Top 5 Technology Trends to Keep an Eye on in Clinical Research in 2024


January 19, 2024

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There is no denying that technology is continually advancing year by year, month by month, and even day by day. As expected, this affects the scope of clinical research in 2024. While we learn to adapt and implement these technologies in our everyday lives, the clinical research field is working to capitalize upon these advancements for optimal benefits. These are the top technology trends to eye as we move throughout 2024.   Technology trends in clinical research continue to evolve at a very fast pace.  Over the last decade we have seen a movement towards cloud computing which has resulted in the pervasive deployment of decentralized clinical trials.  Some technology trends on the horizon for 2024 could results in even more changes to how we set up and manage clinical research.  Here’s 5 trends to keep an eye on.

Artificial Intelligence and Machine Learning Generation

By no surprise, Artificial Intelligence and Machine Learning is at the top of the list. AI and ML are continually evolving processes that are beginning to prove a sustainable effort in optimizing clinical research efforts. AI and ML models are being piloted to see what areas of clinical research will benefit the most. In an article published by Health and Technology (2023), 5 areas of clinical research are described with potential benefits from AI and ML – preclinical, design, recruitment, conduct and analysis. In a preclinical stage, AI and ML can highlight unmet medical needs by accessing previous preclinical and clinical research datasets, as well as toxicity data to predict safety outcomes and develop models with applicable treatments. Another example is within recruitment, which remains a complex process in clinical research. AI and ML have the ability to comprehend inclusion and exclusion criteria and cross-reference demographics, laboratory numbers, imaging reports, therapeutics, etc. that correlates a patient with a specific trial. With such beneficial potential of AI and ML, clinical trial regulation will continue to develop with inclusion of these topics.

Improvement upon Global Harmonization 

There is an increased push for global harmonization across clinical research. The access and conduction of global clinical trials is important for generalizability in the field. The need for technology that suits globalization by being applicable and usable across trials is evident. Data harmonization is a great place to start. For example, a technology trend to keep an eye out for that supports this push are platforms that ensure standardized data formats, security, shareability and increased data protections. This type of platform promotes the consistency within data and makes it available across countries.

Normalizing Decentralized Trials

Decentralized Clinical Trials are at the forefront of clinical research and have been since the COVID-19 pandemic. Their popularity has continued to grow over the last few years. DCT allows for reach across the population, which promotes diversity in a trial. It has been repeatedly cited that less than 5% of eligible patients participate in clinical trials (Murthy et al., 2004). Virtual telehealth visits, remote data collection and wearable devices allow for subjects who are not located near traditional research sites to participate more conveniently, provide direct real-time data, and improve engagement in the clinical trial. Simply put, they better serve clinical research patients. In 2024, we would expect to see regulations from entities, such as the FDA and EMEA, continue to be developed in regard to DCT and what digitized components are allowed.

Inclusion of Advanced Digital Biomarkers

Digital biomarkers are a technological output that we may see used more within clinical research in the coming year. As we previously mentioned, DCTs can include wearable devices to continuously track specific endpoints, but these types of biomarkers can be applied within your traditional trials as well. Digital biomarkers are measured across layers of hardware, that include wearable, implantable and digestible devices that are used in a participant’s home collecting data that may be impossible to obtain in the clinic (Byrom et al., 2018). These devices can impact the results that clinical trials produce with key data points, personalization, treatment suggestions and disease trend tracking. It will not be surprising to see improving accuracy and precision in the data they produce in the year to come.

Blockchain Technology Implementation

In 2024, you can expect a rise in blockchain technology in clinical research. This technology allows for enhanced audit trails and record tracking, while changing the way that patient data is protected. The integrity and quality of a clinical trial can be undermined in the case of tampering, error or misconduct. It leaves the public with a sense of distrust towards the field. Blockchain technology is the solution. Dr. Natalia Sofia, MSc. (2023) explains that blockchain technology provides highly secure, time-stamped audit trials that play a pivotal role in ensuring reliability and coherence within systems for more informed decision-making regarding clinical trials. The honest facilitation and access address the demanding concerns that come from sensitive data security (De Novi, et al., 2023).

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  • Askin, S., Burkhalter, D., Calado, G., & El Dakrouni, S. (2023). Artificial Intelligence Applied to clinical trials: opportunities and challenges. Health and technology, 13(2), 203–213.
  • Byrom, B., Watson, C., DPhil, H., Coons, S., Eremenco, S., Ballinger, R., McCarthy, M., Crescioni, M., O’Donohoe, P., & Howry, C. (2018). Selection of and Evidentiary Considerations for Wearable Devices and Their Measurements for Use in Regulatory Decision Making: Recommendations from the ePRO Consortium. Value in Health21(6), 631–639.
  • De Novi, G., Sofia, N., Vasiliu-Feltes, I., Yan Zang, C., & Ricotta, F. (2023). Blockchain Technology Predictions 2024: Transformations in Healthcare, Patient Identity, and Public Health. Blockchain in healthcare today, 6,
  • Motahari-Nezhad, H., Fgaier, M., Abid, M. M., Péntek, M., Gulácsi, L., & Zrubka, Z. (2022). Digital Biomarker–Based Studies: Scoping Review of Systematic Reviews. JMIR MHealth and UHealth, 10(10), e35722.
  • Murthy, V. H., Krumholz, H. M., & Gross, C. P. (2004). Participation in Cancer Clinical Trials. JAMA, 291(22), 2720.


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