Everything Must Change

Abstract image of brain

Clinical Researcher—August 2023 (Volume 37, Issue 4)


Edited by Gary W. Cramer, Managing Editor for ACRP




In my youngest days as a fresh-out-of-college journalist, I did a lot more original writing than editing, especially for my first job on a daily newspaper. Back then, with a different story deadline looming practically every day on the job, learning to roll with the punches of having my sterling prose edited by others before it went to print was part of a valuable learning process. The main lesson was not to let myself think that my own ways of wording things were so precious that they could not stand some mending when necessary.

These days, I do a lot more editing than writing, and the chores range in complexity from minor tweaks to massive overhauls of manuscripts, and everything in between. Every contributor to this journal has his or her own preferences for phrasing, grammar, organization, and complexity. My job isn’t so much to smooth it all out into a calm sea of sameness as it is to make sure the peaks and troughs experienced within and between one article/column and the next aren’t too jarring.

One little step in this mission that many readers might never think about focuses on breaking up big blobs of text with helpful subheadings (or “subheads”). These give the reader a bit of a breather between major subjects in the manuscript, but not all of the contributors include them in their original submissions, so I take a first stab at supplying them where I think they are necessary. Some authors, of course, don’t like the wording of my subhead suggestions as much as what they come up with on their own once they have been made to think about it, and learning to be flexible as an editor in these circumstances was also a valuable experience for me in my earliest days in this job.

I think I wanted to tell you all this because it helps make some sense of the theme for this issue—“Everything Must Change.” I’m pretty sure that somewhere along the way in my editing of materials for this August’s cornucopia of topics, I suggested that exact phrase as a subhead for one of the manuscripts, but the authors disagreed and inserted some other wording with which they were more comfortable. That’s fine, of course, but I couldn’t let the idea go that, when you take them as a gestalt, in one way or another the pieces of this issue are all about not just the need for, but the inevitability of, ongoing change in the clinical research enterprise—not just change for the sake of change, but change for the better.

Here are excerpts from recent announcements of some more changes happening in our industry (no endorsements implied) that I hope you will find useful, or at least can enjoy as a breather between some of the bigger, more important things you mean to accomplish with your day…

Cost of Translating Consent Documents May Serve as Barrier to Participation for Some

Cancer research centers conducting clinical trials could enroll more patients from underrepresented racial and ethnic groups by placing greater emphasis on relieving investigators of the costs of translating consent documents into languages other than English, according to a UCLA Jonsson Comprehensive Cancer Center study.

Consent documents presented to potential clinical trial participants are required to be in a language understandable to the patient, and studies sponsored by pharmaceutical companies—about 70% of all randomized cancer clinical trials—typically have budgets that cover the costs of translating documents into languages appropriate for participants. In studies that are not sponsored by drug companies or device makers, investigators often operate on a fixed, per-patient budget provided by a grant, often from philanthropic organizations or governmental groups. As a result, an unexpected cost, such as the cost of consent document translation, often reduces the funds available for other potentially important aspects of the research.

The UCLA research team, which published its findings in Nature, theorized that these additional costs could discourage investigators from recruiting patients for whom consent document translation would be required, contributing to the disproportionately low rates of participants from traditionally underrepresented groups in clinical trials. Researchers analyzed “consent events”—situations in which consent documents were signed—and compared those for industry-sponsored studies versus studies not sponsored by industry. Each “event” did not necessarily represent a single patient, because some participants signed consent documents for multiple trials.

The researchers evaluated potential differences in the two types of trials based on participant primary language and English proficiency, basing their findings on more than 12,000 consent events that included 9,213 participants in trials at the cancer center between January 2013 and December 2018. The differences were dramatic. The proportion of consent events for patients with limited English proficiency in studies not sponsored by industry was approximately half of that seen in industry-sponsored studies. When patients from this group signed consent documents, the proportion of consent documents translated into the patient’s primary language in studies without industry sponsorship was approximately half of that seen in industry-sponsored studies.

Academic/Industry Partnership Launches AI Program for Clinical Trials

Texas Tech University Health Science Center (TTUHSC) and Deep 6 AI have announced a collaboration, joining forces to integrate artificial intelligence (AI) within TTUHSC’s electronic medical record (EMR) system to improve patient access to clinical trials. TTUHSC will use Deep 6 AI to precision-match patients to their clinical trials in real time. This process will allow researchers to find the right patients for their trials in minutes, which will greatly reduce the workload on their staff. By using these AI tools, TTUHSC researchers will ultimately give more patients access to participate in clinical trials and will be able to use any resulting therapies to treat patients even faster. This partnership further expands the Deep 6 AI ecosystem, which consists of millions of unique patient records and thousands of trial sites accessible to sponsors for their research.

One of the most time-consuming components of clinical research is finding patients who match the specific criteria needed for the study. Deep 6 AI uses natural language processing to search through millions of structured and unstructured EMR datapoints, such as physician notes, lab reports, outpatient notes, radiology reports, genomics results, and pathology reports, to precision-match patients to the ideal clinical trials. This process simplifies patient recruitment and allows administrators to focus on patient care and managing the trials, which is increasingly important when staff time is at a premium.

Generative AI Now Predicting Clinical Trial Outcomes

Insilico Medicine, a clinical-stage end-to-end generative artificial intelligence (AI) drug discovery company, has demonstrated that it can predict the outcome of Phase II to Phase III clinical trial success using its proprietary transformer-based AI clinical trial prediction tool called inClinico with a high degree of accuracy. The research has been published in Clinical Pharmacology and Therapeutics. The AI engines used in the study are integrated into Insilico’s inClinico system, designed to predict the outcomes of clinical trials as a part of the Medicine42 clinical trials analysis and planning platform.

The research paper included three types of validation of AI engines trained to predict the probability of success of Phase II trials, including retrospective, quasi-prospective, and prospective validation. The AI of interest was trained on more than 55,600 unique Phase II clinical trials over the last seven years. The subsequent model for clinical trial probability of success developed by Insilico researchers demonstrated 79% accuracy on the outcomes of real-world trials in the prospective validation set where those outcomes were able to be measured. The findings indicate that target choice is much more likely to impact clinical trial outcome prediction than trial design, underscoring that lack of efficacy is the primary driver of clinical trial failures.

Project Gives Trial Patients a Platform to Share Their Experiences and Influence Change

Mural Health has launched a non-commercial initiative to share the stories of the people who make clinical research possible. The Portrait Project is a collection of stories detailing the personal experiences of trial participants, caregivers, and medical professionals. The accounts are uncensored and, often, brutally honest. Each story serves to educate by sharing our industry’s victories, what is working, where we have fallen short, and opportunities to improve. In all cases, the Portrait Project aims to amplify the voices of patients and their loved ones. It can be found on Instagram, Facebook, LinkedIn, or by visiting https://portraitproject.muralhealth.com/.

The Portrait Project serves to share the often-overlooked narratives of trial participants and to increase awareness, dispel misconceptions, reduce stigmas, and create a community that collectively uses its voice to influence positive change throughout the clinical research ecosystem. Stories from the Portrait Project cover the spectrum of experiences—from cancer survivors who want to alleviate fears of the newly diagnosed, to caregivers who emotionally recount journeys ending in the deaths of loved ones. Certain stories highlight how clinical research profoundly changes lives for the better. Other stories will be critical of the clinical research industry’s imperfections, recounting moments of sadness, loss, and personal devastation.

Quantifying the Impact of the Pandemic on Cancer Center Clinical Trial Operations

Leveraging its network of North American cancer centers, the Association of American Cancer Institutes (AACI) circulated surveys to more than 100 cancer center members to assess how clinical trial office operations were impacted by the COVID-19 pandemic. A report summarizing the results of the longitudinal series of surveys was published in the Journal of the National Cancer Institute (JNCI) Cancer Spectrum.

The lead authors of “Quantifying the Impact of the COVID-19 Pandemic on Cancer Center Clinical Trial Operations” come from the University of Florida Health Cancer Center, the University of Kansas Cancer Center, and the Huntsman Cancer Institute at the University of Utah. According to a press release about the study, data shared in the report show that AACI cancer centers were able to keep oncology trials available to patients while maintaining safety. Survey results demonstrated a sizeable decrease in interventional treatment trial accruals in both 2020 and 2021 compared to pre-pandemic figures. Though the pandemic significantly impacted the national clinical research infrastructure, cancer centers were resilient, as evidenced by improvements in efficiencies and patient-centered care delivery. The pandemic necessitated rapid adaptation of trial operations to new best practices, including remote monitoring, remote consenting, electronic research charts, and work-from-home strategies for staff.