Those who have conducted pediatric oncology clinical trials know all too well that site-based treatment can create barriers that prevent patients from receiving potentially life-altering therapies.

Important financial, transportation and other social issues can affect parents’ ability to bring their immunocompromised children into research centers. Unaddressed, these issues can result in low enrollment and high dropout rates for clinical trials, delaying study completion and slowing the availability of promising therapies to more families.

Earlier this year, the Children’s Oncology Group (COG) and Signify Health set out on a mission to address some of these barriers by meeting pediatric patients where they are: in
the home.

We started this work by creating an in-home option for children diagnosed with B-cell acute lymphoblastic leukemia (B-ALL). B-ALL is the most common childhood cancer, representing 20% of diagnoses in children younger than 15 years old and the leading disease-related cause of death for children ages one to 19 years. Promising new therapies have the potential to alter the course of B-ALL progression, so removing barriers to clinical trial participation is a primary focus for researchers.

AALL1731 (NCT03914625) is sponsored by the National Cancer Institute (NCI) under a Cooperative Research and Development Agreement (CRADA) with Amgen, and is currently open at 195 U.S. COG sites. COG and Signify Health are partnering to make in-home infusion services available for patients who are randomized to receive blinatumomab on AALL1731 and who are unable to access outpatient pumps and homecare. Amgen has provided funding to NCI under the CRADA to help more pediatric patients receive blinatumomab at home.

We are delighted that after months of preparation, AALL1731 is now available on an in-home basis for eligible patients who choose it. Our experience may be instructive for other study sponsors and investigators considering making an in-home option available, and we thought it would be helpful to share insights around key areas of focus for our team.

Having a stranger in the home and administering a potent drug to your child, can be a scary, overwhelming experience. So we put ourselves in the patient’s and families’ shoes, asking ourselves: What can we do to make this easier for the family? How can we make this less intimidating for the patient? What will make the patient as comfortable as possible? Ultimately, everyone involved in the clinical trial wants the families to know that we all care about the patient as much as they do.

We approached this challenge by designating one point of contact from Signify to answer all of the patient’s and family’s questions, be on call as often as necessary, proactively seeking their feedback after each visit, and coordinating all logistics with the clinician, the hospital and the researchers. This personalized approach makes the first visit that much easier.

Ensuring that the nurse clinician is prepared

Not only do the families need to be prepared, but the visiting nurse clinician also needs to have everything readily available to administer the therapy and follow the protocol. Our teams prepared a bag of everything that might be needed: tubing for infusions, various sizes of needles for blood draws, copious amounts of PPE, proper waste disposal (baggies, containers, etc.), even a thermometer—anything that would be readily available to healthcare workers in the hospital must be on hand for them in the home.

In-home delivery would also not be possible without technology that enables everyone—Signify, COG, the nurse clinician, and clinical coordinators—to communicate and coordinate. Clinical trial protocols and all of our in-home standard operating procedures (for example, what to do if the patient is not home, what to do if the patient has a high fever) are uploaded to an iPad that is kept with the materials. Any issues immediately trigger a call from the nurse clinician in the home to the patient’s managing physician to discuss the finding and next steps.

And of course, one of the many important considerations when delivering continuously infused medications at home for pediatric patients; given that there may be curious siblings running around the home, we placed a lock on the materials to ensure safe keeping.

In clinical trials, timing is everything. For the AALL1731 trial, blinatumomab has a very short half life and thus must be delivered intravenously for 28 days, 24 hours per day. So when a patient is approved for discharge from the hospital, the visiting nurse clinician has a very small window of time that they can arrive at the patient’s home to initiate the treatment—they must hook up the patient within four hours of leaving the hospital. Once in the home, patient metrics are documented in real-time and then the nurse clinician is on call for the first 24 hours after a bag change to address any potential pump malfunctions.

Ensuring that the timing matches up at each touchpoint is no easy feat—and given that we do our best to send the same provider each time, it can be even more challenging. We have to prepare for all scenarios which require flawless logistics, streamlined technology and timely communications.

As in-home clinical trials become more commonplace, a critical component of their success will be the development of clear and forward-thinking plans for managing the clinical trial in the home setting. Our experience has shown us that by offering this easier way for patients to participate in clinical trials—for example by bringing clinical trials to them, in their homes—we can help bring new, life-saving therapies to patients around the world.

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Bringing clinical trials to patients’ homes can address existing site-based challenges.

Patient-Tested Practices for In-Home Trials

At the end of April, The Conference Forum’s Clinical Research as a Care Option, or CRAACO, featured a fireside chat with emerging investigator physicians. These physicians— Ron Blair, MD, President, Forest Lane Pediatrics; Charlotte Grayson, MD, Partner and Internist, First Georgia Physician Group and Tina Kennelly, MD, Director of Tryon Medical Partners—have only been in research for approximately one year. Jennifer Byrne, CEO of Javara, an Integrated Research Organization (IRO) which brings clinical research into healthcare organizations allowing patients and doctors access to trials at the point of care, served as moderator of the discussion. While the physician investigators did partner with Javara to integrate clinical trials into their practices, the insights they shared were specific to their practice’s and patients’ experiences. Byrne acknowledged that their combined efforts led to 2,000 people being enrolled in clinical trials that a year ago would not have had exposure. Byrne also acknowledged that Javara moves “together in partnership with like-minded healthcare organizations, providers, healthcare leaders that actually see the value in research.”

What follows is a summary of their discussion.

Grayson is partner and internist at First Georgia Physician Group located in Fayetteville, Georgia, about 30 miles south of Atlanta. The population around the multi-specialty practice is suburban, somewhat rural, but also draws on the southern Atlanta area. The internal medicine patients start at 18 years of age through end of life and the practice treats many palliative care and hospice patients, as well as complex cases of patients throughout the range of internal medicine. Grayson also noted that the patients were very diverse, with a 90% female base, and a majority of African American, Latino or Southeast Asian descent. “The opportunity to bring research to this population, who tend to be underrepresented in clinical trials, was something I was really excited about. But I also knew that I was going to be facing some challenges with these patients, where many have never heard of research,” Grayson said.

For the majority of physicians in Grayson’s practice, their exposure to research was limited to their residency and training days. They needed refresher-training, as well as full training for the staff, to learn how to present research to patients and answer questions. “As we started to ramp up clinical trials, we did a kind of bedside education with them so that they understood what these trials were and how to interact with our patients.”

Tryon Medical Partners, based in Charlotte, North Carolina, is a fairly new practice, which broke off from a nearby hospital system approximately three years ago. The multi-specialty group includes cardiology, dermatology, rheumatology, endocrinology, as well as Kennelly’s specialty internal medicine. She says her primary focus is on women’s health and preventative care. The group didn’t have a formal research department and wanted to offer research as an option for patients because of what they felt were the inherent patient benefits. “We thought that it would provide a higher touch option for patients. Maybe patients who weren’t as well controlled in their diabetes could get enrolled in a diabetic study and we could couple them with trainers, as well as clinical trial navigators and get them involved. Again, providing a high touch option that would hopefully improve their care overall.”

Kennelly explained that the group began with smaller trials, an anxiety trial and atrial fibrillation, both device trials. But when they were offered COVID vaccine trials, they had to ramp up research pretty quickly. Of the one hundred physicians in the practice, 50% have been trained as investigators or sub investigators. “It took a lot of support and infrastructure to get our group—who was pretty naive because we are a young practice—where we are today. We’ve done the Moderna COVID vaccine trial, as well as the Janssen ENSEMBLE 3001 trial. So having a lot of support on the ground with Javara integrated into our clinical atmosphere helped us get patients involved and enrolled in these trials.”

Ron Blair has nearly 30 years of experience caring for pediatric patients. His practice in Northern Texas, Forest Lane Pediatrics, has a primary focus on infants to age 19, but also includes a multi-specialty group with internal medicine, family practice, and OB-GYN among other specialties. Blair began working with Javara earlier than the other two practices, and he said the relationship has benefited his patients, in addition to being fun and interesting. “We’ve taken a step-by-step approach with a lot of guidance from Javara because our group didn’t have extensive experience with [clinical trials]. We spent time training our clinical investigators and preparing a nice portfolio of our different specialties,” said Blair.

For the patients, Kennelly thinks they have a better sense of support when they are involved with research. “For some of these trials, we’re seeing patients once every other month, but in between, we’re talking to them on the phone. Sometimes once or twice a week, sometimes every day for a couple of days for short periods of time. That allows them to voice their concerns and ask questions, and it allows more interactions for the physician or the PI or sub investigator. The patients also interact with the clinical trial navigators and assistants. Overall, the patient does enjoy the experience and when integrated with primary care and their own PCPs, I think clinical trial retention rates are higher because of the attention from their provider.”

As predicted, Grayson said their staff spent time with patients helping them understand their clinical research options. “I did notice many patients, in some respects, still have a lot of mistrust for the medical community. But I have found that they actually do trust their provider. And if we come to them and talk to them about the benefits of the research, they trust that coming from their own provider,” she said. Grayson also sees that the patients are excited to participate when asked, and spread the word to friends and family. Because of the practice population, and history of underrepresentation, Grayson believes that the clinical research information and understanding for them is enlightening. And she believes that in the bigger picture, it is important to continue to try to include these populations.

Blair’s practice initially sent queries to patients in the form of a survey asking if they would be interested in participating in relevant clinical trials. The response was more enthusiastic than they predicted. “When we interview people, there are several questions about clinical research. Our patients trust our ongoing focus on their continuum of care and gladly share appropriate information relevant to potential clinical trials. So it’s been very good for the patients and good for my staff and good for the other physicians involved.”

Blair, who did have exposure to clinical research during his residency training, is proud of the number of physicians who signed on for clinical investigator training. “It’s pretty exciting for all of us to be involved in contributing to the fund of knowledge. And also that we’re able to provide services and potential treatments to our patients that we would not have been able to previously.” Blair credits Javara for opening doors to research for practicing physicians that previously was just in the domain of academic institutions.

Physicians share their experiences integrating research into practice.

Bringing Clinical Trials to the Point of Care

For years, physicians and medical students, most of them people of color, have tried to highlight the scarcity of images of black and brown people in medical curricula. A study published in 2018 that reviewed over 4,000 images in textbooks that are commonly used in top medical schools, such as 

, found that only 4.5% of images represented dark skin tones.

 As such, while the formal medical curriculum clearly emphasizes equality of care, this message is undermined by the poor representation of people of color in textbooks, case studies, and training materials. Critically, this uneven representation that places a white person as the normative patient has been identified as a significant contributor to racial inequality in health care experience, treatment, and patient outcomes.

Although the underrepresentation of images of people of color in the medical curriculum is an issue that affects training in every branch of medicine, it is especially problematic for dermatology where diagnosis and assessment of the severity of a condition depends almost entirely on the appearance of the skin. In the US, coverage of dark skin at national meetings and in images included in core dermatology educational resources is limited and variable.

 A study published this year focusing on dermatology textbooks found that only 11.5% of images showed dark skin.

 This is echoed by dermatologists and dermatology residents in the US, who report that they have been inadequately trained in identifying conditions on dark skin, and see the need for greater exposure to images of people of color in training materials.

Recently, there has been a growing movement online aimed at tackling this issue. Brown Skin Matters (

) is an Instagram account with reference images of dermatological conditions on non-white skin, aiming to help people of color identify skin conditions. It was launched in 2019 by Ellen Buchanan Weiss after her son, who is mixed race, broke out in a rash and she could not find any images online that matched what she was seeing on his skin. Last summer, Malone Mukwende, a second-year medical student from St. George’s Medical School in London, cowrote a handbook named 

, which aims to raise awareness on how symptoms and signs of conditions can manifest differently on dark skin. Multiple articles featuring these initiatives as well as highlighting the need for better representation of dark skin in dermatology training have followed, including pieces in 

This online movement demonstrates that, unlike other pervasive economic,

 to health for people of color, the underrepresentation of dark skin in training materials can be remedied. By improving the tools and education provided to clinicians, they can be better positioned in diagnosing and treating skin conditions in people of color. In addition to improving standard of care, diversifying training can provide significant benefits to clinical research in dermatology. For a trial to yield the most meaningful results that are applicable across the entire patient population, assessments supporting endpoints need to be measured in the most accurate and consistent manner.

Atopic dermatitis is a common chronic skin condition that typically presents during early childhood but can persist into adulthood. Due to a complex interplay of genetic and environmental factors, the immune system becomes overactive, triggering inflammation that damages the skin barrier. This leaves the skin dry, itchy, and scaly. Atopic dermatitis can often create a vicious cycle where children itch and scratch and itch and scratch, causing further inflammation and damaging the skin. Black skin is significantly associated with the presence of this condition,

 and Black children are more often seen by clinicians for a diagnosis of atopic dermatitis compared to white children,

 suggesting either an increased prevalence or severity.

In clinical trials the effectiveness of a medication in treating atopic dermatitis is determined using clinician-reported outcome measures, such as the Investigator Global Assessment (IGA) and the Eczema Area and Severity Index (EASI). For the IGA, the clinician scores the overall appearance of the skin affected by selecting one of five severity grades. Achievement of IGA 0 (clear) or 1 (almost clear) has been the primary definition of treatment success. The scoring process for the EASI is more extensive. For four different body areas (head, trunk, arms, and legs) the clinician evaluates how much of the skin is affected and how intense the characteristic signs of the condition are. These signs are erythema (redness), induration (thickening), excoriation (most likely due to scratching) and lichenification (i.e. how leathery, akin to a lichen, the skin appears). A total score is then calculated by taking into account the area affected and the severity of the signs. What is common in these and other clinician-reported outcome measures in dermatology is that they very much depend on the clinician’s judgement.

The inherent subjectivity of these measures often results in disagreement between clinicians’ ratings on the severity of a patient’s condition. Hanifin and colleagues (2001)

 tested the reliability of the EASI by exploring score agreement between clinicians (inter-rater variability) and within the same clinician across time (intra-rater variability). To achieve this, 15 dermatologists assessed 20 children and adult patients with atopic dermatitis twice over two days. Overall, inter- and intra-rater variability for the EASI total score was found to be fair-to-good. However, when exploring the scores for each individual sign of atopic dermatitis independently, agreement between the raters was evidently poorer: thickness, scratching, and lichenification showed poor or fair inter-rater variability, with only erythema crossing the threshold to good for both assessment timings. Other studies exploring the reliability of clinician reported measures for atopic dermatitis have found similar results, with scores on the most commonly used assessments in clinical trials showing either poor or moderate agreement between clinicians (e.g. Silverberg et al. (2021)).

Studies have specifically focused on how agreement in clinicians’ scores on dermatology assessments differ across skin types. When it comes specifically to patients of color, rater variability has been found to be disproportionately high for dark skin. For example, Zhao and colleagues (2015)

 compared the reliability of clinician scores on the most common assessments used in clinical trials for atopic dermatitis, including the EASI. They found that across all assessments, inter-rater variability was higher the darker the skin of the patient being assessed, and that reliability was poorest for patients with highly pigmented skin. A significant part of this disagreement was due to a high degree of variability in clinicians’ scores of erythema on highly pigmented skin. When erythema was excluded from the assessment of disease severity and the score was adjusted, disease was found to be significantly more severe. These results echoed the well-reported challenge that dermatologists have detecting erythema in heavily pigmented skin,

 resulting in patients with dark skin that have cutaneous diseases such atopic dermatitis being underdiagnosed and undertreated.

For clinical research in dermatology to yield meaningful results applicable across the disease population, the most relevant outcomes–such as the EASI in atopic dermatitis–need to be measured in the most accurate and consistent manner. Critical to this is ensuring that every clinician rating disease severity understands the scores in the same way and administers the assessments in the same way every single time. Training raters who will administer the assessments prior to the initiation of a clinical trial can ensure their scores of patients’ disease severity during the trial are calibrated, reducing variability. Rater training has been used extensively for clinicians assessing patients in clinical trials on central nervous system disorders, where outcomes are often semi-structured interviews that rely heavily on clinical judgement,

 but only recently has been identified as important for endpoint quality in dermatology clinical trials.

In a recent study, Olt and colleagues (2019)

 investigated the impact of standardizing training on the EASI for clinicians participating in a US nationwide trial. Clinicians were trained on a detailed explanation of the assessment, along with consensus building exercises with expert trainers that involved example images with varying severity of atopic dermatitis signs. The participating clinicians then took part in a test-retest certification test aimed to establish competence and determine inter-rater variability. This certification exercise consisted of two sessions, 5-10 days apart, where a set of case studies with different disease severity were presented, and the clinicians were asked to rate them. The findings demonstrated that variability in clinician’s EASI scores were significantly reduced after they received training, clearly showing that standardized rater training can align clinical judgement thus improving data reliability and quality.

Given the underrepresentation of dark skin in the medical curriculum,

 and the increased rater variability observed when assessing dark skin,

 it is important to ensure that rater training materials for dermatology clinical trials are diverse and sufficiently represent all skin types. This is vital for making sure disease severity and treatment effects are accurately captured for patients of color participating in clinical research. However, although there are textbooks such as the 

 that contain high-quality images of dermatological conditions on darker skin, there is no standardized image library for rater training that illustrates how signs manifest and progress with disease severity across different skin types. Issues with images currently used in rater training range from poor image resolution and artefacts obstructing the affected area, to limited depiction of key anatomical areas affected by disease.

To address this issue, Signant Health gathered a multidisciplinary team of graphic artists, scientists, and expert clinicians to develop a set of training images for clinical research. The team developed high resolution, photo-realistic images of the different signs of atopic dermatitis across severity levels and skin types which can be seen below. These images capture the progression of the signs of atopic dermatitis in common anatomical areas affected by the condition (e.g. inside of the elbow and back of the knee), with the affected area being represented without obstruction. By using this set of images, clinicians can be trained to identify and rate otherwise difficult signs such as erythema on darker skin. Training on such a diverse set of images has the potential to increase the reliability of clinician reported measures in dermatology clinical trials.

Clinical trials are essential in contemporary evidence-based medicine, as they generate evidence on the safety and efficacy of new therapies and treatments. Diversity of participants in clinical trials is critical to ensure that the trial population is representative of the patients who will be using the treatment being tested, and that the findings are generalizable. Although historically racial and ethnic minorities have been underrepresented in clinical research across therapeutic indications,

 major efforts have been made in the US by the FDA and the Revitalization Act of 1993. This has led to a steady increase of dermatological trials involving ethnic minorities.

 As such, diversity in training materials for clinicians taking part in a clinical trial, ensuring they are well positioned to judge treatment effectiveness across skin types, is critical.

Louie, P. & Wilkes, R. (2018). Representations of race and skin tone in medical textbook imagery. 

Martin, G. C., Kirgis, J., Sid, E., & Sabin, J. A. (2016). Equitable imagery in the preclinical medical school curriculum: Findings from one medical school.

Ebede, T., & Papier, A. (2006). Disparities in dermatology educational resources. 

Journal of the American Academy of Dermatology

Adelekum, A., Onyekaba, G., & Lipoff, J. B. (2020). Skin colour in dermatology textbooks: An updated evaluation and analysis. 

Buster, K. J., Yang, L., & Elmets, C. A. (2011). Are dermatologists confident in treating skin disease in African Americans? 

Journal of Investigative Dermatology: Meeting Abstracts

Williams, D. R., Yu, Y., Jackson, J. S., & Anderson, N. B. (1997). Racial differences in physical and mental health: Socio-economic status, stress and discrimination. 

Dressler, W. W., Oths, K. S., Gravlee, C. C. (2005). RACE AND ETHNICITY IN PUBLIC HEALTH RESEARCH: Models to Explain Health Disparities. 

Brondolo, E., & Gallo, L. C. (2009). Race, racism, and health: Disparities, mechanisms, and interventions. 

Shaw T. E., Currie G. P., Koudelka C. W., & Simpson E. L. (2011). Eczema prevalence in the United States: data from the 2003 National Survey of Children’s Health. 

Horii K. A., Simon S. D., Liu D. Y., & Sharma V. (2007). Atopic dermatitis in children in the United States, 1997-2004: visit trends, patient and provider characteristics, and prescribing patterns. 

Janumpally S. R., Feldman S. R., Gupta A. K., & Fleischer A. B., Jr. (2002). In the United States, blacks and Asian/Pacific Islanders are more likely than whites to seek medical care for atopic dermatitis. 

Hanifin, J. M., Thurston, M., Omoto, M., Cherill, R., Tofte, S. J., & the EASI Evaluator Group. (2001). The eczema area and severity index (EASI): Assessment of reliability in atopic dermatitis. 

Silverberg, J.I., Lei, D., Yousaf, M., Janmohamed, S. R., Vakharia, P. P., Chopra, R., Chavda, R., Gabriel, S., Patel, K. R., Singam, V., Kantor, R., & Hsu, D. Y. (2021). Measurement properties of the Rajka-Langeland severity score in children and adults with atopic dermatitis. 

Zhao, C. Y., Wijayanti, A., Doria, M. C., Harris, A. G., Jain, S. V., Legaspi, K. N., Dlova, N. C., Law, M. G., & Murrell, D. F. (2015). The reliability and validity of outcome measures for atopic dermatitis in patients with pigmented skin: A grey area. 

International Journal of Women’s Dermatology

Chansky, P. B., Mittal, L., & Werth, V. P. (2018). Dermatological evaluation in patients with skin of colour: The effect of erythema on outcome measures in atopic dermatitis. 

Ben-Gashir, M. A., & Hay, R. J. (2002). Reliance on erythema scores may mask severe atopic dermatitis in black children compared with their white counterparts. 

Becker, R. E., Greig, N. H., & Giacobini, E. (2008). Why do so many drugs for Alzheimer’s disease fail in development? Time for new methods and new practices? 

Olt, J., Khan, R., Sanderson, B., Feaster, T., Solomon, T. S., Barbone, J. M., Platko, J. V., Bodart, S., Garner, K., & Byrom, B. (2019). Clinician training reduces variability in clinician-reported outcomes of skin surface symptoms in a dermatology study. 

Advani, A. S., Atkeson, B., Brown, C. L., Peterson, B. L., Fish, L., Johnson, J. L., Gockerman, J. P., & Gautier, M. (2003). Barrier to the participation of African-American patients with cancer in clinical trials. 

Spears, C. R., Nolan, B. V., O’Neill, J. L., Arcury, T. A., Grzywacz, J. G., & Feldman, S. R. (2011). Recruiting underserved populations to dermatologic research: A systematic review. 

Clinical Vice President, Internal Medicine, Signant Health, 

Poor representation of dark skin tones in textbooks emphasizes need for change.

Properly Training Physicians in Dermatology Trials

From Prague to Minneapolis to Dubai, clinical trials are increasingly global—and that makes logistics, now more than ever, a mission-critical factor for conducting a successful clinical trial. However, if there are delays during the clinical trial phase, the financial impact can be staggering.

While any number of factors might cause delays, from strategic challenges to commercial barriers, logistics can play a key role. Every delay, from equipment not arriving at a clinical site on time to patients unable to arrive for an onsite visit, creates an avalanche of effects, from decreased patient retention to increased time
to market.

As with other aspects of clinical trials, the COVID-19 pandemic severely impacted the logistics that fuel the supply chain. By July 2020, almost 200 companies had stopped or delayed their clinical trials because of the pandemic,

 and it’s estimated that about 80% of non-COVID-19 clinical trials were interrupted or stopped.

 As the pandemic continued, with delays continuing for months, trials that were in progress were hampered as any inventory redundancies built into their supply chain eroded.

The pandemic—and the upheaval that came with it—underscored gaps in clinical trial logistics. It also created opportunities for organizations to reimagine the process for creating more efficient, reliable, patient-centric clinical trials.

Before the COVID-19 pandemic, many sponsors and CROs had already begun to leverage digitalization to operate more efficiently and prevent costly downtime. As the need to quickly and safely develop COVID-19 vaccines and treatments emerged, organizations needed visibility into their processes as well as the full supply chain. Sponsors and CROs already using digital solutions were better positioned to make that pivot quickly because they already had real-time transparency to make strategic logistics decisions.

In COVID-19’s wake, sponsors, CROs and their logistics partners will need to continue and even expand visibility into every logistics touch point, ensuring supply chain integrity. Along with making sure shipments meet regulatory guidelines, the “Amazon effect” has also increased visibility expectations. Everyone along the supply chain, including clinical staff and patients, want to know not only where their supplies and equipment are, but precisely when they will arrive.

In addition to the expectation for increased visibility, there’s a growing need for flexibility. Traditionally, sponsors and CROs have relied on recruiting parameters based on numerous factors, from regional patient populations to a disease’s prevalence in the population. Predictions help organizations ensure that they are sending the right kits to the right clinical trial sites. Miscalculations can lead to oversupply at one site and shortages at another.

Digitalization tools can provide the transparency needed to overcome these challenges. For example, a kit with a scannable label can be tracked across the entire supply chain, from the moment it leaves the kit assembly line to the patient’s home and finally to the biorepository. Machine learning tools can take the process a step further by considering various factors, like capacity or hours of service, across multiple supply chains. Radio-frequency identification can also help manage shipments needed to service these clinical trials.

These capabilities provide dynamic, multi-mode estimated time of arrival information, whether a package is delayed at a border crossing or five blocks away from a patient’s home. End-to-end visibility enhances the patient experience but can also create the tracking and traceability needed to meet regulatory demands.

Maintaining regulatory compliance in emerging regions

As the COVID-19 pandemic created the need to fast-track vaccines and treatments, emerging geographies, like the BRICS block (Brazil, Russia, India, China and South Africa) and the Middle East, became important locations for related clinical trials. While their large, diverse populations are ideal for conducting multiple, large-scale trials in parallel, the regulatory process in these nations is still evolving. This creates a challenging regulatory landscape for logistics.

From clinical trial approvals to transporting clinical supplies and medical equipment, regulations can vary greatly from country to country. Regulations for transporting clinical trial products and medical equipment can be inconsistent, making it more difficult to plan and coordinate across jurisdictions, especially if they are governed by different regulatory organizations. For example, different transportation modes within an area might require specific types of paperwork to be secured. In addition, the timelines in emerging markets can run much longer than what might be considered standard when conducting trials in many Western nations. Even in well established markets, regulations change and the supply chain needs to adjust to new regulatory standards, such as EU MDR regulation in Europe that came into effect May 2021.

As clinical trials move forward, CROs and sponsors need to fully understand clinical trial regulations in every jurisdiction in which they operate. Working with local trial coordinators or partners who understand each region’s unique logistics challenges can help organizations understand regulations within all relevant jurisdictions to avoid the inadvertent violations and help trials stay on track.

In many aspects, the logistical challenges common to traditional, on-site clinical trials are also evident in those that are hybrid or virtual—albeit on an exponential scale. For example, rather than delivering equipment to a dozen sites for a specific trial, a decentralized trial might require thousands of individual shipments to patients’ homes.

Logistical complexity goes beyond simply making sure the right patient gets the right kit at the right time. Other factors might include coordination and pickup of biological samples from patients, or the return of equipment or perhaps materials that are partially used, unused or even expired. And extending beyond logistical complexities, data compliance regulations, such as HIPAA or GDPR, expand further back in the supply chain as partners need to handle patient data that enables home delivery of equipment as well as labeling for sample collections.

Sponsors and CROs may want to consider partnering with specialized companies with the resources and experience to manage direct-to-patient shipments, no matter where the supplies or equipment is being sent. These types of partnerships can help ensure the sponsors or CROs can focus on clinical trial design and outcomes as well as patient experience.

Mobile health (mHealth) is one tool helping facilitate clinical trial logistics. Two-way communication medical wearables, like smartphone apps, patches or other monitoring sensors, can measure essential biometric data. In addition to providing clinical staff with accurate, real-time health data, these devices help to reduce or eliminate the need for in-clinic visits, making it easier for trials to continue even in the face of unexpected macro events. Patients also experience a greater degree of independence because the technology reduces or eliminates the need for clinic visits, which helps increase retention. mHealth devices can reduce costs, too, by decreasing the time and expense related to in-clinic visits.

Wearable medical device usage is perhaps one of the most exciting aspects of the clinical trials of the future. mHealth devices are currently in the first generation of development. As developers continue to refine the technology, it will evolve, much like the apps consumers use on smartphones. CROs able to leverage this new technology by acquiring or partnering with software companies can help move innovation forward to improve the trial’s efficiency and the patient’s experience.

Delivering training in a decentralized clinical trial

Logistics is more than the movement of people and products; it’s also about the movement of information. As COVID-19 led to wider adoption of decentralized clinical trials, sponsors and CROs were prompted to find effective ways to deliver the training patients need to participate in their care. In traditional clinical trials, a recruited staff would receive any relevant training at the team level. However, hybrid and virtual trials require the delivery of that information to each individual patient.

For example, clinical teams can transmit alerts to a patients’ wearable or medical device to remind the patient to conduct a test or provide a sample. An app might also deliver information, like instructions, so if the patient doesn’t understand a process, they can view a step-by-step how-to guide or even contact off-site, 24/7 support.

Data and cybersecurity in logistics is a concern that will become more critical in the near-term. In traditional clinical trial site settings, patients’ private information is blinded from supplier, service and logistics partners. For example, a repository sample might be shipped with a patient information rendered as a code.

Now, hybrid and virtual trials require partners to ship directly to or pick up directly from patients, requiring partners to have access to a range of personal information, from the patient’s name and address to the study type to the serial number of the equipment used. Data that is not properly secured can create cybersecurity risks that potentially expose confidential patient information as well as violate regulatory standards.

In addition to data and cybersecurity compliance with GDPR in Europe and HIPAA in the United States, sponsors, CROs and their logistics partners must navigate emerging regions where the intersection of virtual trials, data and cybersecurity is still in the early stages of development.

No matter how quickly the clinical trial landscape changes or where those changes lead the industry, there is one factor that will not change: expect the unexpected. There is simply no way to predict every unforeseen event. Within the last few years alone, logistics within the pharmaceutical industry, and clinical trials in particular, have been challenged with events ranging from COVID-19 to Brexit to the vessel that temporarily blocked one of the world’s busiest trade routes, the Suez Canal.

The unexpected will continue to challenge organizations to maximize robust, flexible logistics that ensure supply chain integrity—and those in the clinical trials space will rise to meet that challenge and leverage the opportunity it brings. Whether supplies are being shipped to a patient’s home or equipment is being moved from one clinical site to another, reliable logistics is a key factor in creating an efficient and reliable patient-centric clinical trials.

Adams, B. Fierce Biotech. (Online) Available at: 

https://www.fiercebiotech.com/biotech/more-than-two-thirds-trials-hit-by-covid-enrollment-halts-midstage-tests-worst-affected#:~:text=Drilling%20down%20into%20the%20numbers,impacted%20due%20to%20slow%20enrollment

Van Dornb, A. COVID-19 and readjusting clinical trials. Available at 

https://www.thelancet.com/journals/lancet/article/PIIS0140-6736(20)31787-6/fulltext 

COVID-19 provides unique opportunity for overhaul of logistics.

Moving into the Future of Clinical Trials

Since the turn of the century, the pharmaceutical industry has actively supported the steady increase in the use of digital health technologies, including the important transition from paper-based health records to electronic health record systems (EHRs). An increasing proportion of health data is now digital (known from a regulatory perspective as eSource), bringing benefits to patients and clinicians alike.

While these advances in healthcare data have been mirrored in clinical trial settings, healthcare and clinical research activities remain, overwhelmingly, in separate worlds. Estimates are that 70%

of clinical trial data is duplicated between electronic data capture (EDC) systems used for clinical trials and EHRs. The current methods for transferring this data continue to be manual, open to transcription errors, hugely wasteful and, ultimately, severely restricting to our ability to trial and launch potentially life-saving treatments for patients.

As an illustrative example, in a typical late Phase II/Phase III oncology trial encompassing around 200 patients, an average of 3.5 million data points will be entered into the EDC. Current methods involve a manual re-keying of a large proportion of this data from the EHR to the EDC, copying from screen to screen. This is followed by a manual data quality check known as source data validation (SDV), where it is not unusual for the clinical research associate (CRA) to also be accompanied by a hospital study coordinator. At each stage, time, effort, and costs multiply. In fact, around 20% of the total costs of a study (which can translate to between $16M-$24M

) is allocated to duplicating and verifying data.

The potential for a different approach—EHR2EDC

The idea that the current approach is less than optimal is not a new one. Attempts have been made to achieve an electronic transfer of data from EHR to EDC systems going back up to 30 years. However, previous efforts have been highly localized, bespoke solutions that only work between specific (often in-house) systems, and so have not realized the benefits we need at scale.

Now, with a growing network of eSource-ready hospitals, advances in technology, and a growing imperative due to the increasing complexity and cost of clinical trials, a tipping point has been reached. High quality, structured data is now available; connectivity has seen huge improvements; and adoption of systems designed for interoperability is fast becoming the norm. Achieving a seamless transfer of data from EHR to EDC is now not only possible, but essential.

As Table 1 shows below, the cost savings that could be achieved in a typical oncology trial by using an automated transfer of data from EHR to EDC (referred to as EHR2EDC) in place of the current manual re-keying and verification, could result in a cost saving of $15,000 per patient.

We must also consider the time saving benefits–a staggering 87,500 hours in our average 3.5 million data point study—in a climate where every day that a drug is delayed from market, sponsors lose up to $8 million

, but also delays patient access to a potentially valuable new treatment.

Over the last decade the stage has been set for EHR2EDC. A potted history of some of the work in this space includes:

The Electronic Health Records Systems for Clinical Research (EHR4CR) project ran from 2011-16.

 Under the umbrella of Innovative Medicines Initiative (IMI), this project involved numerous research institutions and companies including AstraZeneca, GlaxoSmithKline, Merck and Sanofi.

 It established an ethically acceptable mechanism to tap into the emerging opportunity from the digitization of patient records for clinical study design and recruitment. The result was a technical proof of concept implementation and a governance framework for remotely and securely querying EHRs to validate protocols and select the best study sites. The project found that estimated efficiency gains through accelerating the time to market for a typical Phase II or III oncology trial could translate to benefits for the global pharmaceutical oncology sector of between $54.2 million and $2516.8 million (depending on level of application).

In 2016 The European Institute for Innovation through Health Data (i~HD) was formed

 to promote, develop and share good practices and tools, and leverage multi-stakeholder cooperation in the trustworthy use of high-quality health data. i~HD provides training, education and certification programs to ensure the quality and good governance of organizations handling health data.

In 2017 concerted efforts began to move on from clinical trial design and recruitment to study conduct.

 consortium was a collaborative effort driven by Sanofi and i~HD, industry partners, hospital partners, and technology providers, to promote and catalyze the most efficient and trustworthy uses of health data and interoperability. It has developed standards, mapping, and validation for the use of automatic data capture from hospital records into EDCs.

 ran from 2018-2019. Sanofi, AstraZeneca, Jansen and UCB worked with four hospitals in four different European countries to define requirements and plug in technology to run mirror studies of real-world clinical trials from different sponsors. Using ‘Insite’ software, the study aimed to prove that at least 15% of data usually manually entered could be automatically transferred under control of the investigator. The study significantly over-delivered on this goal, and it was found that 37%

 of the necessary data could be successfully transferred.

These program studies and developments have demonstrated that it is possible, not only to achieve an electronic transfer of a significant proportion of data from EHR to EDC, but to do this in a secure manner, with patient data remaining on site.

Aside from widespread adoption of electronic records in hospitals, the technical blocker to achieving EHR2EDC has historically been the absence of a scalable solution that would apply across multiple platforms, multiple trial sites, and for multiple sponsor requirements. Bespoke solutions developed to date would require too much adaptation and too much support to be commercially viable at scale.

In recent years HL7 FHIR has emerged as a standard format for packaging health data. A pivotal turning point was the US government’s 2016 

, which requires that all new EHR systems developed in the US use HL7 FHIR. This has paved the way for a new level of interoperability between different systems.

Further, the development of SMART on FHIR–an application programming interface (API)–which acts as the conduit for transferring data from one system to another–has completed the puzzle on the healthcare side to allow the development of software that can be scaled for use across multiple platforms and systems.

Regulators such as FDA and EMA have published guidance in recent years about the quality criteria and provenance metadata they would require in order to accept imported EHR data as valid eSource, to be included within regulatory submissions. EHR2EDC specifications align with and formalize this guidance as EHR system requirements and EHR metadata.

A common concern around system interoperability is in the reliability or suitability of the source data, to support highest quality standards required for clinical research.

Data such as laboratory data, medical history, adverse events, vital signs, demographics, medications, and more, is structured by design and high quality. This has been validated by studies conducted by the EHR2EDC consortium (TransFAIR

 paper, that showed that between 37% to 54% of data in key structured data domains can be successfully sourced from the EHR.

The value of automating this structured data is high as it accounts for a considerable percentage of the data that is currently manually replicated in a typical clinical trial. When this is combined with a dramatic reduction in transcription errors (therefore higher quality data and reduced need for monitoring), the value for both hospital and sponsor is obvious to see.

A notable example of the potential of HL7 FHIR and SMART on FHIR is being demonstrated now in a partnership between AstraZeneca and IgniteData, as shown in Figure 1 below. IgniteData’s software, ‘Archer’ makes powerful use of HL7 FHIR and SMART on FHIR to provide a solution which can be adapted to work between different EHR and EDC systems. Running Archer in parallel with traditional methods, the project is already meeting critical success factors and will test and measure the efficiencies gained in time, cost and effort. Initially being deployed at two leading NHS hospitals, it is worth noting that enthusiasm from the hospital community has been high, with, essentially, a waiting list of hospital sites in line to be involved as the project scales.

In parallel, because of work by i~HD, Sanofi and other members of the EHR2EDC consortium, an eSource-readiness tool is being developed and to be made available this year. Based on the TransCelerate Site Capability Questionnaire and eClinicalForum eSource-Readiness Assessment Tool, this will allow hospitals to check for themselves whether they are ready to welcome this new era of clinical trials.

i~HD have also recently launched an updated quality accreditation scheme for vendors of EHR2EDC software, ensuring good practice and compliance, with the latest data protection thinking built in. Vendors such as IgniteData are working closely with them to consult, where required, on the design of this scheme to ensure it is fit for purpose, and to build commitment and industry buy-in.

Learnings so far, particularly from the TransFAIR study in 2018/19, point to the vast benefits that could be gained from widespread use of automated EHR2EDC technology, exemplified in oncology studies. Research points to the highest benefits in oncology due to the:

Large numbers of active studies. Globally, oncology is the domain where we see the largest number of clinical trials by far, with over 20,000 oncology trials currently recruiting or not yet recruiting.

High number of data points (10-15,000 per patient).

High use of local laboratory data for speed and safety reasons, resulting in high numbers of data points entered manually. (Conversely, studies heavily using central laboratory data have been shown to have less data points entered manually).

The ability to acquire data in near real time for these studies will not only save time and cost, but allow for patient safety and treatment assessments to be made more quickly and with a higher level of confidence, hence improving safety monitoring of patients in trials.

Furthermore, we believe that using real world data more broadly in clinical trial design, recruitment and execution will enhance the generalizability of new drugs. The resulting new dialogue will inform protocols and produce trial results that are more closely matched to the real world.

From the hospital perspective, those taking advantage of EHR2EDC technology will only stand to gain. By removing the painful task of manual data entry, sites will immediately become more efficient, attractive and competitive places to conduct research. The end result will be increased ability to conduct larger numbers of studies and introduce wider variety to the studies they take part in, including opening up capacity for studies that would otherwise not have taken place. And, as using this technology will increase focus on data quality, a virtuous circle will result, with increased quality and increased quantities of data available for automatic transfer feeding off each other.

Finally, transitioning from siloed, manually duplicated data entry into streamlined data collection from EHR records will reduce the current gap between care and research, and enable clinical trials to become treatment options with direct benefit to patients.

Critical to the successful cross-industry scaling of this technology will be:

An expanding consortium of sponsors, hospitals, regulators, and technology providers, all actively collaborating to create the conditions where the whole industry can realise the benefits of this shift.

Governance to promote use of open source, transparent mapping rules, enabling all stakeholders to adopt standard interoperability rules and build confidence and trust in data quality.

Increased capability and focus on data quality in hospitals, with eSource-readiness becoming the norm. This will require collaborative effort (including, in some cases, funding), but the end benefits are too great to overlook. The potential exists for pre-competitive collaboration to sponsor sites that wish to invest in technology and training for staff.

A federation of approved vendors vetted for compliance and ethics.

The potential for a paradigm shift in how we conduct clinical trials has already been proven. The time for separation of the worlds of healthcare and clinical trials is over. What is needed now is collaborative action between the healthcare and research communities to bridge the gap between the two worlds, for the benefit of patients.

We believe that the use of hybrid studies (where eSource capability is introduced for a proportion of the collected data) and a stepwise approach will be the key to accelerating the unlocking of the full potential of EHR2EDC technology. A few years ago, we all agreed that electric cars were the future. We have since witnessed widespread adoption of hybrid cars, which has, in turn, opened the floodgates to the advances needed to achieve the ultimate vision of efficient fully electric cars. Similarly, our industry cannot wait for 100% readiness to switch on the lights of EHR2EDC technology.

And we are, in fact, already in a position where we can see huge benefits from using the power of this technology in many settings. Even if only 10% of sites involved in a typical oncology study deployed EHR2EDC technology, with the remainder using more traditional methods, significant gains will be seen across all stakeholders. If the technology was used to transfer a limited set of 30% of structured data points in a study, think of the benefits all stakeholders would see from reduction in errors, time, and cost. The unmissable opportunity for all players in the clinical trials space cannot be overstated, so the time for sitting on the sidelines of this revolution really is over.

The path forward should be focused on pre-competitive collaboration with vendors, hospitals, pharma and regulators to create the first 100-strong EHR2EDC-ready hospital network across therapeutic areas. This will truly demonstrate how we can transform the way we do clinical trials.

EDC site survey: investigational site perspectives on clinical trial information systems eClinical Forum (2009) (

New Research Emerges to Challenge Steep Costs of Clinical Trials (

De Moor G, Sundgren M, Kalra D, Schmidt A, Dugas M, Claerhout B, Karakoyun T, Ohmann C, Lastic PY, Ammour N, et al. Using electronic health records for clinical research: The case of the EHR4CR project.

Beresniak et al, “Cost-benefit assessment of using electronic health records data for clinical research versus current practices: Contribution of the Electronic Health Records for Clinical Research (EHR4CR) European Project” 

http://dx.doi.org/10.1016/j.cct.2015.11.011

Kalra, D., Stroetmann, V., Sundgren, M., Dupont, D., Schlünder, I., Thienpont, G., Coorevits, P., and De Moor, G. (2016) The European Institute for Innovation through Health Data. 

EHR2EDC - EIT Health - Activity ID 18269 - This project received funding form EIT Health

https://www.i-hd.eu/rd-and-collaborative-projects/ehr2edc/

Griffon et al 2020, _EHR2EDC_Digital Personalized Health & Medicine

Buckley MT et al 2021, Direct Data Extraction and Exchange of Local Labs for Clinical Research Protocols: A Partnership with Sites, Biopharmaceutical Firms, and Clinical Research Organizations

 Health Data Science Director, Data Science & Artificial Intelligence, Bio- Pharmaceuticals R&D, AstraZeneca, 

Global Lead External Engagement, Clinical Innovation Office/Clinical Science & Operation, Sanofi R&D, 

Professor, President, The European Institute of Innovation through Health Data, and 

Advances in technology open door for improved EHR to EDC transfer process.

Innovations in Data Capture Transforming Trial Delivery

Our apologies to those who still wince when reminded of the following figures.

But because these data illustrate successes, or lack thereof, of clinical trials from the past, they serve as an outcomes baseline for the future: Will future outcomes be based on the types of protocols used in the COVID-19 vaccine trials, or will results be a carbon copy of pre-2020 study figures?

Between 1998 and 2015, Hwang et al. found that of 640 novel therapies, 54%, or 344 therapies, failed in development; the FDA approved 36%, or 230. Most failed because they didn’t reach their endpoints, while 17% were pulled for safety reasons. The remainder were abandoned for unexplained commercial issues. The common denominators among the approved therapies: orphan designations and mega-sized company sponsors. Only 10% were approved in other countries.

Postapproval figures are also worthy of note: Of 222 novel therapies approved between 2001 and 2010, 123 of them were named as the cause of a postmarket safety event; three were eliminated from the market, 61 received boxed warnings, and the rest were the subject of an FDA safety communication.

Techniques that were demonstrated in COVID trials, many of which are decades old, could help stop the wincing. By using different trial designs, such as master protocols; using biomarkers on a regular basis to ensure accurate populations; adopting a new mindset about the purposes behind Phase I and Phase II trials; and giving investigators the time and tools to learn new skills—a shift could happen, said those interviewed.

For example, the Recovery trial, the University of Oxford’s mammoth intent-to-treat COVID-19 study, has various stakeholders, including the Gates Foundation and the Wellcome Trust. Designed for flexibility so investigators can make real-time decisions once an arm produces data, be it thumbs up or down, the protocol puts no restrictions on enrollee numbers or their ages. When dexamethasone proved helpful, it became a standard of care. When the opposite proved true of hydroxychloroquine, that trial arm was dropped. “There was a rolling review,” said Brigid Flanagan, founder of Oriel Research Services, Ltd. “There is no reason it can’t be done going forward.”

Different stakeholders have different definitions of success, said Bill Barry, PhD, senior statistical research scientist, Rho Inc. They will all approach the trial design differently—intent to treat? Delineate which subset will see the best treatment results? To make an umbrella or basket trial work, they need one strategy to rule them all. “Reaching consensus is the challenge.”

So while the technology is willing, the human buy-in could be termed weak. Humans tend to act unscientifically on occasion—like extending a trial whose drug has no future because of heavy emotional investment. That is not evidence-based decision making, said Mike Rea, founder and CEO of Protodigm, which advocates using early trial phases for exploring what the molecule or therapy can be used for, and in what diseases, including subsets. “If you’re just collecting information to say yes,” the trial will ultimately fail, he said. “It happens a lot.”

Trials todsy are more tailored than necessary, said Ken Getz, MBA, founder and board chair, CISCRP and director and professor, Tufts Center for the Study of Drug Development, Tufts University School of Medicine. “We see trials so highly customized, introducing approaches that are unique. [But] when you try and measure at the macro level, you see variation.”

Shorter trial times. Improved patient safety. Less bias, fewer ethical concerns. More risk modification. Especially if biomarkers are involved.

In traditionally run trials, specimens go to a lab and investigators wait for the results. Today, adaptive design allows investigators to add, drop or expand arms, depending on the data, all in real time. All these, said Barry, speed up the trial’s progress. “Biomarkers give incredible new information. Once you incorporate a biomarker into a study, there is less risk of bias.” Adaptive is also considered more ethical by some because patients have better odds of getting effective treatment, quickening pace of treatment discovery.

Industry set to make choice on whether COVID-19 trials are the new standard.

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