The power of real-world patient data

Real-world data has the potential to vastly improve the effectiveness and efficiency of the drug development pipeline, advises Aiden Flynn, CEO of clinical trial data and design experts, Exploristics

To unlock its transformative promise, there must be new approaches to organising non-clinical health records. Here, Aiden discusses the potential of real-world patient data in clinical development and how it can be properly collected and utilised.

Beyond RCTs

There is currently a large disconnect between data recording in the highly structured approach of randomised clinical trials (RCT) and the highly varied and sometimes ad hoc approach to data collection in everyday medical practice settings. Both environments provide valuable data regarding the safety and efficacy of a drug during different time periods and patient groups, yet only the former is standardised and well-established.

RCTs satisfy regulators and ensure that a drug is marketable, but they fail to provide information post-authorisation on a drug’s long-term performance. This kind of information could be a valuable asset to researchers and should arguably be collected in a much more structured way to address the gulf between the information garnered at RCT stage and what currently happens beyond this.

Phase IV

Phase IV studies exist to track the effectiveness of medicines in the general population and gather information about adverse events associated with use across the board. But they are not yet comprehensive enough to fully harness real-world data and provide a full picture.

The European Medicines Agency’s 2015 directive does recognise the importance of optimising the safe use of marketed medicines using post-authorisation information via Phase IV studies. The evolving regulatory environment enables the use of electronic health records (EHRs) and encourages the development of new analytics approaches, capabilities and infrastructure.

Aiden Flynn

New practices are being used by healthcare delivery organisations to create better quality Phase IV data. Care providers are developing Learning Healthcare Systems that include an in-built ability to use data and feed it back to innovators. These practices are helping to increase the value of Phase IV studies and improve the next generation of research.

Pharmaceutical companies are also progressing how they use real-world data, shifting from an acute focus on safety and commercial considerations to using data across the end-to-end product lifecycle to support regulatory decisions, enhance disease understanding and aid outcome-based reimbursement decisions.

Challenges

As the regulatory and commercial environment increasingly embrace real-world data, many issues are still associated with its delivery. There are no steadfast methods and protocols for real-world data collection — leading to great disparity in the information that goes into records — which proves challenging when trying to attain reliable information.

To aid the extraction of meaningful data, data sources must be suitably aligned. The increasing use of electronic data collection (EDC) is likely to improve information quality, but stakeholders still need to understand the basic steps that can be taken to facilitate the analysis of real-world data. It is important to prepare and clean data of any potential bias, using statistical modelling approaches to control variability in the data.

Without a quality control check, false conclusions and misinterpretations of the data may be drawn. Additionally, an analysis of the real-world data needs to be conducted to identify any gaps in the exiting data. Following the analysis, steps that will help to improve the interpretability of the data will be determined.

A clear understanding on the effectiveness of new treatments in real-life settings during a lengthy period is needed to better inform the next generation of clinical research. Using the sources available to identify different ways to harness real-world data can improve the development of new medicines and complement evidence gained via traditional RCTs to fully understand new medicines and targeted diseases.

All stakeholders involved in the development and use of medicines are set to benefit from the industry’s move towards the greater liberation of patient data.

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