Christine Bahls

Michelangelo, who was born in 1475, built models for his sculptures from wax and clay. The Wright Brothers, circa 1906, reportedly built a few models of the first airplane in their bicycle shop. And the Model T, so the story goes, was so named because of the 19 models (A-S) that preceded its launch in 1908.

One could argue that these geniuses created models and prototypes because they saw value in investing that time: Where were the flaws in their design? The sweet spots? How could they make their creation more beautiful, efficient, useful? The use of a model, logic would dictate, could help eliminate or minimize the risk of failure in the end result. In the above examples, the end results speak for themselves.

Of course, designing a Ferrari isn’t the same as designing a monoclonal antibody; the latter will behave differently because of human variables.

Variables aren’t anything to fear, say experts in the field of simulation; certainly they aren’t reason enough for the $1.48 trillion pharma industry

 to forgo simulation of clinical trials, or to patient-test the protocol.

Until the pivotal trials begin, lots of time exists to learn about the drug and how patients will respond to protocol demands, experts say.

Once the trials start, a sponsor is trusting fate. If one of the usually two FDA-required Phase III trials fail, says Mark Lovern, senior vice president, Certara, “you’re basically up a creek without a paddle.”

Of the differing types of simulation companies portrayed in this article—predicting drug performance in people, designing optimal protocols, or inviting patients to play-act roles in clinical trials—all say their businesses are growing and repeat customers are the norm. The case studies are impressive, highlighting money saved and FDA approvals achieved.

At Medidata, Alicia Staley, vice president, patient engagement, reports that its role-playing studio for patients—who often leave trials because of the onerous demands placed on them—has become so popular with sponsors that within two years of operation it is now a revenue producer.

Exploristics, CorEvitas, and Certara all report growth; in some cases, significant growth.

However, while significant growth is reported here, industry-wide adoption may be lacking, specifically because of time and money.

Reasons vary from a potential fear of adding more time to pre-trial investigation; queasiness over leaning too heavily on AI results; unwillingness to change long-existing exploratory and analytical procedures; and problems with communication between internal company silos. These are the reasons, those interviewed say, for why the use of simulations is still the exception, and not the norm.

Mike Rea, founder of IDEA Pharma, says the few R&D professionals he has spoken with about relying on AI-based simulation results are very wary. “I get the strong sense from R&D that they are skeptical about how far technology can drive things at the moment with AI, including simulations,” he says. AI, adds Rea, helps create ideas and run various scenarios, “but may not reliable enough to make a decision.”

While AI may not be an iron-clad decision, simulation can help point a sponsor in the right direction. Controversies abound over the efficiency and productivity of pharma R&D. In a recent analysis of 16 industry members between 2001 and 2020, the group collectively launched 251 new drugs, representing 46% of all Center for Drug Evaluation and Research (CDER)-related FDA approvals within the time period. The average total R&D expenditure per new drug was $6.16 billion.

Despite any gains that pharma might make in terms of extending lives or making those lives more livable, it is the remarkable length of time that trials take and the stunning financial outlay involved in taking a molecule from lab to regulator define pharma’s measure of success, or not. Simulators think 

trial models can help decrease time and money spent with more accurate patient selection, a more honed indication, and subsequent endpoint. “Anything you can do in the planning phase will help,” says Lovern. “You can use a model as a framework.”

“What unites people who are interested in simulations is the feeling that too much of the decision-making in drug development” is made by the medically trained who rely on their gut feelings and past experiences to make major decisions on drug development and subsequent trials, says Sam Miller, head of strategic consulting, Exploristics, a provider of biosimulation software and biostatistics services.

In short, more quantification, less qualification in the decision-making process.

PubMed doesn’t provide extensive help in assessing whether simulation of any part of the clinical trial process is, or isn’t, a keeper. There were no studies that assessed any type of simulation’s overall value. Wrote Krishnaswami et al. in 2020: “The discipline needs to continue to evolve from one‐off case studies to a paradigm of systematic, best practices‐driven approaches to improving decision-making across the [drug discovery, development, regulatory approval, and clinical utilization] continuum.”

In a recent study, researchers simulated the effects of a central nervous inhibitor called HSK3486.

 Designed as an anesthetic, HSK3486 was developed in 2019 to guide model-informed drug development (MIDD) on certain populations like infants and the elderly. HSK3486 was designed to have better anesthetic properties and less systemic exposure than the widely used propofol, which tends to stay in the liver. Using MIDD to test for exposure, the researchers found that predicted systemic exposure went up somewhat in those with hepatic impairment and the elderly, which was similar to the data gathered in a subsequent clinical trial.

FDA supports MIDD; it has done so since 2018. The agency runs what it calls its MIDD-paired meeting program, so sponsors and agency experts can discuss different modeling approaches. A successful modeling application, writes the agency, can raise the odds of a drug’s approval and help determine the right dosages for various populations “in the absence of dedicated trials.”

Certara, says Lovern, has enabled 100 novel drugs, found using physiological based pharmacokinetic modeling and simulation, to obtain label claims in lieu of clinical trials. Most are for drug-drug interactions, he says.

An Exploristics’ case study also shows simulation success. A biotech working on a molecule for a rare disorder came to Exploristics to see the probability of this molecule in a particular indication. It was showing possible efficacy in a few different ones. The biotech was looking for a Phase II trial. It had been told it needed 1,000 patients.

Miller says they ran many assumptions regarding various endpoints and different patient groups to recruit. All those scenarios showed less than 50% of probable success. So it pared down the indication and honed the endpoint to mortality. The result: a new enrollment of 180 patients, and at least 80% success rate. The results showed benefit to patients by enabling a trial that otherwise was unfeasible, says Miller.

Computer power and data retrieval have made simulation possible. Before the 20th century, the technology didn’t exist for researchers to look at bodily processes, AKA pharmacokinetics, to measure the minute amounts of drug present in blood and tissues, says Lovern. It wasn’t until the 1980s that computing power enabled analysis of the large quantities of data needed to inform predictive pharmacological models.

However, even with the technology, data at scale, remains elusive. It’s either proprietary or outrageously expensive to get from a provider. Jane Myles, program director, Decentralized Trials & Research Alliance, says that even within a pharma company itself, the silos don’t share. “Our computational vision is limited to that silo,” she notes.

Exploristics and Certara know about data limitations. Both mostly rely on public sources for data and engage teams of scientists to scour PubMed and the like. Certara uses about 30 data scientists. And Exploristics, says Miller, increases its data pool in a singular way. Its clients agree that the company can access the simulated information to add to future simulations. So far no one has said no, he says. According to Miller, Exploristics’ business has grown at least 30% year over year for some time.

Myles says audience members attending one session at the Drug Information Association (DIA) Annual Meeting in June were asked if they incorporated patient voice into their protocols. Fewer than 40% was the response—a far different percentage than found in the DIA-Tufts Center for the Study of Drug Development patient engagement studies conducted a few years ago. Asked a similar question, 65% of those surveyed said they are “investing in patient-centric initiatives in drug development.”

The following are good examples that our interviewees shared in regard to patient-centric simulations.

Five years ago, Medidata wanted to know how being patient-centered would impact clinical trial design. The company’s so-called design studio was the result. The studio, Staley tells 

, is an “opportunity for [the in-house] team to bring problems into the studio.”

The studio is in operation every month; Medidata has a set group of patient advocates and others they can call for specific disease states. Product managers, designers, and engineers bring their problems to the patient team. And these aren’t all new problems—some have been worked and reworked over the years.

One tool that has received such attention is eConsent. The patient advocates—all of whom have some disability—go through a mock scenario and assess every aspect: ease of setting up an account, language comprehension, even if the screen is presented in an “empathetic way.”

Some patient advocates have left their mark, says Staley. A lung cancer patient advocate that she worked with had been in seven lung cancer trials and had received 60 brain scans. The patient had contrast dye (gadolinium) in her brain, of which there are no clear safety guidelines to determine a maximum exposure to gadolinium, notes Staley. The clinical trial teams had not paid attention to this aspect of the patient’s care plan. A team will not act, says Staley, if information isn’t in front of them. “No one is overseeing all the data points,” she points out.

What patient simulations provide is control, notes Staley. “What we are delivering to the market is a team of patients who have looked at it, taken it apart, and put it back together. That is a cost savings right there, that gets back to industry.”

At CorEvitas, Stephanie Terrey, senior director, patient experience, has a team that gathers recruited patients, study coordinators, the principal investigators, and other physicians. An outreach manager is responsible for patient recruitment. Terrey says the protocols are at the almost finished stage. Once the patients and site staff role play key aspects of the protocol, debrief interviews are conducted with all participants and the feedback is “analyzed and then [CorEvitas] reports to the client,” she explains.

Terrey says there have been times when the patient response has influenced protocol change, such as reducing the number of visits, adding a car service, or easier samples drop-off; even the trial’s design from traditional to decentralized.

In another recent simulation between two principal investigators, Terrey relays that one spoke with empathy, the other went straight down the list of requirements. “We are doing the same protocol, but how patients responded was very different, which is valuable to inform site selection and training,” she says.

A decade ago, at Roche, Myles and colleagues built an “imaginarium” for Roche colleagues who were designing trials. Once a team had assessment schedules and the primary endpoint was established, imaginarium staff looked for real patients. It also brought in important team members—key opinion leaders, clinical scientists, and biostatisticians.

The team also included a graphic artist, for visual depictions done in real time. Myles says, “It was so useful, he would be listening for different things, for example, the emotion in the room.”

But those who were most surprised by what they learned from patients in the two-year patient imaginarium were the biostatisticians and clinicians. “They didn’t know how much they were asking of patients,” says Myles, for example, such as staying in an infusion suite for 12 hours.

Even communication among simulators can be difficult. Lovern says oftentimes, bioengineers and statisticians are speaking a language the decision-makers do not understand. The “modeling nerds” have the information, but they can’t communicate that meaningfully.

“It is like they use different vocabularies,” he says. “The engineers have to explain things in non-tech terminology, or even better, in a therapeutic context. This way, the physician can say, ‘I understand what you’re trying to say and why it’s important to the decision that I am trying to make.’”

With the successes and challenges of simulations, it still comes down to time and money. For industry, time is a business driver. Staley, a three-time cancer survivor, says, for the patient, time is life. Industry must move faster for patients.

 is a freelance writer for medical, clinical trials, and pharma information.

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Articles

Experts weigh in on the latest advances and adoption trends.

The Pulse of Modeling and Simulation in Clinical Trials

When the Big Pharma giant Pfizer abruptly aborted its relationship with decentralized clinical trial (DCT) specialist CareAccess six months ago, the company issued a terse statement regarding its decision: Pfizer blamed CareAccess for committing unspecified good clinical practice (GCP) violations. Hence, CareAccess could no longer continue recruiting participants for the huge, joint Pfizer-Valneva DCT for their Lyme disease vaccine candidate; those it had recruited were cut from the study. Since then, not a peep out of Pfizer, even after CareAccess told the world, Pfizer was wrong. Of the 96 or so trial sites, CareAccess had 28.

One would expect all hell to have broken loose at CareAccess. Yes, people lost their jobs and the negative press certainly wasn’t welcome. But one also would expect that other CareAccess clients would have broken their ties, or at least conducted audits of CareAccess’ conduct. But the CareAccess website shows numerous recruitment efforts still ongoing; it also shows it is hiring for multiple positions. As one source said, “Projects are continuing at CareAccess and things are still working. It is a strange thing.”

In a statement about its practices, CareAccess said: “Beyond the required GCP course all employees are required to complete, we also provide hands-on training in small groups both when employees are onboarded and every year as a refresher. Further, we run regular simulations at our sites to learn how to adapt to and address challenges that might arise and to ensure high-quality participant care.”

CareAccess declined to answer questions regarding the trial; Pfizer did not respond to email requests for comment.

Pfizer’s decision to begin new recruitment efforts won’t be cheap.

“It is extremely expensive for Pfizer to do this,” says Francis Crawley, executive director, Good Clinical Practice Alliance – Europe. There is “no sense in working with a site if there is no confidence in the data.”

If it’s a question of confidence in the data, then what would help instill that? Training.

Adhering to GCP requires more than just knowing the rules, says Crawley. It is understanding and knowing how to apply them in real time. Like following a recipe. You have an ingredients list, “but if you don’t know how to cook, you can’t do it,” he notes.

The list of GCP items will only get longer due to more digitalization, the move to DCTs, and the use of massive amounts of real-world data to support new molecular submissions.

“We live in a digital world,” says Crawley.

Another good reason for good training: It is likely that many clinical trial sponsors and contract research organizations (CROs) haven’t been fastidious about GCP. One study from 2011 showed that of 80 published trials reviewed, 32% did not report any protocol violations and none reported on all protocol violations looked for in the study, including patient adherence infractions, data collection infractions, enrollment violations, and randomization violations.

Getting through a trial without some sort of protocol violation is a long shot. Jonathan Cotliar, MD, chief medical officer, Science 37, says it is virtually impossible to avoid protocol deviations. Participants and study team personnel are human beings—humans make mistakes, he says. Protocols ask study participants to behave in ways that are not natural, and often create additional challenges beyond the obstacles that present themselves as individuals living with certain medical conditions.

Jerry Chapman, senior good manufacturing practice (GMP) quality expert, Redica Systems, says that protocol deviations are to be expected because clinical trials are about research. “There will always be problems with compliance,” Chapman tells 

. “We ask [clinical investigators] to do an ungodly amount of work.”

A salient point to make here: A clinical trial sponsor spends more money on finding the necessary number of people to prove an investigational drug’s effect than anything else in the study. What determines the second biggest expenditure is the number of visits those patients will make to the clinical site over the trial’s duration.

 Wrote the study authors: “Our statistical model showed trial costs rose exponentially with these two variables.”

DCTs could help with these two variables, but the irony is that to do so will involve copious levels of technology—and the latter will involve copious amounts of training.

Training is an area often overlooked and often used as a checkbox, contends Chapman.

“You have to be able to test someone on their knowledge, to ensure they absorbed it, or they can demonstrate certain skills,” he says. “You can’t read about how to dose a patient and say, ‘I can do it.’” Redica Systems has published an analysis, the data taken from years of FDA 483 inspection reports and warnings, that details the GCP violations made in clinical trials. Just saying that it was a protocol violation doesn’t help, says Chapman.

He has known quality professionals, he adds, who will look at the boilerplate information on an FDA inspection report and the references to the Code of Federal Regulations (CFR) “and not go further. That is a mistake.” It is necessary to read the whole report, because “there are really important parts that let you determine [violation] severity so you can determine how to remedy those violations with action items,” says Chapman. “You can use this data for internal retrospection.”

Whether by coincidence or calculation, FDA, within a span of a few months, has released new guidances covering training, International Council for Harmonization (ICH) E6 (R3), risk-based trial monitoring, and conducting DCTs.

 The agency last addressed the first two topics in 2013. The DCT document, long awaited by DCT providers such as Science 37, advocates for “appropriate training, oversight, and up-front risk assessment and management.” Crawley points out that the ICH GCP guideline includes information on the “appropriate management of data integrity, traceability, and security.”

Another training in waiting: Regulators like real-time monitoring. A 2020 report on a US-European regulators’ symposium said, “The ICH recommends use of centralized monitoring to ID protocol deviations. It emphasizes the need to focus on trial activities that are vital to safety and trial data reliability.”

FDA does not regulate GCP training details—not the scores, not the topics. Sponsors should provide the clinical investigator site team with training specific to the study and their roles as necessary, said an FDA spokesperson via email.

CITI Program is one of many organizations that offers GCP certifications. Jaime A. Arango, EdD, vice president, content and education, said in an email exchange that its subscribers determine their own needs and minimum-score thresholds for GCP training. CITI Program recommends an 80% passing score per module. The core level comprises about 13 modules.

Over the years, CITI has added video case studies, webinars, and new courses, including for clinical trial recruiting, DCTs, and remote and/or centralized monitoring.

Crawley says he has tested online training in which the answers were wrong. It is difficult, he notes, to learn online. GCP requires not only knowing the guidelines, but also being able to apply them, he adds. Classroom training far exceeds online training, but actual experience in a wide variety of situations for applying GCP is really what is needed.

At that 2020 symposium, representatives of FDA and the UK Medicines and Healthcare products Regulatory Agency parsed what GCP is required in preserving data integrity. It’s an important question, considering that data-generation no longer is exclusive to the trial itself, but also includes data from electronic health records (EHRs), real-world evidence and more. For regulators to reconstruct study conduct, a digital hair cannot be out of place.

The attendees, according to that report, said sponsors must monitor use of e-systems, and address issues with data, be they missing, inconsistent, or outliers. They need to fix tech programming issues and “potential protocol deviations that may be indicative of systemic or significant errors.”

In its risk-based approach guideline, FDA said centralized monitoring would allow sponsors to aggregate and then compare data coming from the various sites to “detect potential anomalies more,” including data entry delays and incomplete entries.

In this guideline, FDA is even advising sponsors when to do assessments—early in the morning. This way, if a few protocol deviations are found, they can be, secularly speaking, nipped in the bud.

In practice, risk-based monitoring is, albeit at a snail’s pace, becoming more reality than theory in the field. A 2020 report that reviewed 6,000 published trials found that 77% had at least one risk-based quality monitoring component in play—such as centralized monitoring and key risk indicators —as compared to the prior year’s 47%. Said the authors: “Risk-based approaches have been around for a long time, but adoption has been slow.”

Considering the operational complexity, technical prowess, administrative detail, and skills necessary to help patients, one wonders if a day’s worth of instruction can cover it all, considering the use of telehealth in a DCT.

A passing comment on inspections: They have been down, across the board, over the past few years. But now, thanks to new legislation passed in December, (the Food and Drug Omnibus Reform Act), FDA can request records before a bioresearch monitoring program inspection.

As for the drop in those inspections, while the pandemic is certainly to blame, a US Government Accountability Office (GAO) report from January found there are fewer independent institutional review boards (IRBs) due to consolidation and private equity investment.

FDA, when asked, did not supply a response for the drop in inspections.

Redica Systems, which has designed software to identify regulatory and quality issues so its clients can reduce their own regulatory pitfalls, had been curious about what was behind the reasons for the 483s and the warnings. Protocol violations aplenty, but, says Chapman, the firm wanted to dig deeper. Using artificial intelligence (AI), machine learning, and natural language processing, along with IRB and clinical investigator (CI) reports, they trained their software to look at the violations through a clinical inspectors’ eyes and using their vocabulary. “Based on the IRB and CI, we can drill down on where the issues are coming from,” says Chapman.

They looked at FDA warning letters dated over a seven-year period. The biggest problem they found was that sponsors and investigators were not adhering to their responsibilities. They found that 75% of the data integrity violations concerned issues like attribution or accuracy. They also found a steep drop in voluntary inspections—82 in 2021 vs. 182 in 2017.

Analyzation of the 483s, for which Redica Systems used a data pool from a 20-year period, found that data integrity issues were more common—these included legibility, accuracy, completion, sourcing, and availability issues. Drilling deeper, Redica Systems found enrollment problems such as failure to properly determine subject eligibility. Some participants had supplied bogus names, phone, and social security numbers.

Severity of a violation, according to Chapman, can be difficult to determine and measure.

“A data integrity issue means maybe somebody didn’t save the original document that they transcribed. It may not be faulty, but it means the data is suspect. That gets kind of murky,” he says. “When you talk about a warning letter, beyond a 483, what you will see, for example, is maybe ‘not according to plan.’ That is one of the bigger citations, but how serious is that? That part is in the text that follows. Seriousness isn’t determined by the number of violations.”

Operations at Science 37 seem to reflect regulators’ proposed guidance: one virtual trial site with real-time protocol inspections across all patient data entries—in short, Sauron-like vision from all digital angles. Not necessarily fewer protocol deviations, but if the trends are there, they are easier to identify. One virtual site, says Cotliar, “provides probably a clearer path.”

And that path is pebbled with study team documentation, from the trial investigators to the visiting nurses to those running the platform. “I don’t have to rely on site files to look at other single platforms, to achieve proper oversight,” adds Cotliar.

Training at Science 37, as one would expect, involves various levels, from issues that are protocol specific to getting into the weeds of the technology. “We spend a lot of time in training, its sole focus being, does everybody understand how to use the platform?” says Cotliar.

Is everyone comfortable with it? According to Cotliar, the visiting nurses go through mock visits to trial participants’ homes. They set up the technology that is automatically linked to a unified platform, “to make sure we are complying.” They learn how to handle the technology if the power goes out. All of this, adds Cotliar, takes repeated practice.

Crawley believes that as clinical trials become more digitized, more AI-dependent, attitudes regarding GCP need to advance.

“You have to operationalize GCP,” he asserts. “Training will be important if we are going to have confidence in trials that are increasingly digitized and conducted through different systems of AI.”

An Efficacy, Safety, Tolerability, Immunogenicity, and Lot-Consistency Clinical Trial of a 6-Valent OspA-Based Lyme Disease Vaccine (VLA15) (VALOR). ClinicalTrials.gov. August 2, 2023. 

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https://www.fda.gov/media/169090/download

A Risk-Based Approach to Monitoring of Clinical Investigations: Questions and Answers

https://www.fda.gov/regulatory-information/search-fda-guidance-documents/risk-based-approach-monitoring-clinical-investigations-questions-and-answers

Decentralized Clinical Trials for Drugs, Biological Products, and Devices

https://www.fda.gov/media/167696/download

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Stansbury, N.; Barnes, B.; Adams, A.; et al. RiskBased Monitoring in Clinical Trials: Increased Adoption Throughout 2020. 

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Thousands of Sites, Less Than 100 Investigators: New Authorities Help FDA Maintain Oversight of Clinical Research 

https://www.fda.gov/about-fda/regulatory-news-stories-and-features/thousands-sites-less-100-investigators-new-authorities-help-fda-maintain-oversight-clinical-research

Institutional Review Boards: Actions Needed to Improve Federal Oversight and Examine Effectiveness 

https://www.gao.gov/products/gao-23-104721

Stepped-up training and real-time application key to avoiding compliance pitfalls. 

More than Just Rules: Raising the Bar in GCP Adherence 

What follows is a bulleted list that outlines why pharmaceutical company sponsors should not consider returning clinical trial data to patient participants. In short, it will:

In other words, the effort would cost more money, and demand a whole new way of thinking.

What follows is why sponsors should return clinical trial data to patient participants:

This slowly emerging idea of returning trial participants their own data is not ephemeral or whimsical. A few pharma houses are seriously considering eschewing the top four bullets in favor of that stand-alone bullet. One, Pfizer, is just about ready to roll out its own return-the-data program. Another, Janssen, is “actively pursuing” its own version of a patient data-return, a spokesperson said. A few others, all members of the nonprofit collaborative TransCelerate BioPharma, are seriously talking about the matter.

“It is a natural next step for a clinical trial patient,” says Sylvia Baedorf Kassis, program director, the Multi-Regional Clinical Trials (MRCT) Center of Brigham and Women’s Hospital and Harvard. Patients, she adds, will want to know, ‘“what can I learn from participating in this study?”’

Sponsors are becoming more comfortable with the idea, according Baedorf Kassis, and for some people, it will make all the difference.

However, she cautioned—like others interviewed for this story—every patient is different, every patient’s need is different, every trial is different. So along with the possible regulatory hurdles that await attention and the significant buy-in from pharma that needs attainment, the data-return supporters have continued working on tools for sponsors to use. The MRCT Center has produced case studies and a patient-friendly glossary of clinical research terms; TransCelerate has made publicly available its resource pack to advise sponsors on returning data; a European consortium has its own project. And, yes, these groups cooperate with one another. (Baedorf Kassis said the glossary has been adopted as a global Clinical Data Interchange Standards Consortium standard.)

A potential selling point to pharma is possible improvement in the historically low trial participant recruitment and retention numbers. In its 2023 omnibus bill, Congress told FDA it wants a diversity action plan with each trial submitted for its review.

 Those interviewed said data return would help in these areas.

At one time, says Christine Lemke, cofounder and CEO, Evidation, “I used to think [the idea] was paternalistic but now I think it is the right decision. Returning the data will take more time.” She adds doing so won’t be easy, but believes it is worth it. “The participants deserve respect.”

“It was maybe 10 years ago when we started saying there’s something here we have to think about, even though it’s not required” by regulators, Jean Sposaro, director, Global Clinical Trial Industry Collaborations at Bristol Myers Squibb (BMS), tells 

. However, not all pharma companies are ready to “take the leap” due to the lack of those requirements.

So why the effort now to create patient data-return plans? “Patient participants are louder than ever,” says Baedorf Kassis. Providing participants with the aggregated results from their trial has not been enough, she argues.

The COVID-19 pandemic, adds Sposaro, put a light on an industry; up until then, pharma had been working behind a curtain, in essence. “Now we’re not,” points out Sposaro. “People know what pharmaceutical companies do and they know that we can’t do it without patients.”

While there always has been a handful of trial participants who wanted their data, “there has absolutely been an uptick in requests for data since the pandemic,” adds Sposaro. “The group of people that I meet with a couple of times a week [regarding patient data return] are all saying the same thing.”

Besides the patients’ desire and appreciation for the value of patient data, “We have the digital capabilities we didn’t have before,” says Sposaro. “So, do we just ignore it or do we start to plan and think ahead?”

While the temptation to ask “what happens if this patient wants this or if a genomic test shows that?” is ever present, an interviewer soon learns those kinds of questions are moot. “We’re just beginning to really scratch the surface,” says Sposaro.

“We haven’t gotten there yet, it is so specific,” adds Baedorf Kassis. The MRCT Center, and other data-return advocates, are going with or recommending a phased-in approach, starting with the easiest data to return and thereby gaining experience with the process.

A ‘what happens if’ scenario is discussed anyway. Imagine, says Lemke, that a patient-participant experiences unintended consequences of a data return. Someone needs to walk through the results with them. “You wouldn’t want someone to get that without context,” she notes.

That scenario is exactly what happened to a patient advocate in an MRCT Center case study.

 The woman, a patient with multiple sclerosis, learned that she was at high risk of developing Alzheimer’s disease, but no genomic counselor was provided to help her, and the institutional review board (IRB) said the clinical trial researchers met their contractual obligations.

At this point, these groups are taking the 30,000-feet view. TransCelerate is creating a patient infographic for patient advocacy groups. It is also creating a sponsor-directed considerations guide that will detail “why they should and how that patient data-return could happen,” says Sposaro, explaining that pharma executives aren’t convinced that patients want their data. “What I get a lot from senior leaders is, ‘Do you think patients really want their data?’”

In Europe, a group called Facilitate–which lists 29 pharma houses, academic institutions, patient groups as well third parties–has formed to devise a model plan for patient data return and for the reuse of study data. No two organizations, says Sposaro, have the same goals.

The plan at Pfizer, according to a MRCT hosted webinar

, is to allow patients to receive their data at the end of the trial, which, of course, could take years. The program will begin in US-centered trials for now. Participants interested in getting some data–no imaging files or genomic data just yet–will create an account via a portal.

A few years ago, says Sposaro, BMS ran a pilot study on data return, but at a specific point–when patients failed admission to the trial.

Those failures still result in a lot of data, including blood draws, potential specimens, or imaging results. BMS gave the data back to those patients. She says BMS is now reviewing the outcomes of that data give-back.

Sposaro counted off the benefits to these patients: It lets them move to the next place for their treatment options.

Pharma reduces the burden on the patient, the participant, “but we also reduce the burden on the healthcare system because somebody has to pay for this,” she says. “For me, this is one of the low-hanging fruits. I’m not telling you pharma is doing it yet. I can tell you that we have started to think about it and people are starting to pilot it because that’s just one example of ‘why not.’”

Lauren Wu, head of privacy and senior director of legal for regulatory and compliance, Evidation, says sponsors who are interested in returning patient data need to move cautiously from a regulatory perspective. “I would be concerned how this would be interpreted by regulators,” Wu tells 

Despite the good intentions, regulatory agencies might consider the data returns when accompanied with insights that would make the information understandable to patients as getting “close to practice of medicine considerations or CLIA testing requirements,” says Wu. There are, the attorney adds, “juxtaposed insights, considerations, and conflicts.”

The discussion to return patient data follows a long history of similar efforts by regulators, the government, and others, to share data that emerges from interventional clinical data. At the NIH, its final policy on data sharing among scientists went into effect in January.

The agency wants to see a data-sharing plan before it considers extending a grant–including from its own investigators.

For the past five years, authors of manuscripts reporting clinical trial results who submitted to a member journal of the International Committee of Medical Journal Editors have been required to include a data-sharing statement.

But pharma hasn’t exactly embraced the “let’s-share” momentum. One study published last year found that of 61 published trials, nine were considered eligible for sharing data–two years after publication. A study was considered ineligible if it lacked a data-sharing policy or involved an ongoing investigation.

As for who owns clinical trials data, that argument has multiple sides. It seems that cases can be made for those who funded it, and also for those who provided it.

“Ultimately,” wrote the National Academies of Sciences in 2015, “the question of who owns the data is less important than the question of the rights and responsibilities of data holders.”

Sposaro says data-return advocates aren’t looking for regulators to tell them what to do, “but what we would like to know is what are the areas that they’d be concerned about.”

Lemke highlighted a study Evidation was part of in 2014 with Brigham Women’s Hospital and Atrius Health that demonstrated the good and the questionable regarding patients’ access to their data. The two-arm study involved 411 patients at risk or already diagnosed with high blood pressure.

 Patients used a blood pressure cuff at home. Researchers wanted to see how adherent they would be in taking their medications and using a smartphone app to record their numbers. The upshot: there was some improvement among those patients using the app. These patients were consistent witnesses to their data.

“This is part of the trickiness of sharing,” Lemke tells 

. Sharing outcome results could be a confounder that contributes to the
actual intervention.

Other complications, she adds, would be sharing data after an observation period. Those results need to be stored away until they are analyzed.

“People want to lock up data until it is time for statistical analysis and in the hands of regulators for decision-making,” asserts Lemke. “These are complications that pharma hasn’t worked out in order to make [data sharing] a fluid process.”

The public is of two minds regarding their data. A 2018 

 study found that of 771 former and current trial participants, fewer than 8% thought the negative reasons of data sharing with scientists outweighed the good reasons.

 The main concerns with sharing data with professionals, the respondents said, was that it would discourage would-be participants in joining a trial (37% “very’ or “somewhat” concerned) and would be used for marketing purposes (34%.)

On the other hand, when the UK’s National Health Service proposed in 2021 that its members’ personal data be shared among various healthcare providers, more than one million people said,
no thanks.

Returning patient data, says Sposaro, is trust-building. How, she questioned, can industry refer to itself as patient-centered if it doesn’t return the data generated by those people who are helping in the first place?

“We know big pharma is a machine,” she notes. “We’re asking the machine to do something very different.”

 is a  freelance writer for medical, clinical trials, and pharma information

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Morawski, K; Ghazinouri, R; Krumme, A; et al. Association of a Smartphone Application With Medication Adherence and Blood Pressure Control: The MedISAFE-BP Randomized Clinical Trial. 

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Experts explore potential paths to achieving buy-in from pharma and regulators.

Christine Bahls

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