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Clinerion Patient Network Explorer

Clinerion Patient Network Explorer

Optimized study design, precise site selection and faster patient search and identification for clinical research - in real time.

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Article: Real World Data as an Instrument to Increase Diversity and Inclusion for Clinical Trials of all Phases.

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By Daniel Gutierrez, Ph.D

The European Union and the USA’s FDA have recently encouraged diversity and inclusion in clinical trials.(1,2) The FDA has issued guidance documents stressing the need for a diverse population in clinical trials, as well as how to achieve this. In particular, they endorse diversity and inclusion in areas ranging from racial and ethnic backgrounds, to genders, ages, and medical conditions in their recommendations. Europe is making it particularly important to include a representative sample of the population.

This article addresses the benefits of diversifying clinical trials, the challenges of doing so, and how real-world data (RWD) can help. RWD can be a powerful instrument to deploy strategies for improving diversity and inclusion in clinical trials, for example, optimizing data collection, analyzing data to identify potential participants, addressing barriers to participation in clinical trials, or ensuring sustainable inclusions and representation.

The Benefits of Diversifying Clinical Trials

Diversity in clinical trials is essential for understanding the impact of treatments and ensure that new therapies are effective and safe across a variety of populations. A diverse group of participants allows any observed differences in the effects of a drug to be attributed to biological, as well as social and cultural factors. It is, therefore, important to identify and include potential participants from different ethnic backgrounds, as well as from different socio-economic groups who potentially have their own unmet medical needs.

Including a diverse group of participants in clinical trials also helps to ensure that the results of the trial are applicable to a wider range of people during commercialization. This is especially important considering patient mobility and the effects of immigration on a country’s sample population.

Understanding the Challenges of Diversifying Clinical Trials

We all know that patient recruitment is expensive and time-consuming. In addition, due to cultural or socio-economic factors, some participants may face barriers to enrolment. For example, patients who are shift-workers may not be able to take time off. Other potential participants may not be aware of the possibility of participating in clinical trials due to complexity of the topic, or face language barriers which could automatically exclude immigrants that don’t speak the local language from the trial.

It is important to ensure that clinical trial staff are aware of and sensitive to cultural differences to create an inclusive environment for potential participants.

How Real World Data Can Help Increase Diversity in Clinical Trials

RWD is data collected outside the controlled environment of the clinical trial setting, such as patient medical records, surveys, and claims data. This data can provide valuable insights into the population of potential participants and can be used to identify and recruit participants who are traditionally underrepresented in clinical trials. This can increase diversity in clinical trials, which can lead to more accurate results and better medical outcomes.

For example, researchers were able to design a clinical trial to test the effectiveness of a new drug specifically in African American patients with heart failure. The results of this trial showed that the drug was effective in reducing mortality rates in African American patients, demonstrating the potential of RWD to improve clinical trial outcomes.(3)

Using real-world data to increase the diversity of candidate drugs during development can also help reduce the cost of the final, launched drug for pharma and patients. For example, an analysis by Gerlinger et al presents a straightforward approach to “assess the potential absolute clinical and economic benefit of a new drug based on real-world data and its target product profile. The approach allows for early data-driven portfolio decisions to select drug candidates based on their expected cost savings.”(4)

The latter article demonstrates that leveraging RWD helps plan and make decisions ahead of commercialization.

Strategies for Optimizing Real World Data Collection

Collecting RWD should be based on a random sampling to reflect the overall diversity of a population for clinical studies. Using standardized approaches, such as coding of inclusion and exclusion criteria, yields an unbiased sample size which can then be retrieved for analysis and study planning. Additionally, establishing technical frameworks of data search and visualization ensures larger sample size retrieval by the institutions holding the data, trust by ethics committees and flexibility when working with sensitive patient information. In addition, it is important to adhere to all applicable laws and regulations when collecting and storing RWD such as with the European General Data Protection Regulation (GDPR).

Prior to deploying strategies for RWD collection, there is the need to consider solutions capable of translating global data sources into one searchable data model. Clinerion’s patented solution, Patient Network Explorer, embeds an ontology system that allows for multisource semantic querying of decentralized patient data, standardizing terminologies for all coded clinical data and thereby making the data interoperable.

Additionally, RWD collection strategies should consider solutions capable of sharing data with external parties and the identification of patients. While ensuring security for the hospital and privacy of the patient’s profile and its raw data is a fundamental feature of RWD sharing, it also needs to provide clinical teams with technical avenues to identify patients for enrolment purposes down the line. Clinerion has a patented solution that tackles this, allowing the pharmaceutical industry to query patients’ data in our network without touching the raw, identifiable electronic health record (EHR) of the patient.

Analyzing Real World Data to Identify Potential Participants

Once RWD has been collected, it can be analyzed to identify potential participants for a clinical trial. This is a key support for diversity and inclusion if searching for patients from underrepresented groups. This process, to identify groups or individuals who are likely to benefit from a treatment or who meet the inclusion criteria for a trial, can be performed by Clinerion’s Patient Network Explorer. By analyzing RWD, it is possible to identify potential participants who may have otherwise been overlooked due to geographical location or lack of awareness.

In addition to identifying potential participants, RWD can also be used to assess the effectiveness of treatments and interventions. By analyzing the data, researchers can gain insights into how treatments are impacting patient journey and identify areas for improvement.

Addressing Barriers to Participation in Clinical Trials

It is important to acknowledge that many barriers may prevent individuals from participating in clinical trials, such as the difficulty of accessing distant trial site locations. By identifying potential participants through RWD analysis, the barriers to entry are significantly lowered as site feasibility analysis and the search and identification of patient candidates become a matter of seconds instead of months. Yes, that wasn’t a typo: seconds. Clinerion allows clinical teams to pre-screen more than 400 million patients in a few seconds, mapping hundreds of hospitals that could match clinical protocols at a fraction of the usual cost.

To sum up, it has become increasingly evident that both the pharmaceutical industry and healthcare institutions that rely on Clinerion's Patient Network Explorer benefit from the patient data access it provides. Additionally, the trial site feasibility provided by patient pre-screening fosters a more inclusive ecosystem that ultimately delivers greater value to patients in the form of a drug that works for them.

Daniel Gutierrez Ph.D, heads Clinerion’s Site Network Engagement group which works with 250+ contracted hospitals of the Clinerion network. Daniel leverages the 60+ million patients of the global Clinerion hospital network in 25 countries to support pharmaceutical projects and clinical trials from sponsors.


  1. U.S. Food and Drug Administration (2018). Considerations for Clinical Trial Design to Optimize Information on Drug Safety and Efficacy in Diverse Populations.
  2. European Commission (2019). Regulation (EU) No 536/2014 of the European Parliament and of the Council of 16 April 2014 on clinical trials on medicinal products for human use.
  3. Gheorghiade, M., Ahmed, A., Fonarow, G. C., Konstam, M. A., Lewis, E. F., O’Connor, C., ... & Butler, J. (2015). African American heart failure trial: design and rationale. American Heart Journal, 170(2), 255-263.
  4. Using Real-World Data to Predict Clinical and Economic Benefits of a Future Drug Based on its Target Product Profile. Drugs Real World Outcomes. 2020 Sep; 7(3): 221–227.  Christoph Gerlinger et al.

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