Digital Biomarkers Could Offer Solutions for Clinical Trial Research

Commentary
Article

The historical health data collected using wearable devices can now be used as secondary endpoints in trials, allowing researchers to monitor responses in real-time without invasive procedures.

Developing a successful drug is no small feat—it requires a decade or more, roughly $1 billion, and the collective effort of countless researchers and patients. Despite this massive investment of time and resources, a staggering 90% of drug candidates in clinical trials don’t make it to market.1 Clinical trials grapple with immense challenges such as patient recruitment, real-time monitoring, data accuracy, and strict protocol adherence, leading to a success rate of just 10%.1

Emerging technologies such as digital biomarkers are carving out promising solutions to these challenges. Take, for instance, Merck’s exploration of digital biomarkers in Parkinson's studies,2 or the recent FDA approval of the Apple Watch’s heart monitoring tool for clinical trials.3 The historical health data collected using such wearable devices can now be used as secondary endpoints in trials, allowing researchers to monitor cardiovascular responses in real-time without invasive procedures, marking a potential revolution in how we monitor patient health and evaluate trial outcomes.

The Era of Digital Biomarkers in Clinical Trials

Digital biomarkers are data collected through digital devices, such as wearable devices, that offer continuous monitoring, real-time data collection, and better patient engagement. Although the integration of digital biomarkers into clinical trials is still in its early stages, the potential to improve robustness and efficiency is significant.

Given this potential, and with the surge in prevalent health conditions such as cancer, cardiovascular diseases, and neurological ailments, accelerating clinical research is crucial. Researchers around the globe are pushing the boundaries of traditional clinical trial and research methods, with notable advancements being highlighted at the recent ASPET 2024 annual conference. To learn more about these developments, Deepika Khedekar, MPharm, a pharmacologist whose work was selected for presentation at the conference, spoke with Pharmacy Times.

Khedekar has led oncology and gastroenterology trials for US and Australia-based pharmaceutical companies for more than a decade and is pioneering efforts to overcome the barriers within clinical trials. Her approach is focused on modernizing trial operations and leveraging emerging technologies in ways that center on patient needs.

About the Expert

Deepika Khedekar, MPharm, is a clinical trial lead at IQVIA Inc., where she spearheads clinical trial monitoring programs for major pharmaceutical companies. In her 12+ years in the pharmaceutical industry, she led phase 1, 2, and 3 clinical trial programs in oncology, gastrointestinal, and respiratory therapeutics.

Q: Can you start by explaining what digital biomarkers are and how they differ from traditional biological biomarkers in clinical trials and research?

Deepika Khedekar, MPharm: Digital biomarkers are objective, quantifiable data collected through digital devices like wearables, smartphones, and artificial intelligence (AI) systems. These devices continuously monitor various health parameters, such as heart rate, activity levels, and sleep patterns, providing real-time data. In contrast, traditional biological biomarkers are typically derived from bodily fluids or tissues, such as blood samples or biopsies, and are usually measured at specific intervals during clinic visits.

The key difference lies in the nature and frequency of data collection. Digital biomarkers offer continuous, real-time health monitoring, enabling a more dynamic and precise assessment of a patient's health status. This is particularly beneficial in clinical trials focusing on areas like neurology, oncology, and cardiovascular research, where real-time monitoring can provide critical insights into disease progression and treatment effects that may not be possible with discrete measurements associated with traditional biomarkers.

Q: What specific challenges in clinical research and trials can digital biomarkers help address.

Khedekar: Digital biomarkers have the potential to tackle some of the core challenges in clinical trials. Take the Apple Heart Study, for example. They used Apple Watches to monitor over 400,000 participants for atrial fibrillation (AF). This study demonstrated how digital biomarkers derived from these wearables can simplify trial recruitment and monitoring while also allowing trials to scale in a resource-efficient manner.4

Digital biomarkers also improve participant safety and add precision to these trials. In the Apple Heart Study, the watch's pulse sensors flagged irregular heartbeats, which were then confirmed with an ECG patch in 34% of the cases.4 This real-time monitoring meant that doctors could step in quickly when needed, improving patient safety. Digital biomarkers are great for early disease detection, too. Researchers at UT Southwestern Medical Center are using AI to analyze speech patterns and catch early signs of Alzheimer’s disease.5 These AI-driven digital biomarkers can spot cognitive issues before they become clinically apparent, allowing for earlier and potentially more effective intervention.

Lastly, digital biomarkers keep participants engaged and compliant. Wearable devices provide continuous feedback, which helps keep participants informed and motivated to adhere to the study protocol, ultimately enhancing data quality and trial retention rates.

Q:Given their potential benefits, why do you think the adoption rate for digital biomarkers is still relatively low? What are the main hurdles?

Khedekar: Even though digital biomarkers offer great benefits, there are a few challenges that we will need to address. For starters, data security is a major concern; we need to ensure that the health data collected is well-protected against breaches. Additionally, the regulatory landscape is complex and time-consuming to navigate, which can slow down the integration of digital biomarkers into clinical trials.

Ethical issues are also significant—making sure data privacy and fair use without bias is crucial. Plus, there's the technical challenge of getting different digital technologies to work together smoothly. This means integrating various devices and data formats into a unified system, which requires standardization across platforms. Lastly, making these tools accessible and inclusive for diverse populations globally is another major hurdle. Ensuring that digital biomarkers are user-friendly and available to all participants, regardless of their location or socio-economic status, is essential for broad adoption and representativeness in clinical trials.

Q: What inspired you to develop the BioGuard Framework?

Khedekar: Having led clinical trials in oncology, gastroenterology, and cardiovascular therapeutic areas for over 12 years, I saw firsthand the limitations of conventional trial methods. I realized that digital biomarkers could address many of these challenges, but their adoption has been slow because they come with their own set of issues. This inspired me to develop the BioGuard Framework. I wanted to create a comprehensive strategy that tackles these obstacles head-on—ensuring data security, regulatory adherence, inclusivity, and ethical standards. My goal was to provide a structured approach that helps researchers and organizations maximize the potential of digital biomarkers while safeguarding the integrity of clinical trials.

Q: How does the BioGuard Framework address data security and regulatory compliance challenges in integrating digital biomarkers into clinical trials?

Khedekar: The BioGuard Framework tackles data security by advocating for advanced measures like AES-256 encryption and Zero-Knowledge Proofs. This approach ensures patient data is encrypted and validated without exposing sensitive information, providing robust protection against breaches.

On the regulatory side, the framework recommends establishing a Digital Biomarker Regulatory Council. This council would develop specific guidelines for integrating digital biomarkers into clinical trials, ensuring they meet regulatory standards set forth by governing bodies like the FDA and EMA, making the compliance process smoother and more transparent for researchers. By prioritizing data security and regulatory adherence, the framework facilitates the seamless integration of digital biomarkers into clinical trials, ensuring the integrity and safety of trial data.

Q: What strategies does the BioGuard Framework propose for interoperability, accessibility, and ethical use of digital biomarkers in clinical trials?

Khedekar: The BioGuard Framework promotes interoperability and standardization by creating common standards for digital biomarkers. This allows different devices and systems to work together seamlessly, facilitating efficient data sharing and analysis. For accessibility and inclusivity, the framework aims to make digital biomarker tools user-friendly and available to diverse populations globally. This broadens participant recruitment, improving the representativeness of trial results.

Moreover, the framework upholds high ethical standards for the use of AI and digital data. It encourages the adoption of fairness indicators and diverse datasets to minimize bias in AI algorithms, ensuring responsible use of digital biomarkers. Additionally, the framework focuses on ethical AI practices and innovative trial designs, such as Hybrid Trial Models and Digital-Biomarker Enabled Adaptive Trials, demonstrating a commitment to ethical and responsible research practices.

Furthermore, the framework emphasizes transparency in communicating with participants about how their data will be used, prioritizing their consent and privacy. By integrating these comprehensive strategies, the BioGuard Framework creates a secure, efficient, and inclusive environment for clinical trials, ultimately enhancing their overall success.

Woman looking at her heart rate on her smart watch

Image credit: © sitthiphong | stock.adobe.com

Q: For organizations interested in adopting the BioGuard Framework, what strategies or steps would you suggest they take?

Khedekar: For organizations looking to adopt the BioGuard Framework, I recommend a phased approach. In phase 1, organizations can start with a thorough assessment of their current trial operations and identify areas where digital biomarkers could add value. In phase 2, document and present these findings to all stakeholders within the organization including but not limited to trial coordinators, regulatory teams, and other relevant personnel. Educate them about the goals and benefits of integrating digital biomarkers into clinical trials, emphasizing the potential improvements in data quality, participant engagement, and trial outcomes.

Then for phase 3, select a trial where digital biomarkers can be integrated and implement the framework. This phase involves setting up the necessary infrastructure, training staff on digital biomarker technologies, and ensuring compliance with regulatory requirements. Once implemented, closely monitor the trial and measure the outcomes, including improvements in data accuracy, efficiency, and participant satisfaction. After the trial, summarize findings and define optimization measures for subsequent integration in other trials.

Finally, scale efforts by leveraging lessons learned and best practices to integrate digital biomarkers into additional trials within the organization. By following this approach, organizations can effectively adopt the BioGuard Framework, enhancing trial efficiency, data quality, and participant engagement.

Q: Finally, what are your thoughts on the future of clinical trials? How do you see them evolving in the coming years?

Khedekar: I believe the future of clinical trials will be shaped by a balanced approach that blends modernized trial operations with emerging technologies. The integration of digital biomarkers will become more widespread, leading to personalized and adaptive trial designs. This will allow us to tailor treatments more precisely and respond quickly to patient needs.

Additionally, as we overcome current challenges like data security and regulatory compliance, we’ll see greater inclusivity and accessibility in clinical trials. Ensuring diverse populations are represented will be key to developing treatments that work for everyone. These advancements will make clinical trials more efficient, robust, and scalable, ultimately improving success rates and patient outcomes.

The Next Frontier in Clinical Trials

While pharmacologists like Khedekar are exploring ways to integrate digital biomarkers into clinical trials to make them more robust and patient-centric, organizations around the world are also starting to embrace this new frontier. Merck is now exploring the use of digital biomarkers in Parkinson's studies.2 Just a couple of weeks ago, the FDA approved the use of the Apple Watch's heart monitoring tool in clinical trials, allowing historical heartbeat data to be used as a secondary endpoint.3 These recent adoptions highlight the potential of digital biomarkers in clinical research.

With 10 million individuals dying each year from cancer and about 19 million from cardiovascular disease, making clinical trials more robust and patient-centric is both urgent and crucial. Digital biomarkers could be the new frontier that acts as the much-needed catalyst in this process.

Reference
1. Sun D. 90% of drugs fail clinical trials. ASBMB Today. March 12, 2022. Accessed June 20, 2024. https://www.asbmb.org/asbmb-today/opinions/031222/90-of-drugs-fail-clinical-trials#:~:text=It%20takes%2010%20to%2015,candidates%20in%20clinical%20trials%20fail
2. Inácio P. Merck joins study of digital biomarkers for Parkinson’s disease. Parkinson’s News Today. March 26, 2024. Accessed June 20, 2024. https://parkinsonsnewstoday.com/news/merck-joins-study-digital-biomarkers-parkinsons-disease/
3. Aguilar M, Lawrence L. Apple pushes into clinical trials with new FDA nod for Apple Watch. STAT. May 8, 2024. Accessed June 20, 2024. https://www.statnews.com/2024/05/08/afib-monitor-apple-watch-fda-approval-clinical-trials/
4. Perez MV, Mahaffey KW, Hedline H, et al. Large-scale assessment of a smartwatch to identify atrial fibrillation. New Engl J Med. 2019;381:1909-1917. doi:10.1056/NEJMoa1901183
5. AI can spot early signs of Alzheimer’s in speech patterns, study shows. News release. UT Southwestern Medical Center. April 12, 2023. Accessed June 20, 2024. https://www.utsouthwestern.edu/newsroom/articles/year-2023/april-alzheimers-in-speech-patterns.html 
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