In July 2019 I had the opportunity to visit the AbbVie campus in North Chicago with six other media folks. Our purpose for being there was to tour the company’s Development Design Center (DDC) and to hear from three executives: Rob Scott, chief medical officer and VP of development; Howard Jacob, VP and head of genomic research; and Kyle Holen, head of the Development Design Center. The visit provided a detailed look into what AbbVie sees as the future of clinical trials.
Three Major Challenges
Scott believes you cannot conduct trials of the future, or what he calls doing trials millennial style, by using tools from the past. There are major challenges the industry needs to overcome, and new tools are required to do so. First, there is the time and cost to conduct trials.
Finally, there is the lack of real-time monitoring of patients participating in trials. For example: If a metric in a trial is blood pressure, measuring a patient’s vitals once a month doesn’t provide the quality of data that you could get from measuring it continuously through a connected watch.
Put those three factors together and you see why Scott believes there needs to be a new clinical paradigm in place for clinical trials. Scott believes that new paradigm could be in place in the next five years and has the potential to transform every step of a clinical trial. He also expects new technologies will be incorporated into almost every step of the process.
A New Paradigm
Those technologies will include:
Social media and web platforms to gain patient insights, receive feedback on feasibility, promote trial awareness, and provide reminders.
Wearables, sensors, and connected clinical devices can assist with remote monitoring, continuous monitoring, passive data collection, digital endpoints and biomarkers, medication adherence, and drug supply tracking.
Predictive analytics will assist with protocol design, validating study feasibility, identifying patients and sites, study surveillance, and risk-based monitoring.
Mobile applications will play a crucial role by helping patients find trials, performing eConsent, providing reminders and notifications, progress tracking, medication adherence, patient reported outcomes (ePRO), and clinical outcomes assessments (eCOA).
Tele-Medicine will enable remote investigators and virtual sites.
The final piece is eClinical applications such as CTMS (clinical trial management system), EDC (electronic data collection), eTMF (electronic trial master file), and more.
“There is no phase of the drug development process that can’t be improved and made more efficient via the implementation of these technologies,” says Scott. “It’s time to stop discussing them and start implementing them.”
3 Major Changes
The new clinical trial paradigm that Scott envisions has three main components. The first is digital trials. AbbVie first dipped its toe into the digital pool in 2017 when it put a wearable device into three trials. One measured movement as a quality of life measure, one measured itchiness by noting the amount of patient scratching done at night, and the third was used for patients with Parkinson’s disease. Scott notes AbbVie learned a lot from the three trials. Today, just two years later, the company mandates that every clinical team entering a Phase 1 study have a digital strategy. If that strategy includes a wearable or other connected device, the device is validated in Phase 2 and implemented in Phase 3 with a regulatory approved endpoint.
Second, Scott foresees the day when there will be alternative approaches to placebos in clinical studies. Placebos do not do much to build patient support of trials, and we have all heard stories of patients attempting to sabotage trials by determining if they are on the placebo. After making that determination, many will stop taking the medicine and drop out of the trial. Scott believes that in some cases, we have enough pre-existing data that can be used to predict the progress of patients versus others who are taking the active treatment.
The final component is big data and machine learning. Algorithms can be used to suggest the most efficient trial designs and procedures. Additionally, machine learning can also be used to predict site enrollment, country and site selection, real-time assessment of study enrollment predictions, and real-time data transfer with instantly updated data. Scott notes machine learning and algorithms can also be used to access analyze large data sets to better predict populations and predict outcomes in a trial.
“Put all of that together and we will have patients wearing sensors, in trials optimized by AI and machine learning, providing more data than we ever could have dreamed of collecting in the past,” says Scott. “Much of that data will be collected from patients at work or sitting in the comfort of their homes. That model has the potential to eliminate all three of the challenges currently plaguing clinical trials.”
The DDC Is Created To Assist Researchers
This is where the DDC enters the picture. AbbVie describes it as a center to strengthen and optimize clinical programs. If you are an AbbVie researcher working on a trial for an investigational treatment, the DDC is there to help you make that trial better.
“The design lab is there to encourage new ideas,” says Holen. “The people who work in the Center could be best described as futurists. They are experts on the latest technologies that can improve trials and are there to help you make your study better. The primary tools we use are wearable sensors and predictive analytics. Together, we believe they can optimize clinical decisions.”
Holen shared two examples of projects the Center is working on. One is matching patients to trials. AbbVie is working with health research network TriNetX. TriNetX has blinded data on 300 million patients and access to 150 million patient EMRs from more than 100 hospital systems, all gathered and used while protecting patient privacy. If AbbVie is planning for a trial, and has produced its eligibility criteria, TriNetX can determine how many patients in its network would be eligible. It can then contact the hospital systems to see if they are interested in the trial. If so, the hospitals can then contact the patients to see if they want to learn more.
Tempus is another company AbbVie has partnered with to help bring the right trials to the right patients Located in Chicago, Tempus will gather and analyze clinical and molecular data using AI. The goal is to better enable personalized medicine by using genomic tests to understand a patient’s tumor at the molecular level. That genomic information can then be used to better match patients to trials.
The second example revolves around the use of machine learning. AbbVie gathered four million data points on 1,000 clinical sites from multiple data sources. While it would be impossible for a human to analyze the data, it was no problem for a machine. Through the analysis, AbbVie identified which sites were the most likely to recruit patients for a trial. Other uses of the technology would be predicting the screen fail rate of patients or predicting which patients might be most likely to drop out of a study. With that information, AbbVie can then design a trial with specific support for those patients to help them stay in the trial, such as more frequent monitoring and mobile reminders and notifications.
Open The Door To Virtual Trials
The implementation of these technologies in clinical trials also opens to door to performing more virtual trials in the future. Scott believes virtual trials will be the future of the industry. Research has found that 75 percent of patients, when asked, indicate they are interested in participating in a clinical trial. Unfortunately, 70 percent of those patients are located more than two hours from the site they need to visit. That makes trial participation difficult for some patients, and impossible for others.
“In the future, patients will no longer always have to travel to clinics for some trials,” says Scott. “They could be at home or at work, wearing digital devices, and sending a stream of data to researchers. Meetings can take place on a laptop via Skype or Zoom. And apps on smart phones will allow patients to record outcomes as they occur. We will have better data, happier patients, and shorter and less costly trials.”