications and technologies that take advantage of health care data liquidity. In Boston/Cambridge alone, we have three start-up incubators dedicated to health information technologies, each with 10+ start-ups.  That’s more than 30 top-tier, vetted start-ups focused on health information technologies being developed at any given point and time. For example, check out:

Pharma companies have long been proponents of “free your data”  as long as it means freeing data from patients, from claims clearinghouses, from pharmacies and so on.  Pharma companies have been less enthusiastic about freeing their own data, about their studies, clinical trials and drugs.  But the logjam is starting to break.

As I mentioned in my previous post, recently GlaxoSmithKline (GSK) publicly announced it would make detailed data from clinical trials available to researchers.  The company’s detailed patient data (data that forms the basis of trials of approved drugs as well as discontinued investigational drugs) would be made accessible to researchers.  Researchers’ requests for access will be reviewed by an independent panel of experts, and the patient data will be anonymous.  

Last year, one of the large biopharmaceutical companies  in collaboration with the electronic health record company Cerner  began an initiative to build an open interface that will enable sponsors of clinical research studies such as Novartis, Genentech, GSK or Pfizer to publish inclusion/exclusion criteria about their clinical studies to specific clinical partners – in much greater detail than what’s available on the National Institutes of Health‘s today.  

The goal of this project is to create a electronic mechanism to ensure that all eligible patients are identified for appropriate studies via their doctors.  This mechanism would be able  without changing any data privacy – to flag patients’ records when they are diagnosed or when new studies or updates to studies become available; and to dynamically notify doctors and match patients with new or evolving studies based on patients’ clinical profiles and the inclusion/exclusion criteria of the trial.

Under this new electronic standard for study information, study eligibility criteria are expressed in a standardized, machine-readable format. Any EHR system can ingest the study data automatically as new studies are created and as existing studies change.  With this more-liquid data, providers can then match the inclusion/exclusion criteria against the health records in their systems.

A provider configures its systems to flag records of potentially qualifying patients using a form of research-study-recommendation engine. The provider runs and tunes this engine so that the next time a clinician pulls up a patient’s health record (or the patient’s health record changes), the EHR system will suggest to the doctor that his patient may qualify for a clinical trial – both local and not-so-local trials (think truly global patient recruitment with little or no extra effort). 

In addition, when a new trial is published, doctors with patients can be notified that there is a new trial of possible interest and eligibility for specific patients.

Through this type of simple standard for study information exchange – one that empowers doctors and is run by providers – doctors and patients could be automatically made aware of trials regardless of where the study is being run or when a new study starts.

Using this simple standard, Cerner has worked with various large biopharmaceutical companies to build and test end-to-end Proofs of Concept   in the process successfully demonstrating that this approach can work very well with relatively little extra effort on the part of the study sponsors, the providers or the biopharmaceutical companies.   There is no additional risk of information privacy, since these criteria have been published previously to the providers, and the patient data does not have to be shared at all. The standard just enables getting better data on studies to providers in a more targeted way.

In short, starting to improve liquidity of clinical research data just requires leadership from pharma companies and cooperation from health care providers to prime the pump and adopt  standards – and perhaps the encouragement of trusted brokers such as LIVESTRONG to bring the parties together. 

Increasing the liquidity of data in ways like this could improve enrollment in studies, especially for rare diseases with small patient populations. Doctors and patients would have a proactive monitoring system that reminds them about all relevant research studies – especially new studies in rare indications – regardless of geography or the distractions in their daily lives.

This blog post came out of a presentation that I recently delivered at Rev Forum, a conference sponsored by Lance Armstrong’s LIVESTRONG Foundation and Genentech. I have worked with LIVESTRONG and various biopharmaceutical companies on new health care information products and apps that take advantage of data liquidity to help patients combat cancer and other difficult diseases.


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1 Response to Improving Data Liquidity in Clinical Research

  1. Pingback: Project FDA: Bringing the FDA into the 21st Century |

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