Real World Data Europe

Apr 28, 2014 - Apr 29, 2014, London, England

Demonstrate the true effectiveness of your drugs to satisfy payers, HTAs and improve patient outcomes

Real World Data: Real World Opportunities

Supplementing information gathered in randomised clinical trials (RCT), optimising RCT design, and streamlining R&D are just some of the opportunities that come with big data, but successful implementation of RWD depends on breaking down data silos, and devising an optimum strategy.

According to an eyeforpharma report, almost 58% of industry professionals spend more than 20% of their working week on real world data, and nearly 80% believe this will increase in the next two years. Additionally, 32% are convinced that RWD will have a huge impact on the development of future RCT design to reduce failure of medicines in the final stage to the market.

“RWD is becoming a critical part of the evaluation of products for coverage decisions, therefore, we’re seeing an increased focus on how RWD can supplement the information gathered in RCTs,” said James Harnett, Senior Director Real World Data and Analytics, Pfizer, in an interview with eyeforpharma.

Getting more out of RCTs

You could immediately look at clinical information or claims information, and identify what is the impact of a study protocol’s exclusion/inclusion criteria on patient enrolment

Optimising RCTs may be one of the biggest opportunities across the industry in terms of RWD’s application. “You could immediately look at clinical information or claims information, and identify what is the impact of a study protocol’s exclusion/inclusion criteria on patient enrolment,” Harnett explained. Additionally, there is the opportunity to operationalise RCTs in those investigator sites where there is a significant proportion of sought after patients identified in RWD.  “In fact, a number of payer organisations are currently offering tools to facilitate this opportunity,” Harnett added.

Moreover, RWD can offer insight into broader populations and sub-populations, provide comparisons of more interventions under real world adherence conditions, and allow to evaluate outcomes of interest that may not be captured in clinical trials. This is of particular interest to the payers who are enabled to decide how a new payment model will be operating.

Another opportunity presented by RWD is in linking the RCT information with the information that is in the electronic medical records (EMR), or in claims data, to understand the broader picture of the impact of interventions on a given group of patients. “There is a lot of opportunity in linking the RWD with the clinical trial data to strengthen our ability to demonstrate the value of products and leveraging the diverse data sources for understanding heterogeneity of treatment effects,” Harnett explained.

Speeding up R&D

In terms of other exciting opportunities, RWD can support R&D by facilitating the  identification of  targets much earlier in the development process.  “With the introduction of linked clinical and genomic data, this certainly would be a tremendous opportunity,” Harnett said. But there is also leveraging to insights into  how products are being used in clinical practice today, which “might allow identification of mechanisms in common with candidate compounds still in development, helping to provide new insights into potential uses for those development  products or potential sub-populations,” Harnett elaborated.

The cutting edge of data collection

The emerging focus in data collection is on EMRs. “EMRs offer the promise of understanding the clinical picture of the patient, (something claims data cannot do), but they have their own challenges, and, like claims data, EMRs were not developed for research purposes and, therefore, often have missing information in the structured data. One way we are hoping that these gaps can be addressed is by leveraging the clinical notes –the so-called unstructured data.”

Some companies are now focusing their efforts on developing natural language processing algorithms, which, in a more automated fashion and, therefore, more anonymised way compared to manual chart reviews, are able to identify and extract information from  the clinician’s notes around specific areas of interest such as reasons for changes in treatment or clinical outcomes. “They’re building computer applications that crawl through the notes, and identify potential statements that could be relevant; these algorithms are refined before applying them to a broader dataset and create structured data for analysis. This is cutting edge, and we’re hoping that this will allow us to better leverage the full potential of EMR in an cost-effective manner.”

Breaking data silos

Data silos are partially driven by the different settings from which the data are derived. In the U.S., the Integrated Delivery Network (IDN) is more likely to have both,  inpatient and outpatient data.  However outside of an IDN it’s difficult to find strategies to centralise data, integrate it, normalise it, clean it and prepare it for research purposes. That’s where a number of payer and data organisations are now making their investments. Oftentimes it is the payers who recognise that there is an opportunity for them to better understand the health of their membership, and also to track outcomes in response to decisions that they’ve made about coverage. “This is really where I think there’s going to be a lot of players emerging to remove those silos and link data together.”

Strategies for using RWD

Companies who want to use RWD in their practice need to consider a number of strategies. First is acquiring and centralizing access to diverse, de-identified datasources in a data mart. “Rapid cycle learning is where there is potentially tremendous value through ready direct access to RWD. Integrated data sources or mash-ups are also the way to go, if feasible.” Second is developing partnerships. “We built partnerships with organisations that have different  priorities but share  RWD capabilities and research interests.” Third is to prepare to analyse your data to rapidly generate actionable insights and leverage multiple analytic approaches including traditional and emerging machine learning methods. “It’s impressive how forward-looking some of the analytical technologies are. To sum up, I think investing into your own data mart, investing in partnerships, and analytic tools are going to be the three most important steps for companies on the road to recognising the value of this data.”

RWD offers insights that RCTs alone cannot provide. An opportunity to study therapeutics under real-world adherence conditions, and to develop new drugs more quickly is already playing a part in the day-to-day functioning of the industry. As we look forward, it is likely that pharma will develop novel methods of data collection, and will work toward a uniform coding system across healthcare records that would make RWD more feasible in practice.

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Real World Data Europe

Apr 28, 2014 - Apr 29, 2014, London, England

Demonstrate the true effectiveness of your drugs to satisfy payers, HTAs and improve patient outcomes