"Irresistible" Data: How Big Data Holds The Keys To Clinical Trial Innovation

By Anna Rose Welch, Editorial & Community Director, Advancing RNA

As clinical trials accrue more actionable data, it is becoming increasingly important to manage that data efficiently to keep the clinical research industry moving forward.           

Clinical Leader turned to PRA Health Sciences’ Mary Mattes, Executive Director Clinical Informatics Delivery, to learn more about the challenges of data management, the emergence of Big Data, and the impact all this data will have on the clinical landscape.

Anna Rose Welch: What are some of the challenges of managing the growing wealth of data in the clinical space?           

Mary Mattes, Executive Director, Clinical Informatics Delivery, PRA Health Sciences

Mattes: There are several key challenges in managing data effectively today. These include ensuring the accessibility of data; compiling the data in a useable way; providing visibility into that data; and, most importantly, defining how to interact with the data and determining what conclusions can be drawn from the output.           

However, one of the most consistent challenges in today’s data management environment is the timely generation of clean and complete patient data during a clinical trial. With so much technology and automation driving clinical data generation, it is logical to expect that we should be able to access and evaluate clean patient data sooner and more readily than in the past. However, the sheer number of data sources has increased the complexity of standardization and synchronization of data throughout the capture and cleaning cycle, making data management inherently more challenging.

What needs to be done to make this capture and cleaning cycle more efficient?

Mattes: For one, it is important to identify the data generation and processing time frames from different sources and build a standards backbone so incoming data can be rapidly melded into the broader structure of the data set. It is also necessary that the expectations of those team members relying on the data are coalesced and aligned with what data can and should be delivered by the necessary time points throughout a trial.

What are some other ways to effectively manage data, despite all the challenges you mentioned above?           

Mattes: At PRA specifically, we found it necessary to increase the specialization of the staff so that there are distinct groups that focus on a type of data or data capture system within the vast variety of these in clinical research.

Overall, it is really important to define what data is present and what are already known as key analysis measures of that data. However, there also must be a way to interact with the data in an open-ended fashion so that new ideas or unexpected trends can be identified. To help with this, reporting systems should be put in place to enable those questions to be asked and resolved within the data set. It is all about getting the disparate sources talking to each other and from that, producing a harmonized body of data.

How does all of your work with this data end up affecting your partnerships? What overall role does Big Data play in your partnerships?

Mattes: The Big Data we use today has helped us enhance partnerships with our sponsors. These large sources of medical informatics data are there to take advantage of and can guide the definition and execution of trials. We are able to identify the systems and data collection strategies most likely to succeed in the targeted research area through the use of trial information we have compiled, as well as information from the other vendors we partner with in the delivery of clinical research. We have found too, that the principles of Big Data can help facilitate and refine identification of trends and signal detection. They can also be used to optimize future study design.           

Overall, as the clinical research industry continues to define standards for data, and as the accessibility of electronically generated information increases, successful partnerships between companies will be defined by their agility in using Big Data.

What impact do you feel Big Data has/will have on innovation in the clinical space?

Mattes: Big Data definitely opens up the canvas for innovation in the clinical space. The pharmaceutical industry may be more cautious about implementing technology and Big Data practices than other verticals, but it simply can’t resist the insights large compilations of data can provide. The heart of our industry is using scientific data to improve the lives of patients, and our vertical is made up of people who love and appreciate the value of data.           

We are steadily becoming more adept at bringing together large volumes of clinical data and applying powerful querying and analysis tools needed to turn that data into ideas, decisions, or actions, and it is because of this we are already benefiting from more precise trial design and execution. For example, we are now able to use compiled historical trial data to predict possible adverse reactions to a new compound or to better identify the location of target patient populations to speed enrollment of a trial and reduce non-productive trial spend.

With Big Data, the body of knowledge compiled about a drug, a device, or a disease state can be strategically grown within the time and money constraints to maximize success. The desire to use vast samples of scientific data to spark new ideas and make positive impacts in research is irresistible to this industry, and the innovation has only just begun.