Science and Law
28th May 2014

Why “Big Data” May be the Holy Grail for Pharmaceutical and Medical Device Litigation

It once was a simple matter to track ADRs and AERs, but with the advent of online adverse event reporting using social media that has changed dramatically. A recent paper demonstrated that the same types of adverse events were being reported on Twitter and through the official AERS system.

Why “Big Data” May be the Holy Grail for Pharmaceutical and Medical Device Litigation

As we have discussed in previous posts, adverse drug reactions (ADRs) and FDA adverse event reporting system (AERs) are a critical part of many drug and device legal cases (see our Drug Safety eBook for a summary of our commentary on this topic).

Adverse Event Reports Are Proliferating on Social Media

It once was a simple matter to track ADRs and AERs, but with the advent of online adverse event reporting using social media that has changed dramatically. A recent paper demonstrated that the same types of adverse events were being reported on Twitter and through the official AERS system. The following figure from the paper demonstrates the strikingly high correlation between AEs in the FDA Adverse Event Reporting System and Proto-AEs on Twitter.

Even more important (and relevant to attorneys litigating drug and device cases), there were nearly three times the number of AEs reported on Twitter compared to AERS. Although at some level this is not surprising, it is a stunning revelation.

The authors of this report highlight other factors that should be highly relevant to attorneys litigating drug and device cases, including the fact that approximately 25% of Facebook profiles and 90% of Twitter feeds are fully public as well as a broad range of other health-focused forums.

Monitoring Social Media For Adverse Events Is Critical

Other investigators have demonstrated that there is high quality AE data being generated by online social networks at extremely low cost. Further, the authors of these reports expect that health agencies and product manufacturers are paying attention to their reports as indicated by their use of hashtags (e.g., #FDA, #Pfizer, #GSK).

These data highlight the fact that should now be obvious as the use of social media skyrockets – monitoring the official sources of adverse events is no longer sufficient to predict what an attorney might face in the courtroom. Developing a keen awareness of adverse event reporting from all online sources will be critical to defending these products in the courtroom.

And yet there are over 400 million daily Twitter posts per day. How can any product manufacturer hope to have a sense of what is occurring in this vast data universe?

What is a Big Data Approach?

Hiring a college graduate to sit and review social media posts is no longer a viable strategy. The only way to efficiently and effectively find signals in the tremendous volume of social data is through a Big Data approach.

For the sake of simplicity, a big data platform is like a high-speed blender (think Nutribullet). In less than one minute it can take a large mix of raw ingredients and turn it into something palatable that can be digested and used by the body quickly. In the same way, a big data platform is trained to seek out information from multiple sources (we call them “data streams”) and to process and make relevant connections across all of these sources. For example, a big data platform can be trained to recognize what an “adverse event” is, where it may have come from, and the characteristics of the individual who reported it. The system can then be fed data from different social media streams and compile complex information that could never be compiled using human review techniques.

A Big Data approach is a way of making sense of large volumes of different types of data. Big Data allows corporate and research organizations to do things not previously possible in an economically feasible way. And the information is analyzed almost instantaneously, one of the key values of a big data approach – we call it “speed to intelligence.”

How Can Big Data Help Drug and Device Lawyers?

Effective litigators are never surprised. Imagine you are cross-examining an opposing expert witness who alleges that your clients’ pharmaceutical product is associated with numbers or patterns of adverse events. He refers to fancy charts and graphs that were generated from data aggregated from social media sources: Twitter feeds, Facebook accounts, online bulletin boards. How can you hope to effectively confront this information unless you were aware of it? Unless you and your expert team had pulled together all of this information before-hand and combed through it.

Product manufacturers and regulatory agencies are actively utilizing big data approaches to identify new safety concerns. Staying ahead of emerging information means you can react more quickly and maintain a competitive edge. The potential applications are as vast as the questions that could be asked.

  • Which drugs in the portfolio are raising concern?
  • Are adverse events for your product being reported on social media more frequently than on AERS?
  • Where in the world are adverse events most frequently reported?
  • Are potential safety issues relegated to a small subgroup of the population?
  • Are there gaps in compliance with FDA reporting requirements and non-adherence to best practices in post-market vigilance?

Someone is going to find out first – will it be you?

This post was drafted by David H. Schwartz, a principle at Innovative Science Solutions, and April Zambelli-Weiner, PhD, MPH who provides expertise to ISS in epidemiology, biostatistics and advanced analytics.  Dr. Zambelli-Weiner has provided consultation and analytic solutions to corporations and counsel for over 15 years including innovative analytic approaches to challenges facing the country’s largest corporations in the drug, device and consumer product markets.   Dr. Zambelli-Weiner is the President and CEO of TTI, an international research and consulting firm providing top tier solutions for a diverse clientele including the Federal government and private organizations.

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