Optimizing the efficacy of clinical trials via proficient management of real-world data, ensuring optimal insights for informed decision-making and successful outcomes.
In a recent interview, Iker Huerga, SVP, life sciences strategy and real-world data (RWD) at Tempus, commented, “Despite extensive planning, resource investment, and R&D innovation, about half of all phase 3 oncology clinical trials fail. Suboptimal trial design, particularly around patient selection and understanding of the performance of the control arm, are major contributors to failures, but RWD can help researchers validate clinical trial designs, select the right patients, and understand the performance of patients on the current standard of care (and) strengthen clinical trial design.”[i]
With the increase of clinical trials and volume of data, and the pressure for trial success, there’s a growing demand for effective solutions to manage research-quality data. Curating clinical trial data and managing the complex data sets requires skilled resources and processes to shorten the time from science and hypothesis to publication and treatment, as well as provide evidence and validation for trial funding.
Another key factor for improving clinical trial data management is the cost of bringing a new drug to market, which is around $350 million—not including the cost of failures and delays.[ii] Leveraging curated data from clinical trials and studies to provide large-scale data sets is essential to making research more usable more quickly.
The growing reliance on Real-world data for clinical trial validation
According to the FDA and the industry, RWD and RWE are defined as:
- Real-World Data (RWD) relates to patient health status and/or the delivery of healthcare routinely collected from a variety of sources such as electronic health records (EHRs), claims activities, and disease registries.
- Real-World Evidence (RWE) is the clinical evidence derived from analysis of RWD and from different types of clinical trial study analyses and observational studies.
Research organizations and clinical trial sponsors are using Real-world data to improve their understanding of how patients perform on their current standard of care and selection of patients that are not benefiting from their current standard of care but may benefit from an experimental drug. This helps to reduce costs and increase the study’s probability of success to bring needed therapies to patients faster.[iii]
In 2019, the FDA approved the first drug (Pfizer’s Ibrance) where analysis was largely based on RWD.[iv] Applying RWD supports the validation of hypotheses and observations, helps in discovering new pathways to treatment, and reduces risk for clinical trials. The return on investment can be significant and proves the financial value of a data-based approach for trial design.
Effective data management is essential for accurate collection, entry, reports, and validation. Conducting valid RWD studies requires data quality assurance through auditable data abstraction methods and electronically capturing clinically relevant data at the point of care. Clinical trial sites, however, are challenged to generate clinical RWE as efficiently as possible to allow for meaningful return on trial and research investment.[v]
Technology advancements facilitate data analysis and drug efficacy
Technology leaders and clinicians must establish and maintain organization-wide data management standards to ensure compliance and consistency across teams. Technology advances such as AI tools and natural language processing (NLP), and a dynamic policy landscape in the U.S., have created an environment that encourages the use of RWD to improve methods of clinical evidence generation.
As the methodology for managing RWD evolves, its use in drug development and approval also continues to gain importance. Proper collection of RWD is essential for analysis and proving drug efficacy, which must be factored into a clinical trial at the design stage. Selecting an appropriate data source and ensuring comparability through proper handling of the data can help raise the efficiency of drug development.[vi]
It’s important to note that organizations are responsible for the quality of data collected through clinical trial execution even when outsourced to a contract research organization (CRO).[vii] CROs and pharma are implementing the latest data management technologies and engaging skilled resources to ensure data quality and compliance.
Technology advancements for research include:
- AI/ML-based platforms that support enrolment of subjects in clinical trials
- AI-based medication and protocol adherence support
- Innovation in electronic clinical outcome assessment (eCOA) technology to facilitate a more patient-centered approach to trial design and administration
- Platforms that enhance interoperability between electronic data capture systems like EDCs, EHRs, mHealth, Real-world data sources, etc.
- Centralized data platforms with smart technologies that integrate data from various streams to expedite analysis and understanding of the data
Partnering with an RWD data curation expert helps ensure clinical trial success
With so much at stake, research organizations are partnering with Real-world data data abstraction and curation experts such as Omega Healthcare Clinical Data Services to help meet the growing demand for faster turnaround on clinical trials and high-quality data. Outsourcing clinical trial data management helps to scale resources as needed, ensure industry compliance, and incorporates leading technologies for producing higher quality work faster.
- Improve quality of data making it research ready.
- Minimize risks and help ensure compliance.
- Improve study efficiency, transparency, and diversity.
- Provide flexible team support and scalability to meet needs.
- Accelerate turnaround times and research timelines.
Omega Healthcare provides technology-enabled clinical data management, RWD services, and cancer registry services to improve patient care, reduce administrative burdens and health management costs. Omega Healthcare’s services include building databases and providing research grade records to improve clinical outcomes, and curating and unifying clinical data from disparate sources—all behind the client’s firewall.
[i] “Q&A: De-risking clinical trials with real-world data,” Iker Huerga, SVP, Life Sciences Strategy and RWD, Tempus, January 2023
[ii] “Clinical trials industry outlook: Fall 2022,” RSM, September 14, 2022
[iii] “Q&A: De-risking clinical trials with real-world data,” Iker Huerga, SVP, Life Sciences Strategy and RWD, Tempus, January 2023
[iv] “Real-world Data for Clinical Evidence Generation in Oncology,” Sean Khozin, Gideon M Blumenthal, Richard Pazdur, JNCI: Journal of the National Cancer Institute, Volume 109, Issue 11, November 2017
[vi] “Clinical Trial Outsourcing Trends and Research in 2020,” Thomas Underwood, March 10, 2020
[vii] “Q&A: De-risking clinical trials with real-world data,” Iker Huerga, SVP, Life Sciences Strategy and RWD, Tempus, January 2023