Marcus A. Banks is a freelance health journalist

Marcus A. Banks

Since 2017 many clinical trial vendors have developed products aimed at improving patient recruitment for clinical trials, tracking patient responses to potential therapies, or integrating all data produced in the trial technology ecosystem. The COVID-19 pandemic hastened these changes, especially related to the technologies that support decentralized clinical trials, although some observers say that many technologies now coming into view existed pre-pandemic.

“The pandemic triggered not a digital revolution, but an attitudinal revolution in the pharmaceutical and life sciences industry. Decentralized clinical trials (DCTs) were a fashion statement two years ago, but now everyone has a strategy,” says Nimita Limaye, research vice president for tech-focused market research firm IDC Health Insight.

“There’s been huge growth in things like wearables and sensors, which are really mapping how patients are responding to interventions in a very subtle way,” observes Limaye. Thanks to these sensors, it’s now easier to tell if patients are taking prescribed medications, or trial participants are maintaining experimental treatments, she says. Limaye adds that the practice of e-consenting patients has become much more routine in the last five years, along with using machine learning to detect safety signals that might not be captured in a structured adverse event report but are hidden in the more idiosyncratic narrative records of the trial.

“Extracting intelligence from structured and unstructured data is an important use case” for machine learning, says Limaye. Another is to use machine learning to mine real-world data about how different populations fared on FDA approved drugs post-approval, to build synthetic control arms for future clinical trials in which real-world experience on the already approved drug is compared head-to-head against the new intervention.

Machine learning depends on training algorithms on large sets of data, Limaye notes, but many pharmaceutical companies securely protect their own clinical trial data in a way that’s impenetrable to machine learning algorithms. Limaye adds that federated learning technologies, in which algorithms access data that never leaves its secure location, are emerging solutions to this problem that pharma companies are beginning to embrace.

Overarching these technological developments is a broad sense among clinical trial observers that there’s a once-in-a-lifetime opportunity to infuse equity and inclusion into the design and deployment of clinical trials that use digital tools. Clinical trial participants, today, are not representative, which means that the results of clinical trials are not always generalizable.

“When we pick up these tools—whether that’s the use of real-world data, whether it’s running [artificial intelligence] and machine learning techniques on these data, whether it’s the use of telehealth for virtual visits, whether it’s the use of digital technologies and remote patient monitoring—it’s not enough to just say we’ll do it and we’ll figure out the equity bit afterwards,” says Jennifer Goldsack, CEO of the nonprofit Digital Medicine Society (DiMe), which aims to promote digital-first clinical trials that could not have been done in the analog world.

“We could be encouraged by how the current process works, when we talk about the history of the informed consent process,” adds Jude Ngang, executive director of representation in clinical research at Amgen and a DiMe partner in a new initiative to develop more inclusive clinical trials. According to Ngang, Amgen takes great pains to ensure that everyone, regardless of language or literacy level, understands what they are agreeing to as they begin a clinical trial, and says the same care can be taken with ensuring that all clinical trial participants know how to use a wearable sensor or other digital device.

Part of solving the trial recruitment puzzle is simply to alert more people about relevant trials. Amgen has invested in CancerIQ, a genetic risk assessment software program linked to patient medical records (EMRs). Many people go to community oncologists, not academic medical centers where frequent clinical trials occur, notes Ngang. With CancerIQ, a community oncologist can alert patients about enrolling studies for new cancer treatments they might not have learned about otherwise.

CancerIQ is just one of many clinical trial-related technologies. This article will detail other emerging tools that enhance clinical trial recruitment, improve participant monitoring once a study is underway, or aim to integrate clinical trial data in more impactful ways. Read on to learn about the brand new kids on the block, or the old kids who’ve learned how to pivot.

Linking patients, improving engagement, and novel measurements

“There’s this idea that doctors are afraid of losing patients to clinical trials, and that’s why they don’t refer them, but that’s not true. The main reason physicians don’t tell patients about trials is because it takes extra time,” says Mukul Mehra, a gastroenterologist and co-founder of IllumiCare. The company aims to make clinical trial referral a “prescribable event,” in the same way that a physician might prescribe a statin and then rely on existing infrastructure to get that drug to the patient.

Mehra says that trial notification systems do already exist within electronic health records (EHRs), but as email inbox messages that physicians might not read until hours or days after seeing the patient. At that point the physician needs to call up the patient record and triage whether they are eligible for the study, which is actually a better task for clinical trial coordinators.

IllumiCare’s “Smart Ribbon” technology surfaces matched trials within the EMR workflow, as the doctor is seeing the patient, and works with all major EHR platforms. A doctor can either discuss the trial with the patient on the spot, or refer them to a clinical trial coordinator to help them decide whether they’d like to enroll. Just launched in May for this purpose, after 24 months of development, Mehra expects that Smart Ribbon will make clinical trial recruitment and discovery easier.

Enrolling patients into a trial is just one challenge. Preventing attrition is another.

“How can we improve the participant experience in a meaningful way?” asks Andrea Valente, CEO of the clinical trial technology vendor ClinOne, whose prime client base are biopharma sponsors. Valente says that the average cost per patient of an oncology trial is $100,000, and up to $300,000 when involving a rare disease patient. Replacing patients who drop out mid-trial is expensive, Valente notes, and could lead to delays in availability of new treatments.

Much of ClinOne’s innovation in recent years is due to COVID-19, although the company pre-dates the pandemic. During the pandemic, e-consenting and video consults bloomed, as many ClinOne clients began to offer DCTs. Interactive SMS messages to remind patients to take medications also became more common, and a partnership between ClinOne and Uber Health offered transportation to patients who were unable to drive as a condition of enrolling in a study for a major depressive disorder treatment.

ClinOne found that, at some trial sites, 98% of elderly patients in a cardiovascular drug trial were successfully taking medications 18 months after the trial began, due in part to the medication reminders; and that offering free transportation (up to two round trips a day within a 200 mile radius, for personal and not only trial-related reasons) significantly enhanced enrollment in the depressive disorder study. ClinOne and the trial sponsor expect that retention in this study will be enhanced as well, thanks to the transportation solution.

Medical sensors and wearables, which people wear regularly as they move about their daily lives, open up new possibilities for clinical trials that the five-year-old company ObvioHealth aims to explore. Start with the humble cough.

“It sounds funny, but everyone’s cough is different,” says ObvioHealth’s CEO Ivan Jarry, who is working on a project that uses AI to detect hidden health risks within someone’s coughing patterns. This could ultimately inform new clinical trials, once clinicians and researchers have a better understanding of the health implications of different coughing patterns.

Meanwhile, ObvioHealth has developed a platform that continuously collects data gathered from wearables such as blood pressure levels, oxygenation levels, or heart rates of patients in clinical trials for different treatments—with the data fed to the research site in real time (or as soon as possible if the patient loses connectivity). ObvioHealth doesn’t just transmit the wearable data wholesale to the researcher, but also uses algorithms to detect if there are safety signals, and sends the results of this analysis, too. Its clients include pharma and biotech companies, contract research organizations (CROs), and academic medical centers.

For example, if a patient’s blood pressure always plunges right after receiving an experimental treatment, either that treatment is a total non-starter or can only work if the patient takes precautions. In the analog world, such a relationship between the medication and blood pressure might take weeks or sometimes months to detect.

“Our aim is to detect actionable signals from data,” says Jarry. ObvioHealth also wants to be a leader in women’s health studies, which Jarry notes have historically been understudied or studied with invasive procedures. This year, ObvioHealth was the research vendor for a fully virtual study that concludes that digital therapeutic devices improve the effectiveness of home pelvic floor muscle training (kegels) for reducing urinary incontinence symptoms in women.

Integrating data from every possible source

Several clinical trial technology companies focus on the so-called “back end” of digital clinical trials, or the data management and integration needed to make these studies possible.

KORE has existed since 2002, but just this year the organization acquired the companies Business Mobility Partners and SIMON IoT (internet of things) to enhance its connected health offerings. The acquisition helps KORE to serve high volume, Phase III clinical trials that can involve up to 3,000 participants, according to KORE’s Chief Marketing Officer Landon Garner.

IoT means that a physical object, like an internet-enabled blood pressure monitor, is linked to other connected objects such as a handheld device that records and communicates results (in this case, the blood pressure readings). IoT is why a programmable thermostat, say, can also turn on a HVAC system. And IoT is the reason why scientists and regulators moved from a COVID-19 vaccine concept to placing vaccines in arms within 12 months, Garner says.

“The pandemic became a forcing function for virtual or decentralized trials, using IoT technology,” says Garner, because the connectivity afforded by IoT technologies enabled real-time data capture that showed the efficacy of now-approved COVID-19 vaccines. The same flexibility is available to any company that wishes to run a global drug trial.

“We have access to 600 mobile networks around the world,” says Garner. According to the executive, KORE can provide tools such as digital weight scales or continuous glucose monitors that will work in any trial location. KORE’s technology does not analyze the data generated by a trial directly—that’s the work of algorithms and the clinical trial research team—but instead it federates the various data streams so that they all go to the right place.

The healthcare technology company Seqster created SeqsterOS to capture patient-matched EHRs, genomic DNA, wearables, and pharmacy and lab test data collected during a clinical trial, via its dashboard. Trial participants authorize with whom they share this data, in a HIPAA and FDA-compliant manner that also complies with European privacy regulations, according to Seqster CEO Ardy Arianpour. Once the trial participant authorizes sharing any of their data with vetted Seqster users, it is available.

“We’re at the tip of an exploding patient-centric and digital clinical trials industry,” says Arianpour, who co-founded Seqster in 2016 and launched an early version of its research portal in 2018. Seqster has continuously iterated its operating system since then, with the aim to “break down health data silos at scale,” in Arianpour’s words. Its most recent software integration, announced in April, is with Salesforce Health Cloud.

For health outcomes researchers interested in how economics affects participation and retention in clinical trials, Seqster includes socioeconomic determinants of health information, such as a trial participant’s zip code or annual income.

“Your zip code is one of the most important determinants of health, and most people don’t know that,” adds Arianpour. Seqster’s goal is to integrate every possible source of data relevant to someone’s health while in a clinical trial or as they are receiving care, and to enable algorithmic and human analysis of these various data streams.

Data curation and management will only become more critical to clinical trial deployments and healthcare delivery, contends Limaye, who notes “we’re a data-hungry world,” particularly when it comes to harnessing personalized data. For example, the ability, she says, to capture not only how people’s heart rate fluctuates or glucose levels vary, but also to sequence individual genomes or proteomes or lipid levels.

One challenge today, however, is that much of this data resides in silos, either in the purview of a clinical trial sponsor or EHR or a third-party provider. Limaye argues that developing holistic and longitudinal views of a patient’s health requires developing interoperable protocols that enable data flow between systems while respecting data security, privacy, and sovereignty.

At the same time as data volume is increasing, the proportion of hard-to-interpret medical data is rising as well. IDC predicts that less than 5% of all data generated electronically will be “analyzable” by 2025, meaning that many data-driven health insights will be hard to derive with current tools.

One exciting data analysis tool Limaye foresees is “codified listening,” in which machine learning and speech emotion-recognition algorithms provide new insights into the emotions or sensitivities that drive the behavior of patients or clinical trial participants. A patient might leave a voice memo that such software decodes. This technology is in its early days, Limaye cautions, but could open new doors to understanding the patient or trial participant experience.

Meanwhile, the distance between the clinical trial site and point-of-care delivery is shrinking. “There is a growing confluence between healthcare and life sciences,” says Limaye, noting that pharmacy giants such as CVS and Walgreens are becoming clinical trial sites, not just places for dispensing medications that were approved through an entirely separate clinical trial process. Limaye foresees an eventual collapse of the distance between healthcare delivery and clinical trial sites. Goldsack agrees.

“When you have to lock the data in a filing cabinet and only the [principal investigator] or the office manager has the key, yeah—you can see why that happened,” says Goldsack, in describing the historical separation between the clinical trial and healthcare delivery spaces. “But we are so far from that reality now.”

New Vendors in the Clinical Trials Industry Discuss Their Products

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COVID has accelerated to the scene upstart digital efforts to transform patient engagement and data management/integration—but progress remains measured.

Clinical Trial Technology: New Kids on the Block are Changing Industry Dynamic

The National Center for Advancing Translational Sciences (NCATS), part of the National Institutes of Health (NIH), turns 10 this December. NCATS initiatives aim to reduce frustration and failure in the journey from bench to bedside. “From the time you work on a drug in a lab to the time you put it in a patient, how can you do this more efficiently and effectively?” asks Lili Portilla, NCATS director of strategic alliances.

One key goal of Portilla’s work is to ease passage across the so-called “valley of death,” in which an academic researcher develops a promising new molecule as a disease treatment, but then does not know how to test their invention, apply for FDA approval, or bring it to market once approval occurs. This is the kind of expertise that a biopharma might have; NCATS brings academics and pharma companies together.

Portilla notes increasing biopharma interest in treatment for rare diseases since NCATS began. This is research that often begins in academic labs and which pharma has historically overlooked as the patient base for a rare disease drug is usually small. But pharmas have become increasingly interested in the incentives offered by the Orphan Drug Act, Portilla says, which grants seven years of commercial exclusivity for any drug that treats a rare disease. The Orphan Drug Act has been on the books for almost 40 years, and the pace of approvals for rare disease drugs continues to increase.

 While some health policy observers say that in some cases biopharmas are creatively slicing data

 to generate ever more approvals for rare indications, rare disease research is likely to continue.

In response, NCATS has developed a program to spur rare disease research collaborations between pharma and academia. And since its inception, NCATS has helped biopharma and academic researchers investigate whether a drug that had failed in one context could be repurposed to treat another disease.

Beyond rising interest in rare diseases, Portilla observes that biopharma companies now prefer to collaborate with academic partners once a molecule is more of a sure bet for eventual FDA approval. “Fifteen or 20 years ago companies would just license things without a lot of data associated with them. That doesn’t happen anymore,” Portilla says.

In discussions with a wide range of industry leaders, 

 found that the current patterns of academic-pharma collaborations began somewhat as a marriage of convenience once NIH support for basic science research began to soften. This transactional foundation has led to continued breakthroughs in cell and gene therapy, along with new breakthroughs in immunotherapy, over the last decade and the use of real-world evidence within clinical trials may be on the horizon. IRB processes have become more centralized across sites too, and smaller biopharmas are increasingly getting into the game. Even so, some observers say that it’s still challenging to enroll in a clinical trial and that managing the inherent conflicts of interest between academic and biopharma missions remains critical.

Academic institutions once shied away from collaborations with researchers in biopharma companies, recalls Paul Nkansah, senior director for corporate partnerships at Johns Hopkins Technology Ventures.

“If you go back and look at academic institutions and their mission, they’re there to educate and provide a service to the community,” says Nkansah, who works to commercialize Johns Hopkins research and previously spent 14 years at Pfizer. “This idea of ‘let’s bring in a partner whose primary mission is actually to make profit’ was a very difficult thing for any academic institution to process,” Nkansah continues.

Eventually a pharma company might come to a university once it needed help in recruitment for a late-stage clinical trial, Nkansah says, but generally there was little interaction between the two parties.

This arms length approach changed after NIH support for basic science research began to flatten

 in the early 2000s, Nkansah says, following an unprecedented period in which the NIH budget doubled in just five years. The NIH budget flattening meant that multiple universities who had beefed up their grant-seeking activities during the budget doubling days were now competing for an ever-more fixed pie to conduct basic research, Nkansah recalls. This spurred a need to seek new funding for basic research from elsewhere.

Enter biopharma; Nkansah says that drug companies stepped in to fund basic science research once the NIH well began to dry up. A 2017 US Government Accountability Office report

 confirms that most of the molecules tested in clinical trials, and which biopharma companies commercialize if approved, originate in academic labs.

Besides the ability to fund research from the preclinical stage, and therefore have first dibs on commercializing any resulting treatments, Nkansah says that pharma leaders increasingly appreciate that much of the research into the biology of rare diseases, or how to address seemingly intractable neurological problems, is happening on campus. And academics who would like to see their work developed into real-world treatments are less wary of direct collaboration with people in pharmaceutical companies, Nkansah observes, perhaps with the exception of an old guard that still believes that never the twain should meet.

Everyone else, Nkanshah says, is interested in a “true partnership” that leverages the strengths that academics and biopharmas bring to the table.

“Academic partnerships are my passion,” says Bayer’s Global Open Innovation Head, Chandra Ramanathan, who also says that the best biopharma-academic partnerships leverage the unique strengths of both parties. When Ramanathan assesses whether to enter a new academic partnership, considerations include whether the partnership is likely to focus on new disease targets, offer a more efficient means of drug discovery using artificial intelligence, or yield new treatment modalities such a biologic, or cell or gene therapy.

Ramanathan points to Bayer’s partnership with the Broad Institute, which began in 2013, as an example of innovation like the kind he described. At first, this partnership focused on finding new treatments for cancer. In 2015, it expanded focus to include cardiogenomics, and in 2018 evolved again to focus on precision cardiology treatments. That step included opening a joint lab

 housed at the Broad, which includes Bayer and Broad scientists working side by side to develop high-resolution maps of single cells as a way to better understand how cardiovascular disease spreads and could potentially be treated.

New possibilities for academic biopharma partnerships

Although the cultural barriers between academia and biopharma that Nkansah describes were real, they weren’t so formidable that the two sectors truly had nothing to do with each other. It’s easy to find calls for collaboration

 between biopharma and academia from a decade ago or longer.

What is different today, says Sandy Smith, RN, MSN, AOCN, senior vice president, clinical solutions and strategic partnerships of clinical trial services provider WCG Clinical, is that much more genetic information to inform personalized treatments is now available.

“A lot of what’s driven this is the Human Genome Project. There are so many things to begin to break open and study,” Smith says, causing biopharmas and academic institutions to partner in a more concerted way to identify and test new treatments and eventually file for FDA approval.

The full advent of personalized genomic medicine may be sometime in the future, but Smith sees direct benefit of pharma-academic partnerships right here and now.

“Just in the last eight years or so, seeing what’s happening in immunotherapy,” Smith finds new fruit in these collaborations. Many new immunotherapies for different types of cancer have been approved in recent years, Smith says, which pharma companies brought to market after partnering with academic researchers who conducted the foundational research. And although the academic work behind cell and gene therapy is now decades old, Smith sees an increasing acceleration within the last decade in bringing such products to market.

Looking forward, Smith hopes that increasingly robust, digitized medical records will enable real-world evidence to be used as a synthetic data arm in clinical trials. Rather than running every new trial as an isolated data gathering event, the idea here is to incorporate real world experience into a trial’s data sources.

Smith says that medical records are finally detailed enough, and interoperable enough, to make incorporating real world evidence into clinical trials possible. So the need to longitudinally follow people for decades to see how they fare on a treatment, an inherently laborious task that Smith was part of in a prior position, may start to decrease.

Third-party vendors promote clinical trial integrity

Everything touched on so far—rare disease drug development, biopharma funding of basic science/preclinical work, designing immunotherapies, refining gene and cell therapies—will eventually need to be tested in humans to ensure that they are safe and effective. This often means that a potential treatment will need to be tested in multiple locations, each of which might have its own local practices for managing clinical trials. The resulting confluence is challenging for study sponsors to navigate, according to James Riddle of the clinical trial solutions provider Advarra, which has helped coordinate gene and cell therapy trials for roughly a decade.

In 2016, Riddle says, the NIH began to require that all multi-site clinical trials have a single IRB

 as a condition of funding. Gone were the days of wildly disparate informed consent processes, which meant that participants in different trial sites had a different understanding of the trial. The trend toward centralized IRBs began roughly a decade ago, Riddle estimates, but accelerated in the wake of NIH’s action. It’s less likely now that a university will run its ethics reviews in house, he says.

“If you want National Institutes of Health money, and you have a multi-site project, you have to devise a single IRB strategy—which the commercial IRB’s have been doing for decades,” Riddle says. This centralized IRB strategy has overlapped with the period in which biopharma and academic interests have becoming increasingly enmeshed.

The IRB process is meant to ensure that clinical trials begin on a sound ethical footing, in which every participant understands the risks and benefits of participation. Once a clinical trial is underway, oftentimes a Data Safety Monitoring Board (DSMB) will meet to assess emerging evidence about whether the new treatment’s benefits outweigh its risks. In this way, the DSMB must be a truly independent entity that isn’t swayed by either an academic or pharma partner. WCG and Advarra both offer centralized IRB and DSMB management services designed to ensure that these processes.

Perhaps unsurprisingly, established biopharmas like Novartis are well-positioned to partner with academic institutions and to capitalize on the commercial potential that such partnerships might bring. In a statement to 

, Novartis Director of External Science and Partnering, Ann Schlesinger noted that in 2020 Novartis recently launched the NIBR Global Scholars initiative to link Novartis scientists and academic scholars to fund novel science that may lead to new drug development. And large commercial players are also skilled at leveraging government funding to carry out their research efforts, as shown in the Operation Warp Speed effort in which the US government bore the cost for the clinical trials of COVID-19 vaccines.

But it’s not just the big players, notes Paul VanVeldhuisen of the contract research organization Emmes, LLC. “Smaller biopharmas and some of the emerging companies also seek government funding to do their research,” VanVeldhuisen says, pointing to substance use research as an example.

Emmes has long standing relationships with academic leaders in substance use research, such as New York University and Columbia University, and also knows how to access government funding from relevant entities such as the National Institute on Drug Abuse. But the smaller biotech that wants to test a promising new treatment for curbing addictive impulses to an opioid or to alcohol—research that may now incorporate greater use of genome-wide associate studies,

 but does not have this knowledge at its ready disposal—might look outward to a CRO. In a brokering role similar to that of NCATS, Emmes is in a position to bring the relevant parties together. “That’s our sweet spot,” VanVeldhuisen says.

Increasing enrollment in clinical trials: an opportunity

All of the above is well and good, but perhaps that’s only as far as it goes if the vast majority of people do not participate in clinical trials. As Adrian Hernandez, executive director of the Duke Clinical Research Institute, points out, less than 5% of US residents ever participate in a clinical trial. Hernandez says there is no easy way for people to express their interest in joining a clinical trial, or easy ways for them to learn what trials are happening in the first place. This is because our clinical trial infrastructure is separate from the places where patients actually receive care; Hernandez recommends linking the two together. A listing of a patient’s clinical trial interests within their medical record, so they could automatically be alerted of upcoming trials that match these interests, might help to address this.

Recruitment is just one challenge. Once a clinical trial is underway, Hernandez says, “the costs and complexity of clinical trials have increased in a number of ways.” In particular, today’s trials are more data intensive than they once were, Hernandez says, as researchers try to address potential “what-if” scenarios of potential responses to a treatment as ways to reduce unknowns once it reaches the market. This requires more statistical and analytical resources, increasing costs.

Before recruitment begins, and certainly before the trial starts, it has to be designed. What are the endpoints? How will they be measured? What level of enrollment is necessary for statistical confidence in a trial’s results? In any biopharma-academic collaboration, Hernandez says, representatives of both entities must be at the table during the design phase. And ideally there would be multiple people with different types of expertise, a “team science” approach that Hernandez says could probe the blind spots in any emerging study design to make sure it does not have a hidden bias that tilts the study’s results one way or another rather than letting the data tell the tale.

Any such tilting would not necessarily be at the behest of the pharma partner, Hernandez notes: “Sometimes I find intellectual conflicts are stronger than financial conflicts.” Perhaps an academic partner is truly invested in seeing a molecule that they have spent years of their life on be vindicated in a clinical trial–an understandable, yet unacceptable, consideration when designing that trial. In another sign of how times have changed—similar to the raft of approved immunotherapies and possible use of real-world evidence in clinical trials—Hernandez suggests that principles of open science could shine sunlight on conflicts of interest that the trial designers themselves might not be aware of. This could involve posting proposed trial protocols and rationales, online for public comments, a sharp departure from current practice.

However, collaborations between academic and biopharma partners evolve, it seems clear that the fates of the two parties are inextricably intertwined in ways that were not always the case. Some observers are optimistic about what this will mean. “From my perspective I think academic and industry partnerships continue to flourish, probably even more so,” Smith says.

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Proactive, pervasive, and strategic planning lead industry into future.

Marcus A. Banks

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Clinical Trial Technology: New Kids on the Block are Changing Industry Dynamic

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