The global pandemic highlighted the necessity for some clinical trials and related data collection to be urgently expedited. While the COVID-19 vaccination results weren’t rushed, researchers did everything they could to navigate the challenges associated with developing clinical trials and analyzing data quickly.
Of course, most clinical trials don’t have the same national support and resources as the COVID vaccine tests. So what can these research organizations do instead?
Quality data is at the root of all clinical trials. As researchers collect more data, will trials move forward faster? Here are a few things to consider as teams develop clinical trials and tap into existing data sources.
Clinical trial length directly affects patients. If a trial takes an extra year or two to complete and work through the approval process, hundreds of patients could be affected. These are people who don’t have access to optimal treatments because those treatments haven’t been developed or approved.
“Clinical trials alone take six to seven years on average to complete,” writes Eian Kantor at digital health company Antidote. “Looking at the big picture, it takes approximately ten years for a new treatment to complete the journey from initial discovery to the marketplace.” This window includes everything from the preclinical research process through all phases of testing and approval.
There are reasons why clinical trials take so long. Smaller phase one trials are meant to ensure treatments are safe before moving on to bigger tests. Drug developers also want to be certain of their results before sending their findings to the FDA.
“There are two key goals in a clinical trial: one is to protect participants and not put them at unnecessary risk; the other is to collect high-integrity data to answer the research question,” says John H. Alexander, professor of medicine at Duke University School of Medicine. “There are just dozens of things that we have layered on that don’t achieve either of those goals.”
Those layers include everything from requiring repeat training by investigators, duplication in trials and having many local institutional review boards instead of one for large trials, Alexander explains.
Good data can alleviate some of those issues. Data that is easily shared and analyzed can change how clinical trials are run. In some cases, for example, clinical trial researchers might not need to completely replicate the patient experience during the treatment process.
Matthew Clark, senior director of Elsevier R&D Solutions, took part in a study that measured how “concordant animal testing is for predicting human reactions to drugs.” They found that clinical trials would be more relevant if pharma companies decide which animal tests are the most predictive. Furthermore, events reported in pre-marketing trials and post-marketing can make trials more predictive. This publicly available data could be used to streamline the clinical trial design.
Big data and electronic data collection have been around for years. So why are clinical trials still slow?
As clinical researchers implemented data systems into their organizations, they often built processes from scratch and developed their own tracking systems. This makes it extremely difficult to share data with other groups conducting similar studies.
“I think the biggest hindrance is the lack of data exchange standards,” says Hunter Walker, chief technology officer at Atlantic Research Group. “Looking at the medical and electronic health record (EHR) world that is part of healthcare today, a lot of these companies developed big systems that have essentially created silos among stakeholders. After entering data into the system, the user has no easy means for data export, migration, or exchange.”
To prevent these research siloes, researchers are supposed to upload their data in a federal database, even if the study was incomplete or produced poor results. The reality is that research institutions aren’t doing that, writes Science Magazine investigative reporter Charles Piller. The magazine examined 4700 trials and found 32 percent of clinical trial results were never reported to the NIH website ClinicalTrials.gov.
“ClinicalTrials.gov...uses a common format, allowing relatively easy comparisons of results across trials that journal articles rarely make possible,” Piller says. “Doctors, researchers, and potential trial participants rely on the site, to judge from its 215 million monthly page views.”
As a result, you have researchers who are desperate for data. They are scrounging where they can in order to access patient information and existing data which would streamline their trial processes.
Even electronic health records (EHRs) are a stumbling block when it comes to making clinical research easier.
“We have billing claims as, absurdly, our only reliable and easily integratable national source of raw patient data,” says Raj Mehta, assistant program director at AdventHealth. “What we don’t have is anything useful to produce evidence-based medicine. The criticism may seem harsh, but if we could trade all the data silos, all the AI/ML efforts, & all the billing data, for a fully integrated, nationwide, RCT platform in EHRs, we would all do it in a heartbeat.”
Data sharing has the power to speed up clinical trials and improve trial development. For example, Dr. Anthony Fauci praised the use of the Adaptive COVID-19 Treatment Trial in the development of the COVID-19 vaccine. This method was meant to streamline the trial process and move the vaccine to market faster.
“Sometimes called ‘learn as you go’ trials, [adaptive clinical trials] accelerate the testing process by allowing early results to dictate changes in a trial’s objectives, its participant pool and even the standards of comparison it uses,” says Melissa Healy, a health and science reporter at the Los Angeles Times.
Better data also means companies can adapt their treatments based on the needs of patients. Using COVID-19 as an example once again, the FDA released guidelines for vaccine developers to test the effectiveness of their doses on coronavirus variants in February 2021.
According to Noah Weiland, Katie Thomas, and Carl Zimmer at The New York Times, the clinical trial process to test virus variants will look more like the annual studies for flu vaccines. Instead of “lengthy randomized controlled trials,” researchers can draw blood from a small group of volunteers who have received the adaptive vaccine. Both Pfizer-BioNTech and Moderna have said they have mRNA technology that can alter existing vaccines within six weeks.
When researchers aren’t starting from scratch with their data and treatments, they can create trials that move through the testing and approval process faster.
Even outside of the actual patient data sharing, the use of improved data changes how researchers plan clinical trials, from the sites they choose to the at-home monitoring of patients.
“Companies could pool and share data on investigative sites within and across organizations,” says Mary Jo Lamberti, associate director and research assistant professor at Tufts Center for the Study of Drug Development. “Very often large pharmaceutical companies are siloed and may not be aware of information available within their own organizations. Some large clinical research organizations (CROs) already share investigator and site information.”
Additionally, at-home tracking of patients can lead to more data and greater confidence from the research team early on. Take the “trials@home” program by AstraZeneca, for example.
“In conventional studies, we collect very little data between clinic visits, but trials@home may give us an opportunity to enhance the density of data we collect from each patient,” says Natalie Fishburn, VP and global head of clinical data and insights at AstraZeneca. “We are developing a suite of home monitors that have the potential to be used across our clinical trials, some of which have already been validated and others we are taking steps to validate.”
More data leads to greater confidence in the treatment, which means companies can send their results to the FDA faster. Better data collection from reliable testing sites can also expedite the data cleaning process. However, at the core of each of these changes are human researchers who are guiding patients and training physicians to run the trial.
“Data is often hailed as an antidote to the biases of human intuition,” says Bart de Langhe, associate professor of marketing at ESADE Business and Law School. “But effectively using data for decision-making actually requires that we intelligently harness our intuition.”
Data alone will never be the solution for improved clinical trials. CROs and pharmaceutical companies have had access to data for years. However, when strategic planners apply data in better ways and collaborate to share that data, they can improve and streamline the trial process, creating shorter timelines and directly impacting patient outcomes.
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