Developing an AI-Guided Triculture Platform to Model NeuroHIV specific Microglial States Under ART Suppression with CellPaint/Morphological and Transcriptomic Readouts

About This Grant

Abstract Despite antiretroviral therapy (ART), HIV-associated brain injury (HABI) persists in over half of people with HIV (PWH), manifesting as chronic cognitive impairment. While HIV-1 primarily infects microglia, driving central nervous system (CNS) neuroinflammation, current preclinical models do not recapitulate the chronic, suppressed infection characteristic of the ART era. Furthermore, they do not capture complex patient genetics and multicellular, glial and neuronal, interactions in a scalable and efficient manner. To address this need for more physiologically relevant models, we propose the development of an AI-guided triculture platform comprising major CNS cell types. This platform will use induced pluripotent stem cell (iPSC)-derived microglia, astrocytes, and neurons, using both morphological profiling and other omics-based profiling to model HABI under ART suppression. AI/machine learning (ML)-driven analysis of cellular morphology, combined with multi-omic data integration, will facilitate rapid classification and prediction of microglial functional states and their impact on neuronal health. Leveraging Modulo's established triculture system, previously successful in yielding therapeutic candidates for amyotrophic lateral sclerosis/frontotemporal dementia (ALS/FTD) currently in Investigational New Drug (IND)-enabling studies, we will construct a scalable HABI model under ART suppression. Our objectives are to (1) develop and validate an HIV-infected, ART-suppressed triculture platform, utilizing AI/ML-driven morphological profiling to classify HABI-specific microglial states; and (2) comprehensively characterize this model through neuroinflammatory profiling, behavioral correlates, and integration with publicly available HABI patient datasets. We hypothesize that our combined computational lab-based triculture system can effectively model HABI pathophysiology under ART conditions, enabling both rapid disease state classification and identification of therapeutic targets. Through the integration of experimental and computational approaches, this platform will provide insights into HABI mechanisms and accelerate therapeutic development. We will disseminate this model to the scientific community through publication and collaboration. Connecting in vitro modeling with patient outcomes offers a powerful tool for investigating neuroimmune dysfunction in HIV and related neurological disorders. Successful implementation will yield a platform for modeling neuroHIV under ART suppression, advancing our understanding of disease mechanisms and facilitating the discovery of novel therapeutic strategies for PWH with cognitive impairment.