A Collaborative, Data-Driven Approach to Transforming Clinical Trials

A global panel of experts representing sponsors, CROs, clinical research service providers, and data analytics companies recently came together to discuss the “Power of We,” a collaborative approach to making the drug development path simpler and more predictable — in terms of timelines, cost, and quality. The power really comes from everyone bringing their specific expertise to the approach, because no single organization owns and controls this entire process, making it challenging to operate in a silo.

The global panel included representatives from:

  • Trialbee: Lollo Eriksson, Chief Strategy Officer
  • Clinerion: Barıs Erdogan, Vice President
  • RARAS CRO: Claudia Rodriguez, Co-founder and Director of Operations
  • AstraZeneca: Dr. Mats Sundgren, Director of Health Informatics
  • Captario: Magnus Ytterstad, Head of Decision Analytics
  • Trialbee: Robert Molander, Chief Commercial Officer

Collaborative Approach to Clinical Trials

The industry has the opportunity to create synergies between different expert groups and organizations to further advance how we manage and treat diseases. The use of new resources and techniques that emphasize the use of real-world data, investigator-supported needs, and participant recruitment and retention can improve the productivity of the drug development process.

At the heart of the issue for sponsors and CROs is a lack of insight into the information needed for a successful trial – key participant characteristics; locations of qualified, willing participant populations; availability and locations of experienced investigators and sites. For example, a key challenge experienced by sponsors when launching and implementing a new clinical trial is optimizing the study design – with the right participants, right investigators, and right sites.

Selecting experienced investigators also remains a challenge for CROs, especially given the fierce competition among CROs for active investigators. Poor participant representativeness stems from gaps between the inclusion/exclusion criteria and the real clinical participant profile. A lack of awareness of clinical trials contributes to the limited number of participants taking part in clinical trials, which in turn is a reason that sites do not have continuous access to qualified participants. A steady stream of trial-ready participants allows sites to perform well and facilitates better, predictable planning and trial execution.

Setting Up Trials for Success

How do we address these issues? Strategies include:

  • Utilizing a wide range of real-world data, including electronic health records (EHRs), trials data, and other data, to facilitate participant profiling, identification, recruitment and engagement
  • Using multiple sources of participants to connect, quantify, and refer “study-ready” participants to investigator sites
  • Automating and efficiently pre-qualifying participants
  • Simulating and analyzing the clinical trial process to identify and mitigate risk 
  • Applying operational excellence practices to efficiently use limited resources and effectively manage trials

It Starts With High-Quality Data

We know that HCOs have a wealth of patient data available that could inform protocol development and feed into participant recruitment strategies. But how do you bring all the data together? Clinerion tackled this problem with its proprietary solution “Patient Network Explorer,” which is a high-performance, interoperable, scalable, secure system that runs on federated hospital networks worldwide, covering 200+ hospitals in 25 countries, including the UAE and Kingdom of Saudi Arabia. The system connects with a number of different system types, from state-of-the-art to legacy, through Clinerion’s proprietary, built-in connectors. This technology is disruptive to the current business model by collaborating directly with HCOs.

With this strong network of HCOs, rapid protocol refinement becomes possible based on timely feedback on patient population numbers and their geographic distribution. In addition, patient population and geography information is available by querying the EHR systems for clinical trial inclusion and exclusion criteria. This helps identify the best locations that have suitable participants, ultimately allowing a trial to be conducted with fewer sites, each with more participants. Care providers at these sites provide identification of eligible participants, for fast, efficient participant recruitment.

This type of data is particularly important for site and participant feasibility assessments, which contribute to making informed decisions and quality operational planning, as well as identification of patient populations and surrounding investigators and sites.

Feasibility Analysis

Integrating this HCO data with different other types of real-world data provides more powerful insights for operational planning. For example, an ecosystem of global, real-world patient data is available through Trialbee based on its partnerships with Clinerion; TriNetX, provider of a similar EHR network for research; and Datavant, the leader in privacy-protecting data connectivity. These data span both EHR and claims data, which enables robust patient and site feasibility analyses; smart participant matching to study specifications; and participant engagement.

HCOs with patients meeting a study’s inclusion/exclusion criteria can be identified.

Using claims data, patient availability or patient population at a 3-digit zip code level can inform the ideal recruitment areas and potentially areas to avoid.

Smart Matching

A consolidated profile, including sex, age, race, diagnosis, medications, procedures, and more, of the individuals the study is seeking to recruit is particularly helpful for targeting.

Using consumer, behavioral, and media consumption data, and more, this individual participant profile can be scaled up into a very large group of people that predictably would fit the protocol. The syndicated data and partnership between the companies enable a smart digital presence, where the potential participants receive targeted education and their interactions can be tracked and measured.

Simple, patient-friendly, study-specific landing pages provide further education and information about the study. Interested individuals can complete a self-assessment, which acts as an online pre-qualification step, and eligible persons are invited to provide consent for a personal nurse interview for further qualification. This is a critical component in a multi-step qualification process — to ensure participants are not only matched to the protocol but also willing to participate — in essence, “trial-ready.” 

Therefore, layering the public domain in this way on top of an HCO’s own pool of participants facilitates a steady flow of highly eligible, motivated, and willing participants into the study.

Engagement and Retention

A variety of participant engagement solutions can then be used to ensure that these participants stay in the study and remain compliant. Mobile devices are a user-friendly method for this purpose; an app can provide study information, medication instructions, and FAQs as well as push reminders to take medication and questionnaire completion. Mobile apps can also use geo-location to help the participant navigate to site visits and provide on-demand travel vouchers, immediate reimbursement, or just general travel assistance. This also removes the site burden of following up all participants, allowing time to be spent where needed to address issues or personally engage participants.

Controlling Risk

All of these tools create a better-informed, more efficient trial; however, not all risks can be eliminated. Therefore, an integrated method of controlling risk is needed, which can be accomplished through forecasting models and operational simulations.

Understanding the time and cost-related operational risks can be accomplished with a study recruitment model that incorporates “known” data, such as potential sites, their available patients, and cost data for centers and countries. For data that are initially “unknown,” such as activation time and screening ratios, ranges can be inputted. Using this model, test different site combinations and site activation strategies can be tested as early as possible, even during the planning stage. As data become “known” throughout the trial, “unknowns” can be replaced with these data to refine the model. These ongoing simulations allow us to understand the potential operational risks and implement effective mitigation as the trial is executed.

Benefits for Sponsors and CROs Alike

For sponsors, this data-driven approach utilizing real-time access at the source delivers efficiencies into the trial process. It provides a multi-faceted method of changing the way we conduct clinical trials: study design, site and recruitment feasibility, patient recruitment and engagement, and automatically capturing EHR data into the study database. 

From a CRO perspective, there is the opportunity for value to be embedded throughout the whole project lifecycle, from preparation, implementation, and execution. This value-added information complements the CRO’s experience and knowledge of particular geographies, therapeutic areas, and sponsors. It becomes possible to go beyond study-level feasibility to determine patient-level feasibility, which is becoming increasingly important. For implementation and execution, CROs can adjust plans based on operational modeling that supports monitoring of progress, forecasting, and early detection if the study is going off path.

Collaboration = “Power of We”

This type of integration between different organizations and expert groups allows clinical product development to be executed differently — and more efficiently.

The essential building blocks are real-world driven feasibility using appropriate data sources from a rich ecosystem of information, where EHR and claims data play a key role. Finding patients from multiple sources, including the HCO, provides a steady flow of well-informed, motivated, high-quality, study-matched patients. And engaging patients in a meaningful way during the implementation of the study drives compliance with procedures, adherence to treatment, and retention. Finally, applying advanced operational risk simulation in the preparation stage and during execution enables mitigation planning and activation. 

The “Power of We”: It’s strategic, collaborative, data-driven, patient-centric, and site-centric. Watch the on-demand webinar to learn more.

For more information,  request a demo of this solution.


December 2, 2020