A novel patient-derived cellular platform for validating microglia-targeted therapeutics for Alzheimer's disease

The scarcity of effective biomarkers and therapeutic strategies for predicting disease onset and progression in Alzheimers disease (AD) is a major challenge to improve much-needed therapeutic outcomes. Conventional drug discovery approaches have been unsuccessful in providing efficient interventions due to their one-size-fits-all nature. As an alternative, personalised drug development holds promise to pre-select responders and identify suitable drug efficacy indicators. In this study, we established a preclinical drug testing strategy by assessing the efficacy of anti-inflammatory drugs in 2D and 3D in vitro models of monocyte-derived microglia-like cells (MDMi) derived from AD and mild cognitive impairment (MCI) patients, and matched healthy individuals. We observed that the cytokine inflammatory profiles of MDMi in response to drugs clustered separately between cohorts, with the 3D model showing a more defined separation between healthy and patient donors than 2D. By ranking donor and cytokine responses to drugs, we identified that drug efficacy was limited in AD patients and involved cohort-specific responsive cytokines. Our findings suggest that MDMi models have the potential to predict disease progression, stratify responders and identify biomarkers for estimating the efficacy of microglia-targeted drugs. Together, our pipeline could serve as a valuable tool to enhance the clinical translational value of preclinical drug screens and ultimately improve drug outcomes for AD.