How RWE Improves Evidence Generation Across the Product Life Cycle

Real-world evidence (RWE) is crucial for biopharmaceutical companies and other life sciences organizations to develop the right products for the marketplace. RWE is a powerful tool for regulators, too, in terms of continually assessing the safety, effectiveness, and value of new products or existing products in the context of new indications. In fact, there are numerous examples of life sciences organizations leveraging RWE to support regulatory submissions with success. Take a look at this compilation of use cases for 10 recent examples.

To truly harness the power of RWE, life science organizations need a solution that surfaces critical insights faster throughout the product life cycle, including the optimization of clinical trials, informing comparative effectiveness and safety assessments, and addressing payor-specific needs.

Here’s how the right RWE solution can help teams during each stage of the product life cycle.

Early Phases

Research & development and clinical trial teams should look for an RWE solution that can help to quantify burden of disease, optimize clinical trial design, and identify opportunities for label expansion. RWE can support the creation of external control arms, profile target populations and understand market potential – all to drive an end product that better serves the marketplace. Additionally, RWE helps teams identify clinical trial sites, providers and patients that meet enrollment criteria, making the development process more efficient overall.

By using RWE in the early phases of the product life cycle, epidemiologists are armed with valuable information that helps them assess a product’s benefits and risks, evaluate incidence and prevalence, conduct feasibility studies, and understand the natural history of disease.  Pre-clinical epidemiology teams or trial operations teams can focus on which trials (or studies) to prioritize, how to optimize trial/study design, and the feasibility of those trials/studies, including equitable and inclusive site, provider, and patient selection.

• Example #1: Global Pharma Company Leverages RWE to Bring Greater Equity to Clinical Trials
  The epidemiology team of a top ten global pharmaceutical company was tasked with providing prevalence estimates and corresponding age, sex, race, and ethnicity distributions for indicated populations to benchmark clinical trial diversity enrollment. Partnering with a Panalgo analyst, the team leveraged the Instant Health Data (IHD) analytics platform to design and implement the diversity study. Prevalence estimates were obtained via IHD across databases and indications of interest, generating RWE to identify benchmarks to bring greater equity to clinical trials. Not only did the team help bring greater equity to clinical trials, but they managed to save $1.1 million in three months vs. outsourcing and completed analyses for 11 separate indications. The team was able to benchmark clinical trial recruitment against regularly updated RWD.

Late Phases and Post-Approval

In the later phases of the product life cycle, RWE is a valuable tool, as well. Epidemiologists use it to respond to regulators’ requests and requirements more quickly, evaluate product safety and effectiveness, and monitor treatment patterns, dosage, and duration.

HEOR therapeutic area-specific researchers whose database studies are a part of their broader evidence generation plan to support payor conversations also benefit from RWE. The right RWE solution helps HEOR teams analyze comparative effectiveness, determine healthcare resource use and cost, and understand patient outcomes. RWE also helps HEOR with study adherence and drug utilization and with generating evidence for market access and reimbursement. Through the use of RWE, researchers can develop value-based contracts for their product and support payor conversions.

• Example #2: HEOR Team Leverages RWD to Inform Real-World Patient Management and Resource Allocation for COVID-19
  At the start of the COVID-19 pandemic, providers were challenged to understand which patients would return for hospitalizations after COVID-19 diagnosis, causing issues with resource allocation and utilization. HEOR researchers at a top 10 pharma company needed to identify the risk factors for COVID-19 hospitalizations to inform which patients would require critical care or hospitalization within 30 days following outpatient diagnosis of COVID-19. The team used the IHD platform to run statistical analyses every 2-4 weeks as new RWD emerged and to develop predictive models for subsequent hospitalizations. They generated RWE to help providers improve decision making for patient management and treatment, allowing hospitals to improve resource allocation and utilization.

For payors, too, RWE is a valuable resource. Payors look for data to benchmark healthcare delivery and to make decisions regarding their formulary and benefit designs; RWE can help them do that. RWE gives payors insight into population benchmarks and trends such as the course of care and cost within a population. RWE helps payors to inform care management programs, benefit design, value-based care models, and formulary decisions. RWE enables payors to evaluate provider and network performance regarding treatment, prescription patterns and patient outcomes.

It’s clear that RWE is essential across the product life cycle – but it’s not as clear how companies can stay ahead of the curve. To fill this gap, Panalgo is providing full service analytics solutions with the IHD Analytics platform, streamlined access to data through industry partnerships, and analytics services. Custom solutions combine access to data, software, and services in ways that best fit a client’s research needs and resources. With solutions like these, teams can generate RWE across all use cases, improving evidence generation from pre-clinical to post-marketing.

Additionally, Panalgo’s RWE solution enables teams to:

1. Leverage multiple data sources from one vendor to raise the value, effectiveness, and efficiency of RWE generation, from feasibility to forecasting.
2. Meet rapid timelines within reasonable budgets.
3. Support planned or ad-hoc responses to internal and regulatory requests or requirements.
4. Start their in-house analytics journey and scale their research as they bring on new data sources.

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To learn how to leverage RWD across the product life cycle with our end-to-end RWE solutions, contact us today.