Sujay Jadhav, CEO of Verana Health, outlines the best practices to ensure real-world data has a beneficial impact in clinical trials.
Healthcare and life sciences organisations are under pressure to move faster and make decisions with confidence, but the challenges they face are only becoming more difficult. The process of bringing a treatment through clinical development takes significant time and resources. Market access teams need to show value in a stricter reimbursement environment, while commercial teams need to have a full scope of who patients are, how providers make decisions, and where a treatment fits in the patient care journey.
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Many organisations are turning to artificial intelligence (AI) to make better use of healthcare data. AI has potential, but it’s only as useful as the data that backs it. The challenge is not only in building sophisticated tools, but also ensuring the tools are fed data that is accurate, clinically meaningful, and realistic in how care is delivered.
Real-world data (RWD) is more than just a way to support clinical trial results or answer specific research questions. It can now contribute to informed decision-making throughout the product lifecycle, but only when organisations use it correctly
As AI becomes more heavily utilised in healthcare, the quality of the data needs to be prioritised. While AI can help teams be more efficient in finding patterns and organising information, it cannot fix data that is incomplete, inconsistent, or missing clinical context.
How data can reach its full potential
To show its full potential, data needs to reflect patient care. It needs to show how patients are treated over time, be representative of populations under concern, and include the clinical details that matter. It also needs teams with medical and scientific experts to help translate what the information is showing.
RWD is important at every stage of a product’s lifecycle. Even before a clinical trial begins, it can help teams determine the patient population they aim to reach, how those patients are currently being treated, as well as any obstacles that may delay enrollment. This context can inform design considerations and give sponsors a clearer sense of how the trials may work in the real world.
RWD also plays a significant role after a product reaches the market. Once a therapy is used in everyday care, organisations need to understand how treatment is being administered, how patients are responding over time, and how real-world use of the treatment compares to what was observed during the trial. These insights can help teams confirm whether a therapy is reaching the right patients, how providers are using it, and where it’s having the greatest impact, as well as what barriers may delay access, adoption or long-term use.
For market access and commercial teams, this type of evidence is becoming harder to overlook. Payers and providers want to know how a therapy performs outside of a controlled setting, and companies need that same clarity to make informed decisions in the future. They want to know what’s working and what’s not, and how they can use this information to improve their strategies. By examining the data with a sharper eye, companies can now have a better understanding of what’s really going on and make better choices. This is especially important when deciding which therapies to invest in and how to bring them to market. With the right data, companies can make more confident decisions and achieve better outcomes.
The future of real-world evidence
Most organisations understand that RWD matters. But the big challenge is getting the best data in the right form and at the right moment, especially when decisions can affect medical, regulatory, and business results.
The future of real-world evidence will rely on a balance of data, technology and human expertise. AI will help as organisations search for faster ways to work with large amounts of clinical data, but even the best tools can go so far without clinical data behind them. That is what will help them make better decisions for patients, providers, and the broader healthcare system.
