Patient Centricity in Clinical Trials: When Searching is a Struggle

Tom Krohn, Chief Development Officer, Antidote

Tom Krohn, Chief Development Officer, Antidote

It’s no secret—it’s not easy for a patient to find a relevant clinical study. Heck, it isn’t easy for a research pharmacist like me to help a patient find a relevant trial; yet, patients and caregivers are looking. serves almost 200 million page views/month, and that does not count the number of times it is replicated on other sites.

Try searching from the perspective of a patient. You’ll be delivered a long list of search results. The only way to compare trials is to read them one-by-one, and then you’ll hit a second challenge: advanced medical terminology. I have done readability analyses on the purpose statements of numerous studies, and they are consistently greater than 16 years of education, and can go as high as 27 years! Meanwhile, the average reading level in the United States is about 7th to 8th grade.

A clinical study participant said in an interview with Antidote, “I always felt like I needed some advanced degree to figure out if I qualified or not. Some trial listings had conflicting information or were just very scientific, not ‘average Joe’ information.”

Here’s the problem: sponsors communicate and operate from a scientific and study point-of-view. Each study protocol is written by a different medical writer, and registries were made for disclosure compliance, not patient engagement. From an operational point-of-view, researchers are focused on finding patients for their study, whereas patients and caregivers are looking for any relevant study that will help them.

The Patient Voice: Improving Patient Experience by Understanding Patient Perspective – Gain valuable patient insights and practical strategies for implementing patient-centricity measures in your clinical trials at ACRP 2018 this April. This session, led by Jeneen Donadeo from TransCelerate Biopharma Inc., will explore patient perspectives gathered from a global survey conducted by TransCelerate and CISCRP, and how the resulting data have been put into action to improve the patient experience. View Session Details

ACRP 2018

The traditional model makes sense in the framework of an individual study, but with more than 58 million clinical trial participants needed in the U.S. alone, we require a significant industry shift to usher in willing study participants and match them to the right studies—a collective effort to accelerate research through patient centricity.

Clinical trial search platforms are paving patient-centric journeys to medical research participation. The best of them are empowering patients to broadly search all trials in a therapeutic area and narrow in on their “match” by answering questions in plain language. Here’s how.

Structuring Trial Listing Data for Searchability

 Today, clinical trial eligibility criteria are published in free-form text format to public registries, such as This free-form text is a type of unstructured data that is difficult to organize and analyze in terms of how one piece of data relates to or compares to another. This means that using unstructured data to match patients to clinical trials with any degree of precision is challenging, at best.

Structured data, on the other hand, is organized and can be coded for consistent meaning (semantics). Structured data can be searched with algorithms, and with use of medical ontologies, the algorithm can infer context, just as humans do. An example of inference is parent-child relationship: if an exclusion criteria is “no autoimmune disease” (disease concept parent), one can infer that a patient with rheumatoid arthritis (disease concept child) would be ineligible. While humans make inferences naturally, the use of semantic technologies (ontologies) with structured eligibility criteria helps advanced search platform narrow in on relevant studies for patients.

Companies have begun working to structure the publicly available, free-text clinical trial data; in the case of Antidote, we are structuring eligibility criteria using industry-standard medical ontologies. Once the data are structured, algorithms can be applied to match a patient to clinical trials based on their answers to eligibility questions. Instead of a long list of results, patients receive listings for the few trials for which they may be eligible.

An alternate and complementary method to connect volunteers to medical research is to build a structured database of patient profiles. For example, PatientsLikeMe has built a community of 500,000 patients who can receive trial notifications. Similarly, The Michael J Fox Foundation for Parkinson’s Research has connected more than 70,000 volunteers to clinical research by allowing patients to build profiles and receive trial alerts via its tool, Fox Trial Finder.

Simplifying Study Language for Readability

 According to the U.S. Department of Health and Human Services, just 12% of Americans today are health literate, and for the first time, national data show that “currently available health information is too difficult for average Americans to use to make health decisions.” Efforts to deliver patient-friendly language are critical, including communications reviews to ensure the appropriate reading level in eligibility questions and presentation of medical terms in lay language.

Patients and caregivers are looking for trials—all the more now that we are entering the days of precision medicine. In the end, significantly improving enrollment rates for a single trial is dependent on transforming how patients find and access all trials relevant to them.

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Author: Tom Krohn, Chief Development Officer at Antidote