Clinical Trial Trends For 2024: AI and other Gamechangers in the New Year
AI, patient advocacy groups, digital health technologies, and more. Here’s everything you need to know about the clinical trial trends of 2024—and how they’re reshaping the industry.
A sign of the times: “AI,” “prompt,” and “authentic” have been ranked among the top words of 2023 by famous dictionary publishing companies, Collins, Webster-Merriam, and Oxford. Not only has artificial intelligence (AI) overtaken the way we speak, it’s also transforming every industry—including clinical research.
In 2024, AI will become more sophisticated and reliable in its applications for clinical trials, changing the way we sample, recruit, and manage participants as well as the way we capture, analyze, and report data. For example, APAC is already embracing these changes.
This blog post delves into how AI and other developments will reshape the industry in the coming year. From increased use of sensors and wearables to a growing influence of patient advocacy groups, these shifts are not just enhancing the efficiency of trials but also making them more attuned to the needs of patients. Without further ado, here is our take on clinical trials trends in 2024 and beyond.
The Biggest AI Trends in Clinical Research 2024
Artificial Intelligence for Optimizing Study Design
In 2024, we’re likely to see more researchers experimenting with artificial intelligence to design more effective and safer protocols. AI can analyze vast amounts of medical data, as well as previous trial outcomes, to identify patterns and correlations at a scale not accessible to human researchers. This can lead to more informed decision-making with regard to participant selection criteria, dosing schedules, and endpoint determination. AI can also use historical data to help identify potential risks, enabling researchers to develop mitigation strategies for safer trials.
Predictive Analytics for More Precise Recruitment
Harnessing AI to accelerate participant recruitment has been has been trending for the past few years, and the momentum will continue in 2024. Trial sponsors are using AI to sift through real-world data—such as electronic health records (EHRs), medical histories, and other relevant health information—to find potential participants.
Perhaps, in 2024, we’ll see companies take that a step further: using AI to predict which participants are most likely to benefit from the trial, adhere to its protocol, and remain until completion. This can improve the quality of participant selection, leading to more successful outcomes.
Growing Use of Voice Recognition
Voice recognition technology uses natural language processing (NLP)—a subset of AI—to capture data in a new way. Instead of typing, texting, or writing answers to ePRO questionnaires, the technology speaks to the participants, the participants answer back, and their responses are recorded. Because of its convenience, this model has the potential to address two major clinical trial challenges: participant engagement and adherence.
A noteworthy example is CardioCube,1 a software developed for Amazon's Alexa. Designed to collect patients' medical histories directly and interface with electronic medical records, CardioCube has shown promising results. In a feasibility study involving cardiovascular patients, it demonstrated an impressive 97.5 percent accuracy rate in gathering cardiovascular risk factors and past medical history.1(p4)
While promising, the technology does have its challenges. Users have reported voice assistants misunderstanding their accents.1(p4) Additionally, navigating long interactions can be cumbersome: users experienced difficulties while revising responses or were forced to restart the entire process due to errors or the device timing out.1(p4) As with other new technologies, we can expect to see some fits and starts alongside growing rates of experimentation and adoption.
Tighter Guardrails Around AI Monitoring and Analysis
AI tools are currently being used to monitor clinical trials in real time, ensuring adherence to protocols and accelerated identification of issues. This includes monitoring patient compliance and safety based on information gleaned from communications with participants and clinical outcomes that might indicate an adverse event. These anomaly detection models alert site teams to atypical values, providing tighter guardrails to streamline the workflows of study managers. The annotations from study managers, in turn, help to further refine and train the AI.
In addition to monitoring data, AI can also analyze it. AI-powered image analysis is being used for more accurate and faster interpretation of medical images, such as MRIs, CT scans, and x-rays. This aids in better disease detection, progression monitoring, and treatment response evaluation.2
Greater Adoption of Sensors and Wearables
AI can help to interpret large quantities of data collected from sensors and wearables in a way that maintains both accuracy and privacy. For example, a deep learning-enabled walking stick is capable of sensing a person's unique walking gait pattern. The patient’s live motion status at home can be mirrored in a virtual environment. If a fall occurs, the anomaly is detected immediately.
In September of 2023, there were more than 4,000 clinical trials that registered use of a device for data capture—a small fraction of the more than 400,000 studies registered.3 But, as sponsors recognize the benefits of collecting and transmitting data from people’s homes—almost instantaneously and with minimal effort from participants—we will see a greater interest in deploying devices for secondary or exploratory endpoints as a way to test their feasibility in studies, both from a participant experience and a data quality standpoint.
Other Important Trends Shaping the Industry
A Turning Point for ePRO Measurement Comparability
Will this be the year we can finally put the comparability debate between paper and digital to bed?
An ISPOR task force recently released a report4 assessing the need to demonstrate comparability among the various ways to collect patient responses (e.g., using a tablet or smartphone app versus paper). The task force reviewed research evidence and found comparability was regularly demonstrated between electronic and paper and across various devices.4(p623) The task force now says that additional comparability testing is no longer needed for many questionnaires.4(p625)
In the words of Florence Mowlem, PhD, Vice President of Science for ObvioHealth, during her session with the TransPerfect LifeSci Talks podcast: “I hope this can be a turning point for the industry with regard to comparability testing. We can stop having [comparability] conversations so frequently, and instead we can start talking about optimizing our electronic measures for all individuals.”5
Big Pharma Expanding into DCT Business
The efficiency and streamlined workflows inherent in digital clinical trial technology are encouraging some pharma companies to explore opportunities in the DCT business. AstraZeneca, in collaboration with Fortrea and Parexel, recently announced the launch of its own digital health solutions provider, Evinova, for the “delivery of clinical trials and better health outcomes.”6 Interestingly, this new company will not just serve AstraZeneca, but outside companies as well.
Is this a good idea? Only time will tell. The design and conduct of a successful digital clinical trial requires digital thinking and design as well as smart technology, so it’s likely that pharma and biotechs will find themselves on a steep learning curve.
Patient Advocacy Groups Will Play a Bigger Role
The FDA recently released its patient-focused drug development regulatory guidelines,7 putting an increased emphasis on patient engagement and centricity in clinical research. At the urging of regulatory agencies, pharmaceutical companies are starting to recognize the need for patient input at every stage of the drug development process. This means patient advocacy groups will play a larger role—from advising on protocols to supporting clinical trial education and helping to recruit prospective participants.
This is certainly a positive trend for the industry, as input from these groups can lead to the development of drugs that are more aligned with patients’ needs and preferences, including factors like dosage forms, treatment schedules, and side effect management. A recent report8 estimates patient input during the early stages of study design may help to avoid research protocol amendments; improve enrollment, adherence, and retention; and, consequently, accelerate product launch by as many as 2.5 years.
Pharmacies Ramp Up Trial Recruitment
In 2023, CVS announced its exit from the business of clinical trials. In contract, its rival, Walgreens, announced its commitment to the industry.9 Walgreens signed 15 contracts for clinical trial recruitment in Q3 of 2023, versus 8 contracts in Q2—a sign of growing momentum.10 In 2023, we also saw additional players entire the space, including Kroger, which is currently recruiting for two trials.11 And, across the globe, ObvioHealth announced a partnership with Australia’s largest retail pharmacy, Chemist Warehouse.
So, while some thought this trend was dead when CVS revealed its sunset of trial activities,12 in fact it’s the opposite. Pharma companies recognize the benefits of these partnerships: they provide access to millions of potential trial participants who are already attuned to their own health. We’ll be seeing more pharma companies collaborate with these grocery and pharmacy giants in the coming year.
Conclusion
As we look towards the future of clinical trials, it's evident that technology and patient engagement are at the forefront of industry evolution. The integration of AI, the increasing reliance on digital tools like ePRO, and the growing role of patient advocacy groups are becoming integral components of clinical research. These developments promise to make trials more patient-friendly and tailored to individual needs. They signal a shift towards a more inclusive, data-driven, and efficient approach to drug development. As these trends continue to unfold, they hold the potential to significantly accelerate drug discovery and improve health outcomes.
References:
1. Gouda P, Ganni E, Chung P, et al. Feasibility of Incorporating Voice Technology and Virtual Assistants in Cardiovascular Care and Clinical Trials. Curr Cardiovasc Risk Rep. 2021;15(8). doi: 10.1007/s12170-021-00673-9
2. Tang X. The role of artificial intelligence in medical imaging research. BJR Open. 2020;2(1):20190031. doi: 10.1259/bjro.20190031
3. NIH. Search: Wearables OR Sensors. clinicaltrials.gov. Accessed September 9, 2023. https://clinicaltrials.gov/search?term=Wearables%20OR%20sensors&aggFilters=status:com%20act%20enr
4. O’Donohoe P, Reasner DS, Kovacs SM, et al. Updated Recommendations on Evidence Needed to Support Measurement Comparability Among Modes of Data Collection for Patient-Reported Outcome Measures: A Good Practices Report of an ISPOR Task Force. Value Health. 2023;26(5):623-633. doi: 10.1016/j.jval.2023.01.001
5. Wade M, Mowlem F. The Age of Bring Your Own Device: Considerations for Accessibility in Trial Design with Dr. Florence Mowlem. LifeSci Talks. 2023. Accessed December 10, 2023. https://open.spotify.com/episode/6lmzurY7eSm9EOmg1OfKGo?si=b6c8d3ce30c34697&nd=1
6. AstraZeneca launches Evinova, a health-tech business to accelerate innovation across the life sciences sector, the delivery of clinical trials and better health outcomes. Press Release. AstraZeneca. November 20, 2023. Accessed December 10, 2023. https://www.astrazeneca.com/media-centre/press-releases/2023/astrazeneca-launches-evinova-health-tech-business-to-accelerate-innovation-across-the-life-sciences-sector.html
7. FDA. FDA Patient-Focused Drug Development Guidance Series for Enhancing the Incorporation of the Patient’s Voice in Medical Product Development and Regulatory Decision Making. FDA.gov. April 2023. Accessed December 9, 2023. https://www.fda.gov/drugs/development-approval-process-drugs/fda-patient-focused-drug-development-guidance-series-enhancing-incorporation-patients-voice-medical
8. Levitan B, Getz K, Eisenstein EL, et al. Assessing the Financial Value of Patient Engagement: A Quantitative Approach from CTTI’s Patient Groups and Clinical Trials Project. Ther Innov Regul Sci. 2018;52(2):220-229. doi: 10.1177/2168479017716715
9. Japsen B. Walgreens Committed To Clinical Trials Business Despite CVS Health’s Exit. Forbes. May 15, 2023. Accessed December 9, 2023. https://www.forbes.com/sites/brucejapsen/2023/05/15/walgreens-committed-to-clinical-trials-business-despite-cvs-move/?sh=249272aa6ceb
10. Landi H. Walgreens to close 60 VillageMD clinics as part of aggressive cost-cutting strategy. Fierce Biotech. October 12, 2023. Accessed December 9, 2023. https://www.fiercehealthcare.com/providers/walgreens-close-60-villagemd-clinics-part-aggressive-cost-cutting-strategy
11. Clinical Trials. Kroger.com. Accessed December 9, 2023. https://www.kroger.com/health/clinical-trials
12. Mesa N. CVS Health Winding Down Clinical Trial Business. BioSpace. May 17, 2023. Accessed December 9, 2023. https://www.biospace.com/article/cvs-health-winding-down-clinical-trial-business-/
