ABSTRACT
Alzheimer's disease and related dementias (AD/ADRD) are the most common neurodegenerative brain disease
and characterized by massive loss of memory and learning. AD/ADRD affects more than 6 million Americans
and puts a heavy burden on caregivers in society. However, effective treatment of AD/ADRD is still lacking.
While randomized clinical trials (RCT) can provide reliable evidence on the effectiveness of interventions, they
also have inherent limitations including high cost and long execution time. In addition, RCTs usually are
conducted on selected populations and in specialized environments with limited follow up time. Therefore, they
could have limitations in generalizability to real-world clinical practice. Clinical trial simulation is becoming an
effective approach to assess feasibility, investigate assumptions, and refine study protocols before conducting
the actual trials. Increased availability and granularity of real-world data (RWD) such as electronic health record
(EHR) and medical claims data along with advances in data science offer untapped opportunities to leverage
RWD for trial simulation studies to generate real world evidence (RWE). Nevertheless, there are methodological
barriers and informatics challenges in supporting RWD-based trial simulation studies, especially for AD: (1)
clinical trials need to be represented using a formal and standard approach (i.e., ontologies) to capture the entire
scope of a trial, especially eligibility criteria and outcome measures (i.e., both effectiveness and safety); (2) such
formal and standard representation needs to be made interoperable with RWD standards (e.g., common data
models) to identify study cohorts and relevant, important patient characteristics (i.e., via computable phenotypes
and natural language processing [NLP] methods as rich AD-related information such as cognitive scores often
exist in unstructured clinical notes); and (3) comprehensive and reusable pipelines need to be implemented that
can seamlessly align with existing large-scale RWD for generating high-quality analytic-ready datasets for AD
clinical trial simulation studies. To address these barriers, we propose create and pilot test the ACTS
(Alzheimer's disease Clinical Trial Simulation) system, leveraging three large collections of RWD (~20 million
patients from the OneFlorida network, UT Physician Clinical Data Research Warehouse, and the Optum’s
Clinformatics data). Specifically, we propose to develop novel informatics approaches to represent the entirety
of AD trials while considering the connection of RWD (Aim 1), to use both structured and unstructured RWD to
develop robust phenotyping algorithms that will render previously incomputable AD study traits computable (Aim
2), and to develop the ACTS web application, which will provide an integrated environment for AD researchers
to construct virtual AD trials using an interactive web interface and obtain analytic-ready datasets for trial
simulation studies (Aim 3).
