The biggest challenge in clinical research today isn’t complexity, it’s the speed at which complexity arrives. Every year, new therapies, data streams, and regulatory expectations land on teams faster than traditional systems can process them. This isn’t just a set of separate trends, it’s a single, connected shift that’s changing how trials are designed and managed.

The fact that the global clinical trials market is set to almost double between 2024 and 2033 shows just how fast the field is changing.¹
Such growth reflects not only the bigger demand for advanced treatments but also the rapid progress in biotechnology and personalized medicine. As clinical research continues to evolve, the field shifts year after year, creating new opportunities for innovation.

So, which key trends defined 2025?

Clinical trial trends are shaped by the demands of a data-driven, patient-focused, and technology-centric landscape. Staying ahead of these innovations is essential for all stakeholders, from CROs to clinical research sites and technology providers.

Novel therapies, such as those targeting rare diseases and cancer, require advancements in trial design and execution to ensure research success. These trials often face challenges such as small patient populations and complex endpoints that demand innovative approaches and adaptive methodologies.

The year 2025 was mostly defined with digital innovations, such as artificial intelligence (AI) and machine learning, and the popularization of decentralized studies. These advancements are not just improving trial efficiency; they are continuing to redefine how trials are designed, executed, and experienced by patients.

AI and Machine Learning

Computational modelling based on AI and machine learning has made various drug discovery processes achievable.³ These include:

  • Drug monitoring
  • Target identification
  • Peptide synthesis
  • Structure and ligand-based virtual screening
  • Chemical compound identification
  • Drug toxicity and many more.

Besides making research easier, AI has become an important factor in trial documentation. Many software solutions embedded AI into its electronic Trial Master File (eTMF) to automate quality control, metadata tagging, and document classification.⁴

Instead of manually sorting documents, a lot of companies rely on AI to file them in real time and flag any inconsistencies. These technologies are also being applied in patient selection and recruitment processes, where AI models can identify eligible patients by analyzing genetic profiles and electronic health records (EHRs).⁴

AI is also being used in protocol design, automation of adverse event detection, and optimization of trial site selection. These advances allow researchers to tailor trial designs for specific populations, reduce variability, and increase precision.⁴

“This year I have seen AI being adopted in several areas. The most interesting ones are protocol writing and protocol design. There are companies making extremely good progress on that in a very collaborative fashion. I also see AI being used to actually accelerate certain activities within the clinical trial life cycle, for example CRF design or implementation of eCRFs, the mapping for submission, and submission of data sets.” says Dr. Urosh Vilimanovich, our Chief Customer Officer.

It is expected that collaboration between AI and clinical organizations will increase over the years as stakeholders recognize the advantage of automated systems.

Decentralized clinical trials

Decentralized trials have become an important part of modern clinical studies, as the pharmaceutical and biotechnology industries increasingly adopt digital solutions for clinical research.

They allow remote monitoring of patients and real-time data collection through digital tools such as wearable devices and mobile applications. These trials enable participants to engage in studies from their homes, which improves patient recruitment. What they offer to stakeholders is a more efficient way of conducting clinical trials, as they help cut down on recruitment times and operational costs.

One of the challenges when pursuing a decentralized clinical trial is to ensure data quality, compliance, and inspection readiness. Because of that, sponsors and CROs should focus on:

  • Data interoperability - ensuring all systems communicate efficiently

  • Automated quality - checks maintaining compliance and Good Clinical Practice (GCP) standards

  • Real-time visibility – enabling faster decisions without compromising data integrity

At Wemedoo, we address these challenges by unifying diverse systems into one interoperable solution. This ensures smooth data exchange and real-time visibility across every data point. Patient information is collected anytime, anywhere, reducing participant burden while providing study teams with continuous insights into therapy responses and overall health, all in a fully compliant, inspection-ready environment.

Patient-centric trials

In 2025, well-executed trials are designed around participants’ needs, improving recruitment, and overall experience. But what does it mean for clinical trials to be patient-centric?

Clinical researchers and systems they use must make trials more convenient for patients, by asking what they need instead of guessing it. In another words, the patient-centric trials are meant to reduce the burden on patients.

A Huron study surveyed over 25 leading research institutions to gain a better understanding of their current and planned practices for improving participants’ experience. They found that 80% of respondents are actively working to improve the experience of those participating in clinical trials, and more than 90% are planning to become more subject-friendly research sites in the next 3 years, by implementing new policies.⁵

On July 23rd this year, the new ICH E6(R3) Good Clinical Practice (GCP) guidelines became effective, representing the most significant update to GCP since its inception almost 30 years ago. The revised guidelines promote patient inclusion and consideration of their viewpoints in various aspects of the process.

One of the key changes in R3 is the modernization of the informed consent process. The guidelines now formally recognize electronic consent (eConsent) and remote consent procedures. They also require that participants be informed about public study registries and be offered the opportunity to receive overall study results at the end of the trial. This represents a major shift toward transparency and respect for study volunteers.⁶

As Dusan Goljic, our Director of Quality Management, explains:

“The R3 revision seriously acknowledged the use of electronic tools in clinical trials. While patient-centricity is the primary goal when implementing these technologies, an even more stringent issue lies in ensuring robust controls over regulatory requirements. This includes preserving data integrity and accuracy within systems, as well as enforcing locked and strict security options. These regulations are driving us not only toward better trials but toward excellence in achieving accurate, reliable, secure, and compliant study datasets.”

As patient-centricity becomes a priority, technology plays a critical role in turning these principles into practice. At Wemedoo, we put patients first. Through unified tools, we can improve patient participation and remove location as a barrier through decentralized studies. Our solution is all-in-one infrastructure where eConsent, eCOA, ePRO, and direct-to-patient workflows are already in place. Every stakeholder sees the same data, in real time, from any location, and every patient can provide their health status daily through their device of choice.

Rare diseases and oncology are in focus

According to Lancet Diabetes & Endocrinology data published in 2023 there are more than 7,000 rare diseases, with only a small portion having effective treatments available 7 In contrast, oncology dominated all pipeline stages in 2025, representing 38% of new medicines in development.⁸

Compared to previous years, there has been an increasing number of approved rare diseases and cancer drugs. This trend encourages pharmaceutical companies to invest significantly in research and development activities, increasing the volume of clinical trials and bringing innovative treatments with faster approval times.⁹

Regulatory frameworks such as the Orphan Drug Act have also played a significant role in boosting investments in these fields. These initiatives have led to an increasing number of orphan drug approvals, with FDA approving 50 novel drugs in 2024.⁹

Advancements in technology also play an important role in shaping rare diseases and cancer. By enabling real-time monitoring of treatment responses, the effectiveness and efficiency of trials is significantly growing.

Wearable technology and connected devices in clinical trials

In 2025, wearable devices became an important tool for capturing real-time data. They present electronic devices that people can wear on their bodies, to collect health-related information. Common examples are fitness trackers, smartwatches, biosensor patches, and even weight scales.

New ICH E6(R3) Good Clinical Practice (GCP) ensures continued relevance in an era of rapid technological and methodological advancements. R3 explicitly recognizes the use of wearable devices which can be integrated into trials to expand data collection and participant monitoring. The guidelines encourage sponsors to explore these digital innovations to make trials more efficient, for example, by facilitating patient recruitment and retention, collecting real-time data from diverse and complementary sources, and reducing site operational burden.⁶

These devices can track various health metrics, such as heart rate, sleep patterns, glucose levels, physical activity, and many more. Thanks to their practicality, they help researchers monitor participants in real time without the need for constant clinical visits.

Data collected from digital devices like wearables is a physiological or behavioral data called digital biomarker. The most important part is that digital biomarkers are continuously gathered in everyday settings and processed in real time. They offer a new way to track health changes such as:

  • A smart watch which monitors heart rate can help identify early signs of cardiovascular stress

  • A wearable patch that tracks sleep patterns may reveal signs of neurological disorder

This type of information leads to faster identification of side effects and better understanding of treatment impacts.

In a recent collaboration, we successfully connected data from the Withings smart scale into oomnia, creating a fully automated, compliant, and real-time data flow from patient homes to the study database, in just two weeks, compared to the typical 3–6 weeks required for such integrations.

Connecting clinical trial ecosystems with interoperability

One of the biggest problems in clinical trials is the fragmentation of data across various systems. As decentralized trials become more popular, managing work of disconnected tools sounds impossible. Trials mostly rely on a mix of technologies to collect data, including wearables, mobile apps for patient-reported outcomes, telehealth platforms, and more. However, these systems often operate in silos, creating barriers to data harmonization and real-time insights.

With interoperability, this problem is fixed by allowing data to flow freely and securely across diverse platforms. Interoperability presents exchange and integration not only of data, but also of processes and workflows across multiple stakeholders. By adopting interoperability standards such as FHIR (Fast Healthcare Interoperability Resources) and CDISC ODM, systems can normalize data structures and ensure compliance with regulatory frameworks such as ICH-GCP.

In an era where protocol complexity is growing and leading to longer timelines of trial execution, an interoperable architecture is no longer optional; it is foundational. oomnia exemplifies this approach: aggregating disparate data streams into a single system. This transformation reduces manual intervention, accelerates decision-making, and supports scalability for next-generation trials.

Clinical trials are changing over time

Impacted by the COVID-19 pandemic, we have seen a change in clinical trials, mostly in a way they are conducted, regulated, and perceived. In recent years, technological advancements and a growing emphasis on patient-centricity have had a huge impact on the clinical research process.

How much this field is continuously changing confirms the fact that several countries have recently undergone significant changes in their clinical trial regulations to align with new advancements.

These advancements have made clinical trials more efficient, patient-centered, and more globally connected. The future of this field holds promise with decentralized trials, real-time data, wearable technology, and improved data analytics.

Despite various innovations in the clinical trial field, a 2024 scientific report⁹ highlights that trials are becoming more complex, with trial complexity scores rising across different phases and therapeutic areas. Because of that, choosing the right solution is the most important part of every study. A unified clinical research information system that connects all necessary programs for efficient trial management is half the battle, and that’s exactly what oomnia delivers.

Curious to learn more about how we can support your clinical trials in 2026? Reach out to our team!

References

Grand View Research. (2025, October). Clinical Trials Market Size To Reach $158.41 Billion By 2033. Accessed December 17, 2025 https://www.grandviewresearch.com/industry-analysis/global-clinical-trials-market

Rehman, A. U., Li, M., Wu, B., Ali, Y., Rasheed, S., Shaheen, S., Liu, X., Luo, R., & Zhang, J. (2025). Role of artificial intelligence in revolutionizing drug discovery. Fundamental Research, 5(3), 1273–1287. https://doi.org/10.1016/j.fmre.2024.04.021

GForce Life Sciences. (n.d.). Trends in clinical trials: Innovation & technology in 2025. Accesseed December 9, 2025. https://www.gforcelifesciences.com/blog/clinical-trial-trends-for-the-future/

Huron Consulting Group. (n.d.). Creating a patient-centric clinical trials experience. Accessed December 9, 2025. https://www.huronconsultinggroup.com/insights/creating-patient-centric-clinical-trials-experience

Cagnazzo, C., Resente, F., Penolazzi, L., & Fagioli, F. (2025). Good clinical practice revision 3: Evolution or revolution? AboutOpen, 12(1), Editorial. https://doi.org/10.33393/ao.2025.3595

Rare diseases: Individually rare, collectively common. (2023). The Lancet Diabetes & Endocrinology, 11(3), 139. https://doi.org/10.1016/S2213-8587(23)00042-6

O’Shea, B. (2025, April 28). Trends in the global drug development pipeline, 2021–2025 [Poster presentation]. ISPOR Clinical Trials Innovation (CTI) Meeting. https://www.ispor.org/docs/default-source/cti-meeting-21021-documents/d8225529-3270-4cf3-bea4-db5724675d61.pdf?sfvrsn=302d9854_0

Grand View Research. (n.d.). Rare diseases clinical trials trends and pipeline outlook. Accessed December 9, 2025. https://www.grandviewresearch.com/market-trends/rare-diseases-clinical-trials-trends-pipeline-outlook

Markey, N., Howitt, B., El-Mansouri, I. et al. Clinical trials are becoming more complex: a machine learning analysis of data from over 16,000 trials. Sci Rep 14, 3514 (2024). https://doi.org/10.1038/s41598-024-53211-z