Project Summary Problem: Despite remarkable advances in HIV treatment over the last 2 decades, viral suppression in people living with HIV (PLWH) still requires lifelong adherence to expensive, multidrug, daily dosing regimens. The stark reality of this challenging treatment modality is that almost 50% of PLWH in the US are not virologically suppressed. An HIV cure that achieves sustained, medication-free remission is desperately needed. The main obstacle to this cure is the latent reservoir, a subset of long-lived, latently infected cells harboring replication-competent virus. Investigational cure strategies seek to activate then clear (Target and Clear) this reservoir by pairing latency-reversing agents (LRAs) with immunomodulators. Over 50 small molecules across 7 mechanistic classes have been identified as potential LRAs. Yet in the last decade of research, none have advanced past early stages of clinical development due to unacceptable toxicity or inadequate efficacy. A critical component of drug development that has been widely overlooked in the development of LRAs, is identification of PK/PD indices (e.g. Cmax/EC50) associated with drug effect. These targets are essential for optimizing doses to achieve a concentration profile within the therapeutic window. Overarching Goal: By leveraging the predictive power of PK/PD modeling and simulation, we aim to accelerate the advancement of LRAs from the Laboratory to the Patient. We have developed an in vitro to in vivo extrapolation (IVIVE) system that incorporates a cellular model of latency and can simulate human PK. We will employ this system to identify PK/PD indices for latency reversal. Study Design: We have selected 6 promising LRAs from 3 mechanistic classes to assess using our novel IVIVE model. We identified these LRAs based on published human PK data, and prioritized LRAs with existing or anticipated clinical study results in PLWH. In AIM 1 we will use established cellular models of latency to characterize the LRA concentration vs latency reversal relationship across a 4-log concentration range by fitting sigmoid Emax models to estimate the following parameters for each LRA: EC25, EC50, EC75, and EC90. In AIM 2 we will identify PK/PD indices for HIV latency reversal by simulating the human PK profile for each LRA and conducting dose fractionation studies. We will fit sigmoid Emax models for 12 combinations of PK/PD indices (Cmax/IC50, AUC/EC90, Time>EC75, etc.) vs HIV latency reversal and determine the best fitting models. We will validate our model (where possible) by cross-referencing our predictions with clinical trial results. Anticipated Outcome: This work will guide dose optimization for a broad portfolio of LRAs and assist in selecting effective doses for animal and human studies. Through clinical validation, we will establish our novel IVIVE model as a new paradigm to accelerate the development of HIV cure strategies.