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Real World Evidence Opportunities in Rare Disease
Mar 09, 2021
Pharma companies developing rare disease treatments face unique challenges in collecting real world evidence (RWE) data to support their initiatives. Real world studies of these diseases are limited by multiple factors: the prevalence of under/late diagnosis; the understanding of the disease being limited to a low number of specialists; and, patients being seen across a variety of settings—primary, secondary, and tertiary—by both primary care physicians and specialists.
The pervasiveness of healthcare data and the growing data fluency among regulators, payers, and other stakeholders, means that pharma companies now have a much wider range of options to use real world evidence (RWE) to support their development efforts.
In some cases, a combination of claims data, electronic medical records (EMR), and patient registries can be used to answer key research questions, even among small and dispersed patient populations.
Direct-to-patient studies, a ‘mosaic’ of combinations of clinical and real world components, and enriched studies that combine data collected from physicians and patients with secondary data are being deployed across rare diseases. These innovative RWE methods can provide a more comprehensive understanding of the patient journey and be used to identify patients and support more comprehensive diagnosis of these conditions.
Here are two examples of those innovations in action.
Algorithm finds cardiac patients
IQVIA recently partnered with a large pharma company that had a highly efficacious treatment for a rare cardiac disease treated by a small number of specialist centers in the UK. They wanted to provide support for patients in early diagnosis when treatment had a greater effect, but due to the rarity of the disease, the diagnostic coding in the hospital claims dataset was insufficient to identify these patients.
To find them, IQVIA built a machine learning algorithm to assess patterns of healthcare utilization and diagnoses in the UK’s national Hospital Episode Statistics (HES) records. Then the team linked EMR data from the leading specialist center to the national HES to define a precise cohort of patients and validate the findings. The analysis identified opportunities to accelerate diagnosis in certain regions, which led to the subsequent development of a predictive algorithm that eventually will be piloted to support screening efforts.
Oncology evidence generation
RWE can be especially useful in the competitive oncology market, where product differentiation and value demonstration are key. Pharma companies can use RWE to hone their R&D plans, accelerate launch, improve uptake, and differentiate their products in a crowded marketplace. However, they face multiple challenges, particularly in Europe where the quality and depth of data is limited, privacy restrictions limit access to data, and fragmented data systems and electronic medical records (EMR) limit comparative analysis opportunities.
IQVIA is mitigating these challenges by leveraging our data expertise and our relationships with key opinion leaders (KOLs), and our advanced analytics capabilities, to create disease specific networks that can be used across the drug development lifecycle. Their applications include
- Offering external comparators to support Health Technology Assessment (HTA) and regulatory submissions
- Using retrospective observational studies to run real time queries and bespoke analyses
- Using internal RWE studies to test protocol feasibility and hypotheses during clinical phases
- Honing differentiated value messaging for commercial applications
What study design is right for you?
RWE studies are a powerful tool to gather insights about hard-to-find patients. However, selecting the right RWE methodology and format is critical to generating the most value from these investments.
RWE studies generally fall into two categories:
- RWE studies based on broad coverage data sources. Studies using existing data from medical claims, pharmacy records, and ambulatory EMRs are generally quicker and less costly to execute, and provide generalized insights across large segments of the population, with limited specificity. They are useful for defining the patient journey, identifying population characteristics, and tracking patients across a region.
- RWE studies based on clinically rich sources. These studies provide detailed insights about specific populations, but they come from a much smaller number of patients (lower coverage) and can be costly and complicated to run. The data can come from specialty network databases, patient registries, specialty EMR, and studies custom built for a specific evidence need. They are useful for
- Generating evidence/outcomes
- Understanding the economics of the disease and treatment landscape
- Demonstrating comparative effectiveness
- Supporting deep scientific investigation
The rare disease treatment landscape is complicated and competitive, and sponsors need strategies to help them enhance their submissions and commercial efforts. Taking advantage of the available ‘mosaic’ of clinical and real world components in RWE studies can deliver these benefits. They cut the time and cost of clinical research and provide a more robust picture of the patient journey, and a treatment’s impact on their quality of life and healthcare costs.
IQVIA can help you analyze and understand the ever-expanding ecosystem of clinically rich data in the context of your organization’s needs. By combining advanced analytics with unparalleled data and scientific expertise, IQVIA provides customers with innovative real world evidence approaches to meet stakeholder needs throughout the product lifecycle.
eBook: Explore Transformative RWD Sources
Discover how you can leverage RWE to accelerate study timelines, shorten time to market, cut research costs, and more. In this interactive eBook, read case examples on how key client questions were answered in various therapeutic areas and glean insights on how you can use RWD to answer challenging research questions.