In this discussion with Kathleen Mandziuk, Vice President of eClinical Development & Delivery at ICON, we explore the dynamic world of clinical trials. Kathleen offers insights on the persistent challenges of patient recruitment, the revolutionary role of AI and digital tools, and the critical importance of diversity and inclusion. As the industry shifts towards patient-centric trials, Kathleen provides a nuanced perspective on how these elements reshape drug development.
Moe: Why is patient recruitment challenging in clinical trials, and how has it evolved?
Patient recruitment is complex due to access, knowledge, and potential trust issues within patient communities. Historically, many patients were unaware of clinical trials or lacked access because their healthcare providers may not have been involved in clinical research. Today, the challenge is compounded by the plethora of options available to patients in healthcare and clinical trials. For instance, multiple sponsors may target the same indications in rare diseases, creating competition. Patients now evaluate the burden of participation, such as time and travel, and weigh clinical trial participation against other healthcare options. This evolution means that recruitment is not just about enrolling patients but ensuring they choose the proper trial that aligns with their medical needs and lifestyle.
Moe: AI and digital tools are seen as game-changers for recruitment. How can companies move from piloting to full-scale implementation?
At ICON, we’ve embraced AI and machine learning to enhance our processes and evidence-generation methods. A prime example is our Cassandra tool, which uses AI to predict post-marketing requirements by regulatory bodies like the FDA and EMA. This foresight allows sponsors to plan their product lifecycle more effectively, collecting the necessary evidence early in the product lifecycle. The industry has come a long way from the days of paper case report forms (CRFs) to electronic data capture (EDC), and now we’re poised to make significant strides with AI and digital endpoints. The key is to integrate these technologies into the drug development process, moving beyond experimentation to create tangible efficiencies and insights. By doing so, we can streamline operations and improve the overall effectiveness of clinical trials, ultimately benefiting patients and sponsors alike.
Moe: How can AI be leveraged to create personalized engagement strategies and reduce dropout rates?
AI and machine learning offer powerful tools for understanding treatment patterns and engaging with patient communities. By analyzing real-world data, we can identify a representative sample of the patient population, considering factors like age, comorbidities, and demographics. This understanding helps us design trials that reflect real-world conditions, ensuring safety and efficacy data apply to broader populations. Additionally, AI can pinpoint where patients receive healthcare, allowing us to engage those providers in patient education and recruitment. This targeted approach and broader patient engagement strategies like social media and community outreach can significantly enhance participation and reduce dropout rates. By personalizing engagement, we can create a more patient-friendly trial experience.
Moe: How can organizations ensure digital innovation aligns with patient needs, not just operational efficiencies?
One innovative approach we’ve implemented at ICON is clinical trial tokenization, which reduces patient burden, especially in long-term follow-up scenarios common in complex cellular and genetic treatment trials. Through tokenization, we can maintain passive and secure visibility of clinical trial patients over extended periods by minimizing the need for patient visits. Additionally, as trials use increasingly digital endpoint collection methods, digital risk detection allows us to identify and address potential issues in real-time, keeping patients engaged and ensuring data integrity. Solutions such as telehealth visits, patient concierge, digital stipend processing, and home health visits can streamline operations and enhance the patient experience, making participating and remaining in trials easier. By focusing on patient needs, we can ensure that digital innovations truly benefit those involved in clinical research.
Moe: What is ICON’s stance on DEI, and how can AI improve representation in clinical trials?
Diversity, equity & inclusion (DEI) is a cornerstone of our trial design and execution. Study populations must mirror real-world patient demographics to ensure our data is representative. For example, if a trial only includes the youngest and healthiest patients, we risk missing safety signals that might appear in a more diverse real-world population. By leveraging AI to understand the epidemiology of the disease and the demographics of affected populations, we can tailor our recruitment and engagement strategies to ensure inclusivity. This approach enhances the study findings’ validity and ensures that all patient groups benefit from new treatments. We can improve clinical trials’ quality and impact by prioritizing DEI.
Moe: How are sponsors balancing digital innovation with regulatory compliance, particularly in data integrity and patient safety?
Regulatory bodies are increasingly recognizing the value of digital endpoints, especially for long-term follow-up in trials for cellular and genetic treatments. Traditional methods of data collection are often impractical for the extended timelines required. By incorporating digital tools like Bluetooth devices, we can gather real-time data on patient health, ensuring compliance with regulatory expectations while maintaining patient safety. These innovations are about meeting requirements and enhancing the quality and reliability of the data we collect. By balancing innovation with compliance, we can ensure that clinical trials remain cutting-edge and safe for participants.
Moe: How can the industry create a unified, patient-friendly digital clinical trial ecosystem?
The need for cohesive solutions is paramount as the clinical trial industry becomes more digitized. Rather than piecing together disparate technologies, we’re seeing a shift towards integrated, end-to-end solutions with configurable modules. This approach reduces the risk of data silos and ensures seamless communication between systems. Patient-facing technologies also need to be supported by an operational framework of education and engagement, such as telehealth and concierge services. Sponsors, CROs, and regulators all have a role in fostering this ecosystem by supporting the development of standardized, interoperable technologies and engagement that prioritize patient experience and data integrity. Working together can create a more unified and efficient clinical trial landscape that benefits all stakeholders. This collaboration is key to advancing the industry and improving clinical trial implementation.
Moe: Is there anything else you’d like to add about the future of clinical trials?
Integrating clinical research into regular healthcare delivery is crucial, mirroring patients’ expectations post-COVID. By making trials more accessible and engaging, we can continue developing essential drugs for real-world patients. Keeping an open dialogue and adapting to these changes is key to advancing our industry. By aligning clinical trials with everyday healthcare practices, we can ensure that patients receive the best possible care and that new treatments are developed efficiently and effectively. This integration is essential for the future of clinical research and patient care.
Moe Alsumidaie is Chief Editor of The Clinical Trial Vanguard. Moe holds decades of experience in the clinical trials industry. Moe also serves as Head of Research at CliniBiz and Chief Data Scientist at Annex Clinical Corporation.
