How to design patient-centric clinical trials using real-world data

How to design patient-centric clinical trials using real-world data 

Despite continuous innovation in clinical development, the speed and cost of getting new drugs to market remains high, while success rates remain low. Advancements in science, regulatory requirements and the need for greater speed and efficiency has made clinical trial design increasingly complex. But with more patient data available than ever it’s possible to achieve greater precision in clinical trial design, reduce complexity and patient burden, and deliver faster cures by designing for the patient.

The key to delivering better performing clinical trials lies in unlocking the vast array of real-world data that exists today to gain an in-depth understanding of the patient at the very outset of the trial. A deeper understanding of the patient population results in better protocol design and the avoidance of unnecessary protocol amendments. The time and cost implications of protocol amendments are widely reported. The average phase III protocol for example experiences over 3 substantial amendments, each costing an average of $500,000 and together adding 5.2 months to the cycle time.

Designing for the patient population enables greater precision with outcome measures, making it easier to select trial sites, recruit more patients in a shorter period of time, and collect better quality data from those patients. It’s easy for Sponsors to fall victim to data FOMO (“fear of missing out”) and try to collect as much data as possible while they have access to a patient. But this results in trial protocols having many outcome measures that are redundant or duplicative, placing unnecessary pressure on both patients and investigator sites. By harnessing insights from real-world data and using it to model the true impact of each outcome measure it’s possible to optimize the number of outcome measures used and simplify the protocol design, reducing investigator site and patient burden.

The best way to bring true precision to clinical development is to put the patient at the heart of it. This can be achieved by starting with a Digital Patient Profile. 

What is a Digital Patient Profile?  

A Digital Patient Profile is a detailed contextualized picture of the target patient population – it helps sponsors to have a clear understanding of their patient from the outset. We can create a Digital Patient Profile for any disease using Phesi’s award-winning AI-driven Trial Accelerator™ platform powered by contextualized real-world data from 200 million patients across 195 countries and more than 90,000 dynamically updated data sources (including observational studies, EHRs, retrospective studies, cohort studies, disease records, pharmacy records, claims data and randomized clinical trial data). The Digital Patient Profile is the only way to ensure that the protocol and trial design aligns precisely with the characteristics of the target patient group and the unmet medical need. 

Fig1.0 Illustrative example of a Digital Patient Profile

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What characteristics does it include? 

We have the industry’s largest source of historical and real-world data and using this we are able to create an accurate, statistical view of the patient population for the specific disease area being studied with demographics including age, sex, comorbidities, outcome measures and concomitant medications.

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What can the Digital Patient Profile be used for? 

The Digital Patient Profile is the foundation for profiling patient populations and for optimizing program and protocol design as well as improving diversity and enrollment in any study. It underpins our ability to provide patient-centric analytics to simulate clinical development and improve decision making.

In protocol optimization you can profile your patient before you start the trial. We can create Digital Patient Profiles for over 4,000 indications.  Digital Patient Profiles can be used to identify a set of relevant protocols to highlight the ideal number of outcome measures and endpoints for an indication and the specific target population.

The Digital Patient Profile also drives greater precision in investigator site selection. Aligned to the Digital Patient Profile is our Patient Access Score which provides a unique performance measure of an investigator’s potential to access the patient population defined in the protocol. It enables sponsors to select the best performing investigator sites in the world and eliminate non-active, non-enrolling investigator sites.

For relevant use cases, the Digital Patient Profile can also be used to generate AI-driven digital twins. The alignment between a protocol and the corresponding patient population derived from a Digital Patient Profile enables a digital twin to be generated that represents the patients recruited when following the protocol design at baseline. Safety and efficacy outcomes of the control arm as defined by the protocol can be analyzed, completing the construction of a digital twin. Digital Patient Profiles provide a structured adoption pathway for regulatory acceptance of digital twins and allow early and consistent engagement with regulators. The value of a digital twin extends beyond an external control arm – for example the digital twin can be used to interpret results from a single arm clinical trial or as a historical control arm for regulatory submissions.