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Real World Evidence (RWE): Predictive Analytics to Impact Patient Safety

February 23, 2018 by Ale Vazquez-Gragg, MD Leave a Comment

Real World Evidence and SafetyThe use of new analytical tools applied to large, diverse, complex data sets, so called “big data”, the development of devices to track and gather real-time healthcare data and information and the use of digital media are on the increase in the healthcare environment and have the potential to be of great value if harnessed and utilized appropriately.

The current main system for keeping track of dangerous side effects of prescription drugs is deeply flawed according to the Institute for Safe Medications Practices (ISMP). The study conducted by the ISMP found that only about half of reports of serious side effects submitted by manufacturers met basic standards for completeness.

No longer just a sideline used to fill knowledge gaps, the evidence generated from real-world data (RWD) is rapidly becoming an integral component of product evidence strategies. However, the growing volumes and heterogeneity of real-world data sources are creating increasingly inefficient and chaotic analytic environments and as a result, new approaches for database analyses are needed.

Real-world evidence (RWE) allows companies to make more informed and reliable strategic decisions earlier when it comes to protect patient safety. Another value added is converting RWD into valuable RWE that offers great scientific and patient benefit trials as well as shortening phase III to accelerate the approval procedures. These benefits include improving the ability to positively impact patient outcomes through understanding of disease characteristics and treatment patterns, enhancing medicines compliance and aiding in interpreting treatment outcomes for individual patients. It also enables organizations to demonstrate health outcomes and support the case for the value of their products to health authorities, payers, health care providers and patients.

The opportunity to use these technologies and derive their potential benefits to assess the efficacy and effectiveness of therapeutic options is in its infancy. Although they could be the key to establishing a credible new generation of fit-for-purpose RWE, pharmaceutical companies have been cautiously investigating the use of the various technologies that contribute to big data collection (e.g., social media, electronic health records, insurance data claim databases) and the application of analytics to these data sets including pharmacovigilance to assess side effects. The case for accessing and evaluating the plethora of different data sets is clear. However, while the opportunity is large, exploiting the value requires the appropriate governance, knowledge and analytics capabilities to stay within the acceptable tolerance levels for compliance and reputation risk management. Pharmacovigilance departments will become a key element within the organizations.

Questions have been raised as to how best to deploy innovative collection and analytic technologies to maximize their effectiveness. Approaches such as the Advancing Medical Innovation initiative encourage the FDA to identify opportunities to use big data to streamline and support pre- and post-approval activities. In Europe, collaborative projects in the area of post-authorization efficacy studies have identified the need for companies and agencies to be able to measure safety and effectiveness in the real-world use of new medicines.

This is mirrored by the need for pharmaceutical and biotech companies to quickly adapt their pharmacovigilance departments into cross-functional teams to strategically make decisions regarding how new medicines will be used in the real world and to confirm the expected benefit and value, often derived largely from controlled clinical studies. In a rapidly changing regulatory environment, with a diverse set of data sources, contractual mechanisms and data privacy requirements, the capabilities needed to extract the value from the data become strategic in their own right.

Over the last years the potential of real-world data and analytics has been discussed as opportunities to enhance patient engagement, reduce uncertainty in the development and approval space, as well to serve as a natural process for the collection of benefit and risk data post-authorization. Collecting data from a mix of evidentiary experiences would support novel flexible regulatory pathways that accelerate reviews and access to medicines, and therefore, will likely play a key role in transforming medicine development and access over the next decade.

Are we ready for this?

Ale Vazquez-Gragg, MD
Ale Vazquez-Gragg, MD

Ale is the VP, Head Global Patient Safety at Intarcia Therapeutics, Inc.

Related posts:

  1. Artificial Intelligence in pharmacovigilance? What a challenge!
  2. Pharmacovigilance Audits/Inspections and PV Analytics!
Related Terms:
  • Term: Big Data

Filed Under: Opinion

About Ale Vazquez-Gragg, MD

Ale is the VP, Head Global Patient Safety at Intarcia Therapeutics, Inc.

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