The Future is Connected Data By Katrina Rice, Executive Vice President, Professional Services, eClinical Solutions LLC

posted on June 15th 2017 in Data Talk with 0 Comments /

In today’s electronic world, we all are benefiting from some of the advances.  I can check on my bank balances and even the status of my mortgage all within a single application.  Yet when working on clinical trials, our approach has continued to be to combine that data on the back end and analyze it in data siloes.  If we believe that the connected world we are living today in our personal lives represents a foreshadowing of the world to come to drug development, then we must consider that the future for clinical research is connected data.

Increased volumes of data from traditional sources, new sources like wearables and the future of eSource may all be leading us toward what one colleague terms “Data Deluge” if we don’t proactively plan for it.  Despite the slow uptake to data integration, some of the newer entrants to our space like Amazon, Google and even Samsung are helping drive the future of clinical research through apps, devices and other sources of information.  We are in the era of Big Data but are we taking full advantage of that opportunity?

At the end of all this, is not just data for the sake of data but the belief that having access to connected data can make us be better at what we do, and ultimately help us deliver therapies and medications to those who need them.

Consider the potential that lies in a future vision of more connected data.  Can we easily integrate future data sources that add insight beyond simply what is collected in the investigator visit?  How much would our understanding of the treatment increase with additional sources of data?  Could we increase the criteria for allowing patients into trials – for example genetic information – and target specific populations and thereby potentially enabling smaller, shorter, less expensive but ultimately more powerful trials?  Can we continue to collect information in real world settings to assess the effects of a drug or device with minimal impact to patients and investigators?  Could we leverage the diversity of available molecular and clinical data, and use predictive modeling could help identify new potential-candidate molecules with a high probability of being successfully developed into drugs that act on biological targets safely and effectively?

As we reflect on the power of connected data for our future, what holds us back?  We have some very real issues to work through such as how to implement best practices to assure the privacy of patients involved in clinical trials that are particularly of concern with the adoption of mHealth.  But there are also very practical issues that prevent us from moving forward.  How many leaders struggling with current workload can willingly undertake a major overhaul without a short term hit to performance. At the end of the day, we all must deliver on our current projects and this short term, heads down state we exist in often not conducive to a systems overhaul.

Formerly connecting data mean exactly that – bringing in a consultant to review, recommend and often rebuild large scale systems.  But today’s cloud based environment has helped to spur the development of solutions that can sit on top of existing systems and provide means of integrating your data without having to completely overhaul your existing infrastructure and the investment and training in the systems you already have.


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