How Technology Is Shaping the Future of Clinical Trials

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Clinical trials are important for evaluating the safety and effectiveness of drugs, medical devices and treatments. However, conducting these trials is a complex and expensive process that involves extensive planning, execution and analysis. Technology has disrupted all industries recently, and clinical trials are no exception.

In other words, the use of technology in clinical trials is gradually transforming how studies are designed, executed and analyzed. For example, electronic data capture (EDC) systems have replaced paper-based data collection, simplifying managing and monitoring patient data. Moreover, digital technologies such as wearable devices, mobile apps, and remote monitoring tools help collect real-time data and reduce patients’ need to visit clinical sites.

Another area where technology is shaping the future of clinical trials is artificial intelligence (AI). AI algorithms can help identify potential trial participants, analyze patient data and predict patient outcomes. This can help reduce the time and cost associated with clinical trials and improve the accuracy of results.

Additionally, technology has opened the gates toward addressing many critical challenges when conducting clinical trials. These challenges are discussed in detail below.

Challenges in clinical trials

Recruitment and Retention of Participants

Clinical trials require many participants to get a more accurate and holistic outcome, which isn’t always possible. Moreover, retaining participants throughout the trial can be challenging, as they may drop out for various reasons, including lack of efficacy, burden of participation, protocol requirements, financial restraints, lack of support and inconvenience.

According to a report from Clinical Trials Europe in July 2021, 71% of the surveyed participants stated that decentralized clinical trials resulted in better patient recruitment, and 74% mentioned improved patient retention. Patient recruitment and retention play a crucial role as patients dropping out can significantly impact the time it takes to bring a drug to market. Considering the potential costs of delaying market entry, which can range from $600,000 to $8 million per day for blockbuster drugs, it’s important to avoid delays at any cost.

Cost

Clinical trials can be expensive, particularly for larger studies requiring multiple sites and more participants. Moreover, funding for clinical trials can be challenging for researchers not affiliated with large institutions or pharmaceutical companies.

Regulatory Requirements

Government agencies like FDA heavily regulate clinical trials to ensure they are conducted ethically and safely. However, compliance with regulatory requirements can be time-consuming and expensive, posing a serious challenge for conducting clinical trials.

Safety Concerns

Clinical trials involve testing new treatments, which can have unknown side effects. In other words, ensuring the safety of participants is a critical challenge for clinical trial researchers.

Data Management

Clinical trials generate vast amounts of data, which must be collected, analyzed and stored securely. As a result, researchers have to focus on ensuring the efficacy of the clinical trial.

What are the different types of decentralized clinical trials?

There are two types of decentralized clinical trials (DCTs), and which one is used depends on the degree of patient/clinician interaction and proximity to the trial site. Certain trials are better suited to specific types of DCTs. For example, in early-stage trials where there is a higher potential for adverse reactions, it is beneficial for the patient to be near clinicians.

Decentralized Clinical Trials with Patient/Clinician Interaction

Decentralized clinical trials with patient/clinician interaction involve patients who are geographically closer to the trial site and have regular interactions with clinicians. This type of DCT is suitable for early-stage trials where close monitoring and immediate clinician intervention are important due to the higher potential for adverse reactions. Patients benefit from being near clinicians who can provide timely medical attention and support. This approach ensures the safety and well-being of participants and allows for effective management of any unexpected events or adverse effects during the trial.

Remote decentralized clinical trials

Remote decentralized clinical trials rely entirely on digital technologies and connected devices to capture data, eliminating the need for participants to be physically present at the trial site. These trials offer the advantage of greater patient convenience, reduced costs, and improved patient recruitment and retention. Remote DCTs are particularly beneficial for larger Phase II and Phase III trials with a larger number of participants spread across different locations. Participants can take part from the comfort of their own homes, enabling the inclusion of individuals who live far away from trial sites or have limited mobility.

Which technology impacts clinical trials?

As discussed above, technological advancements have revolutionized the clinical trial process and helped researchers to gather, manage and analyze data more efficiently and accurately. This has led to faster and more effective clinical trials, which have helped develop new treatments and therapies for various diseases. Here are some of the technologies that are impacting clinical trials:

AI and Clinical Trials

AI and machine learning (ML) technologies have significantly impacted clinical trials by streamlining various processes. AI can analyze large data sets and identify patterns indiscernible by humans. This capability is particularly useful in clinical trials, where researchers must analyze vast patient data to identify the most effective treatments.

AI can be leveraged to develop predictive models for identifying patients most likely to respond to treatment or identify potential complications that may occur during a trial. ML algorithms can help optimize the trial design and reduce the cost and time required. For example, AI-powered platforms like Deep6 AI can help accelerate patient recruitment by identifying eligible patients from electronic medical records, saving researchers time and resources.

Big Data and Clinical Trials

Big data plays a crucial role in clinical trials, as it enables the aggregation of data from multiple sources. The ability to gather a vast amount of information is essential. However, it is equally important to extract meaningful insights from this data. By leveraging big data, researchers and biostatisticians can draw insights that inform conclusions and recommendations, ultimately shaping the direction of the trial.

Digital platforms serve as valuable tools in this process. They provide the infrastructure and capabilities necessary to manage and analyze big data effectively. Through digital platforms, researchers can access and analyze diverse data sets, including patient-generated data, healthcare provider data and data from clinical trial researchers. These platforms enable the integration and harmonization of disparate data sources, allowing for a comprehensive view of patient health and treatment outcomes.

The insights derived from analyzing big data on digital platforms empower biostatisticians to make informed decisions about trial protocols. They can identify patient populations that are most likely to benefit from a new therapy, refine inclusion and exclusion criteria, and detect potential side effects or adverse events that may have gone unnoticed in smaller-scale trials. By leveraging the power of big data and digital platforms, clinical trials can become more efficient, precise and effective in advancing medical research and improving patient outcomes. You can simplify your clinical trials today through Avantor’s clinical and biorepository services.

Digital Technology and Clinical Trials

Finally, digital technologies, including mobile apps, wearables and telemedicine platforms, are transforming clinical trials. These technologies have made collecting and analyzing data easier, enabling researchers to monitor patients in real-time and identify potential issues seamlessly.

Specifically, mobile health technologies are being used to collect data on patient behavior and symptoms, which can be used later to make rational treatment decisions. For example, the Parkinson’s Disease Digital Biomarker DREAM Challenge used a mobile app to collect data on patients with Parkinson’s disease. This data was used later for new digital biomarkers to improve the accuracy of diagnosis and treatment.

In contrast, wearable devices, such as Fitbits or smartwatches, can also monitor patients’ physical activity and sleep patterns, providing valuable insights into patient health that were previously unavailable. Telemedicine platforms allow patients to communicate with their doctors. These platforms became popular during the COVID-19 pandemic, enabling clinical trials to continue even when face-to-face interactions aren’t feasible.

How technology is addressing the challenges of clinical trials

Clinical trials are important to advance medical research and improve patient outcomes. However, they also present several challenges, such as recruitment, patient data capture and monitoring. Fortunately, technology offers innovative solutions to these challenges, making clinical trials more efficient, cost-effective and patient-centered.

Decentralized Clinical Trials

Decentralized clinical trials involve a combination of digital tools and traditional clinical trial equipment. The latter comes with connectivity capabilities into central data hubs and technology data platforms. DCTs are made possible through technological advances such as electronic data capture (EDC), remote monitoring and mobile health (mHealth) applications.

DCTs offer several benefits, including increased patient engagement, reduced patient burden and improved data quality. However, implementing DCTs can pose challenges, such as ensuring data security and privacy.

Patient Recruitment

Patient recruitment can indeed benefit from technological advancements to enhance diverse patient representation in clinical trials. For instance, companies have utilized algorithms that analyze social media data to identify potential participants who meet specific trial criteria.

This approach saves valuable time and resources while broadening the pool of eligible individuals. Nevertheless, concerns regarding data privacy and the accuracy of social media data must be addressed to ensure ethical and reliable patient recruitment practices.

Capturing Patient Data

Capturing patient data is challenging, especially when patients must visit clinical sites for data collection. New tools, such as wearable devices, mobile apps, and electronic patient-reported outcomes (ePRO), help capture patient data in real-time and from remote locations. For example, wearable devices can track patient vital signs, while mobile apps can collect patient-reported outcomes. This reduces the in-person or physical visits.

Patient-Centered Trials

Patient-centered trials are designed to prioritize the needs and preferences of patients, making the clinical trial process more patient-friendly. New tools such as patient portals and personalized communications make engaging patients easier and keep them informed about the trial process. Additionally, patient advisory boards and patient-centric endpoints can help ensure that the trial design and outcomes are relevant and meaningful to patients.

Monitoring Patients Virtually

Monitoring patients in clinical trials can ensure patient safety and data accuracy. However, traditional monitoring methods, such as in-person visits, can be burdensome for patients and expensive for sponsors.

New tools such as remote monitoring technologies, including wearable devices and mHealth applications, can allow for the virtual monitoring of patients. This approach can reduce the burden on patients and improve the efficiency and accuracy of data collection.

Wearable Devices

Wearable medical devices, such as smartwatches and fitness trackers, are becoming increasingly popular and used in clinical trials to collect patient data. Wearable devices can track patient vital signs, physical activity and sleep patterns, providing real-time data that can be used to monitor patient health and treatment efficacy. However, there are concerns about data privacy and the accuracy of wearable device data, which may require validation before use in clinical trials.

The future of clinical trials

Clinical trials are critical to developing new treatments and medicines and will continue to play a vital role in healthcare. However, the future of clinical trials will likely be shaped by new technologies and innovative approaches to trial design. Some of the key trends that are likely to shape the future of clinical trials include:

Decentralized Clinical Trials

Decentralized clinical trials are likely to become more prevalent in the future. These trials leverage digital technologies to conduct remote monitoring and virtual visits, which can reduce the burden on participants and investigators and increase the speed and efficiency of the trial.

Real-World Evidence

Real-world evidence (RWE) refers to data collected outside traditional clinical trials, such as electronic health records, claims data and patient-generated data. RWE will likely become more important, as it can provide insights into how treatments perform in real-world settings.

Artificial Intelligence

Artificial intelligence has the potential to transform clinical trials by enabling more efficient and accurate data analysis, patient screening and trial design. AI can also help identify new drug targets and improve the efficiency of drug development.

Precision Medicine

Precision medicine involves tailoring treatments to individual patients based on their genetics, lifestyle and other factors. Clinical trials incorporating precision medicine will likely become more common, as they can improve treatment outcomes and reduce adverse effects.

Overall, the future of clinical trials will be shaped by new technologies and innovative approaches to trial design that prioritize patient needs and preferences.

Avantor’s clinical trials research

Avantor is actively engaged in exploring the possibilities and benefits of decentralized clinical trials. They have dedicated resources and expertise in this area, aiming to advance the field of clinical research and contribute to the development of innovative solutions. Read our thought leadership article on Decentralized Clinical Trials to learn about the benefits of DCTs and how the pandemic has increased their adoption.