In describing what happens in clinical practice and beyond the doctor’s office, real world evidence gets to the core issue of patient-centered development.
As yet however, there is little agreement on what constitutes real world evidence, how and what data should be collected and how it should then be marshalled and analysed in support of personalized medicine and new health models.
In addition to these practical considerations there are other barriers – a lack of consensus, lack of standardization of real world research methodologies, the brick wall of data protection legislation, scepticism about the whole enterprise and cultural hurdles in implementation.
Sarah Garner, Associate Director Science Policy and Research, National Institute for Health and Clinical Excellence (NICE), described a number of projects in which she is involved that are seeking to address some of these issues and lay a foundation for real world evidence to be used in practice, creating a bridge between efficacy in clinical trials and effectiveness in clinical practice.
Such work, “Puts a regulatory focus on efficacy downstream [of approval], on what happens in patients like me,” Dr Garner told the conference.
So for example, the IMI 2 Adapt Smart project aims to establish a platform for MAPPs to be implemented in Europe. The project, which involves more than 30 participants, is investigating tools and methodologies, engaging all relevant stakeholders to develop concepts that will make MAPPs work in practice.
The research will allow MAPPs-related activities to be coordinated across IMI as a whole.
Meanwhile, another project underpinning MAPPs, GetReal, is looking at how to develop a decision-making framework to assist in designing trials that capture real world evidence during clinical development, providing insights into how effective a drug is likely to be in clinical practice.
For Dr Garner, MAPPs is about taking the existing rigid “fixed price menu” approach to drug development and reconfiguring it to introduce flexibility and increase relevance. Real world evidence sits at the heart of this effort. Amongst the challenges to be faced are cultural change, skills development, confidentiality and defining best practice. “Real world evidence is about managing complexity,” Dr Garner said.
Jeff Brown, Associate Professor, Department of Population Medicine, Harvard Pilgrim Health Care Institute and Harvard Medical School, described how the FDA’s Sentinel system is overcoming the fragmentation of the US healthcare system to use real world data for evidence generation.
“The data is there and we have a requirement to use it – we must figure out how to use it,” Dr Brown said. He told delegates to, “fight the idea that because the data is not perfect and the methods are not perfect, you can’t do anything with it.”
From its inception in 2008, the Sentinel system has grown to include data on 180 million people and is being actively used for monitoring the safety of approved medicinal products. One example of how the information has been used in practice concerns the new-generation oral anticoagulant dabigatran, which was expected to reduce incidences of bleeding compared to standard of care treatment with warfarin.
However, following its approval by the FDA in 2010 adverse event reports seemed to imply dabigatran-treated patients were more likely to suffer bleeding episodes than patients treated with warfarin.
As Dr Brown noted, bleeds are such a common side effect of warfarin the likelihood is they are rarely reported. “The FDA came to us and said what do you see? We saw no evidence that dabigatran presented a higher risk of bleeds. We could do that quickly, before a longer-term epidemiology study, we got an instant answer.”
Although to date the Sentinel database has solely been used for safety queries, Dr Brown said it could be applied to answer questions about effectiveness.
The pharma industry is making forays into the application of real world data and Adam Heathfield, Senior Director Global Health and Value Innovation Center, Pfizer, said the company is now routinely using a database of claims data to inform decisions from phase I development to market.
Pfizer has added a layer of functionality to the database, making it possible to carry out specific queries. “There have been dramatic reductions in cycle time as a result,” Dr Heathfield said.
Typical queries might involve identifying non-responders or tracking when patients experience a disease flare. “We are not necessarily dealing with big questions, but looking to see Who’s ill? Where are they? How are people cycling through healthcare systems?
Claims data is not being substituted for RCT data. “It is the right type of data for these kinds of questions,” Dr Heathfield said. The reduced time to get answers provides a competitive advantage, for examples in decisions about licensing. It is also important in planning and resourcing clinical trials.
Pfizer’s experience also illustrates that applying real world data in a meaningful way does not require a single, harmonized database.
As Mark Pearson, Deputy Director, Directorate of Employment, Labour and Social Affairs, OECD, noted, pharmaceuticals pricing is an increasingly hot political issue. The way to defuse and deal with this is to apply real world data to inform pricing and reimbursement.
However, the feedback from OECD member countries is that doing this is both cumbersome and requires payers to have expertise that is lacking currently. “If it is to become routine we need to use routine data, not require special data collection,” Mr Pearson said.
A survey of the OECD’s 34 member countries showed 13 are using real world data in reimbursement decisions, with some providing coverage with evidence development and other adopting a more ambitious outcomes-based approach, where the price paid reflects the performance of a drug in real life.
Along with helping to speed up access, use of real world data is supporting value-based pricing, and differential pricing for the same drug in different indications. However, as yet payers have neither the time, expertise or political capital, to apply real world data at scale, and as a result it is used only in special cases.
In addition, agreements on outcomes-based pricing currently rely on special data collection, creating yet more information silos.
Johnathan Sheldon, Global Vice President Healthcare, Oracle Health Science, said that in the past two years real world evidence has made the transition from research to clinical care. At the same time pharma has embraced it, with Roche, for example, having accompanying biomarkers for half of its products in development.
Personalized medicine has reached the public consciousness through President Obama’s Precision Medicines Initiative, announced in this year’s State of Union address.
Obstacles remain however. The mechanics of bringing together RCT data, real world data, patient reported outcomes and other data sources, require some level of consistency – even if this is only at the level of a unique patient identifier.
There is a need for action on data privacy, with current rules constraining collaborative research.
And despite long-running efforts to tackle it, interoperability remains a roadblock to progress. “The Precision Medicines Initiative is an opportunity to reboot the system: to use it as a focus to fix interoperability in healthcare,” Dr Sheldon said.
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