Investigators:
Tim K. Mackey, PhD: S-3 Research LLC
Joshua Yang, PhD: California State University, Fullerton
MassAITC Cohort: Year 4 (AD/ADRD)
Alzheimer’s disease and related dementias (ADRD) significantly impacts millions of Americans, yet participation in clinical trials remains low, limiting the development of effective therapies. This project aims to develop TrialChat, an AI-powered chatbot and clinical trial navigator designed to increase participation in ADRD clinical trials by providing users with personalized trial recommendations, educational resources, and support throughout the recruitment and enrollment process. Leveraging advanced AI technologies, including a large language model (LLM) chatbot and a machine learning-based trial matching algorithm, TrialChat will be accessible via mobile and web platforms, focusing on usability and tailored features for older adults and caregivers.
The project’s specific aims include the development of an ADRD clinical trial database and trial-matching algorithm integrated into an LLM-powered chatbot, co-designing the tool with older adults and caregivers, and creating a minimally viable product (MVP) for feasibility testing. The chatbot will use an LLM and retrieval-augmented generation (RAG) capabilities to provide reliable, user-friendly responses in English and Spanish. The trial-matching algorithm will incorporate data mining and natural language processing (NLP) to extract trial features from ClinicalTrials.gov and other sources, enabling precise and personalized trial recommendations. Insights from co-design sessions with potential users will guide the design and functionality of TrialChat, ensuring the tool aligns with their needs, preferences, and perceptions of clinical trials and technology.
Data collection will include ADRD clinical trial information, user characteristics, preferences, and feedback from co-design and feasibility testing sessions. The project will result in a trial navigator MVP with features such as interactive ADRD educational content, personalized trial matching, and a user feedback loop to enhance accuracy and relevance. By leveraging AI-driven tools, TrialChat aims to improve access to clinical trial information, promote participation, and support the development of effective ADRD therapies.