Look behind the lecture: an industry perspective on real-world evidence

In this feature, Jefferson Tea (Takeda Canada Inc.; ON, Canada) discusses his presentation from the Patient Registries, Real-World Evidence and HEOR meeting (27–28 January 2020; Miami, FL, USA) on how and why the industry perception of real-world evidence may differ from that of other stakeholders.

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Please could you introduce yourself, your work and organization?

I am the Vice President of Medical and Scientific Affairs at Takeda Canada Inc. (ON, Canada), where I lead a department consisting of teams in medical affairs, evidence generation, real-world evidence, regulatory, medical information/pharmacovigilance and quality assurance.

Takeda is a global, values-based, R&D-driven biopharmaceutical leader, focused on four therapeutic areas: oncology, gastroenterology, rare diseases and neuroscience. Takeda also makes targeted R&D investments in plasma-derived therapies and vaccines. Overall, I have over 20 years experience in the pharmaceutical industry.


What do you perceive to be the current global industry perspective on the quality and usability of registry and real-world evidence?

Although stakeholders generally agree on many uses of real-world data or evidence that may contribute valuable information for healthcare professionals and in regulatory and reimbursement decision making, the use of real-world evidence to answer questions concerning the relative effectiveness of interventions is generally not widely accepted; some may even question the possible impact of increased reliance on these data.

 …the use of real-world evidence to answer questions concerning the relative effectiveness of interventions is generally not widely accepted…”

Currently, real-world evidence is used mostly to confirm or supplement, rather than replace, evidence derived from randomized controlled trials concerning the safety and efficacy of medical products. However, I think there will be increased recognition and acceptance of real-world evidence in specific situations, such as when randomized controlled trials are not feasible. This may include instances when one is investigating rare disease conditions, when clinical trails may be unethical – such as during pregnancy – when there is significant unmet need, when investigating life-threatening conditions, and/or to identify serious, rare or long-term adverse effects of therapeutics.


What are some of the challenges associated with working with and employing real-world evidence in industry?

  • Acceptance of real-world evidence

Traditional randomized controlled trials remain the gold standard for demonstrating efficacy and safety of medical products; this is well accepted by healthcare professionals, patients, payors and regulators. As a result, this represents a significant hurdle for real-world evidence and its acceptance. That being said, I think we are starting to see a growing recognition that randomized controlled trials alone cannot provide sufficient data for informed healthcare decision making in some situations. Because real-world evidence can capture the use of medical treatments in real-life settings, it could be used to better understand and characterize patients, and evaluate new treatments when randomization to placebo for clinical trials may be impossible, impractical or unethical, such as in rare disease conditions.

…I think there will be increased recognition and acceptance of real-world evidence in specific situations, such as when randomized controlled trials are not feasible.”
  • Difficulty defining the quality of real-world evidence

Despite the value of real-world data, it is also clear that a lack of defined quality standards to develop real-world evidence limits its broader use. Unlike randomized controlled trial methodologies and practices (for example, Good Clinical Practices and other practice quality guidelines), which are well developed and understood, the same cannot be said for real-world evidence. There are emerging attempts from different groups to define the quality of evidence required for real-world evidence, but we are far from a consensus. To be impactful and useful, real-world data need to be susceptible to robust analytics to confirm that data methods have eliminated biases, controlled quality and allowed for integration of disparate data sources for both prospective and retrospective studies. Greater transparency around real-world evidence study designs and results is needed, similar to the publication of clinical trials through a platform like clinicaltrials.gov.

…I think we are starting to see a growing recognition that randomized controlled trials alone cannot provide sufficient data for informed healthcare decision making in some situations.”
  • Limited access to real-world data

A more uniform access to existing real-world databases for medical research could improve data quality. However, there is not consensus among healthcare professionals, patients, policy makers and the general public regarding the potential public health benefits of real-world data. Privacy concerns related to allowing access to these large datasets and the potential results of advanced real-world evidence analytics have restricted both the collection and sharing of existing data. Although there is stronger support for access from stakeholders in independent academic research – compared with industry-sponsored science – data access remains a major hurdle.


What can be done to progress industry consideration and use of registry and real-world data?

  • Increased partnerships in the healthcare ecosystem

The industry will need to identify academic collaborations to ensure credibility and trust in analyses, as well as gain access to novel data sources. Unbiased academic experts are needed to address short-term concerns around credibility and trust of these real-world data. Industry may also need to consider partner­ships with subject matter experts that have defined roles, such as in analytics, machine learning and artificial intelligence. In the long term, investment in building real-world evidence expertise across the entire healthcare industry will be needed to elevate the science and methodology of real-world evidence analytics, so that it is on par with, or even better than, randomized controlled trial data in specific situations. Similarly, partnerships with database owners will be required in the short term to use data in restricted-access databases, whether these are government-funded databases of public health systems or private payers, where access to data is restricted.

Despite the value of real-world data, it is also clear that a lack of defined quality standards to develop real-world evidence limits its broader use.”

In the long term, however, such partnerships could demonstrate the public health benefits of real-world evidence to both database owners and the public at large, to build support for higher-quality real-world databases and expanded access to them.

  • Building platforms and capabilities to address needs of the future

Industry must capitalize on the benefits of real-world evidence over randomized controlled trial data and address the inherent weaknesses of real-world datasets. Building platforms and capabilities – includ­ing data infrastructure and storage – to increase the turnaround time and decrease the cost of real-world evidence studies is critical to being able to utilize these data for internal business decisions. Platforms can also incorporate standardized methodologies, which can be applied across all studies, improving the robustness and credibility of outputs.


How do you see the industry perspective on real-world evidence changing in the future?

First, I think there will be a rapid and exponential rise, globally, in the capture of healthcare data in routine electronic format, which has fundamentally changed the way we generate evidence.  Second, the ability to interpret real-world evidence and apply it to key decision making will accelerate for healthcare professionals, payers, governments and industry, with powerful tools centered around data analytics – such as machine learning and artificial intelligence. Finally, I think global regulatory frameworks will be built and this will enable real-world evidence to be accepted at the same level as randomized controlled trial data, starting with very focused areas such as rare diseases, eventually expanding to all areas.


Disclosures:

The views and opinions expressed in this piece are those of Jefferson Tea, based on his 20+ years of experience within the pharmaceutical industry, and do not reflect any official position of his current employer, Takeda.

The opinions expressed in this feature are those of the interviewee/author and do not necessarily reflect the views of The Evidence Base® or Future Science Group.

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