Modernizing Vaccine Trials by Leveraging eCOA and Harnessing Innovation

The COVID-19 pandemic fundamentally transformed the landscape of vaccine development, driving rapid innovation while ensuring safety and efficacy.  

As we look beyond the recent global pandemic, vaccine research remains imperative for addressing emerging and existing infectious threats. In this blog, we explore how harnessing innovation and utilizing digital health technologies (DHTs) can support sustained global preparedness and accelerate the development of the next generation of vaccines. 

Optimal eCOA for Vaccine Trials 

Vaccine trials rely on capturing comprehensive longitudinal data from each participant to accurately assess immunogenicity and reactogenicity endpoints. In our Clinical Viewpoints series, we underscored how electronic clinical outcome assessment (eCOA) platforms have become essential for collecting high-quality electronic patient-reported outcome (ePRO) data to support these endpoints. 

By leveraging eCOA libraries consisting of standardized assessments for reactogenicity developed based on regulator recommendation¹, along with intuitive interfaces and automated reminders, eCOA platforms can streamline real-time data collection, reduce timelines, lower operational costs, while enhancing participant retention – safeguarding the completeness of the trial’s results and ensuring regulatory compliance.  

Decentralized and BYOD Approaches: Expanding Access and Engagement 

Decentralised and bring-your-own-device (BYOD) strategies have the potential to improve efficiency and patient-centricity by addressing the unique demands of large-scale vaccine trials.  

Decentralized elements, such as home-based ePRO data collection and telemedicine, may simplify participation, and encourage more diverse participation by reducing the number of traditional on-site visits.²  

However, before introducing decentralized elements, researchers should carefully evaluate study design, participant needs, operational logistics, and monitoring strategies required to conduct the trial in accordance with regulatory expectation.^3,4  

With the potential to drive further convenience for participants in vaccine trials, BYOD strategies enable participants to use their own device to complete ePRO. Due to familiarity of the device, participants may be more engaged, leading to improved retention and enhanced data quality.⁵  

While certain considerations must be addressed when implementing BYOD in vaccine trials, such as provisioning devices when participants lack suitable technology and demonstrating device equivalence, regulators are demonstrating increased openness to BYOD data for regulatory submissions, as evidenced by the Pfizer-BioNTech COVID-19 vaccine trial, where majority of the participants used their own devices to collect reactogenicity data.⁶  

Powering Precision and Efficiency Using AI and Machine Learning 

Artificial intelligence (AI) and machine learning (ML) technologies have rapidly advanced in recent years, demonstrating significant potential to transform the landscape of vaccines across the entire development process, including: 

1. Antigen target identification: Identification of disease-specific targets based on differential expression, specificity, and biological relevance by leveraging multi-omics datasets can accelerate antigen target selection.⁷
2. Vaccine candidate design: Molecular simulations can enable the prediction of epitope immunogenicity, as well as antigen-adjuvant compatibility to ensure higher clinical translatability.^8,9  
3. Preclinical evaluation: Prediction of off-target interactions, and modeling of pharmacokinetics (PK) and pharmacodynamics (PD) can optimize screening and testing of vaccine candidates.^10,11  
4. Clinical trial design and management: Predictive analytics can be used to determine suitable patient cohorts to improve statistical power and can optimize endpoints.9 AI-driven systems can also support expedited translation, as well as enhance data collection and management.^12,13  
5. Distribution and rollout: Demand forecasting, supply chain optimization, and real-time monitoring of logistics can be improved using AI-driven systems.¹⁴  

While AI and ML technologies can be used to significantly reduce vaccine development timelines and enhance trial success, it is critical first to address the issues with implementing these technologies, such as ensuring the availability of high-quality data, mitigating algorithmic biases, and establishing ethical frameworks that prioritize transparency.  

Enhanced Data Quality With Wearable Integration 

Integration of wearable DHTs in clinical trials has increased in recent years, allowing for the collection of objective physiological data alongside ePRO. In vaccine trials, wearables can continuously track physiological changes, such as heart rate variability, fever, and sleep disturbance, after vaccination – enhancing safety surveillance by enabling earlier detection of adverse events.¹⁵  

Since wearable data is collected automatically, this minimizes manual entry errors and eliminates participant recall bias, offering a more robust and objective dataset to evaluate safety endpoints.¹⁶  In addition, while effect on daily activity is not routinely evaluated in vaccine trials, objective measurement using actigraphy wearables could provide valuable insights into the impact of the vaccination on the participant’s functional status, informing overall safety and addressing patient-centered outcomes not visible through traditional trial endpoints. 

Regulators are recognizing the potential of wearables to enhance data quality and monitoring in clinical trials, but emphasize the need for robust validation and data integrity.¹⁷ Integration of wearables in vaccine trials should carefully assess the wearable’s validity, usability, and data quality while ensuring it aligns with study objectives and meets regulatory expectations.  

Conclusion: The Future of Vaccine Trials

As regulatory frameworks and technology continues to advance, implementing eCOA and harnessing innovative technologies such as wearables and AI-driven systems, researchers will be better equipped to meet the challenges of vaccine development, enabling more efficient, patient-centered, and globally accessible vaccine trials.