AZD5582-reactivated cells likely differ from productively infected cells 2266717

Abstract Introduction AZD5582 (AZD) is a SMAC mimetic that reverses latency by activating the non-canonical NF-κB pathway. AZD can trigger 3-4 logs transient viremia in ART-suppressed macaques; however, the reductions in the latent reservoir have been modest. Detailed analysis of the mechanisms is difficult to study due to low amplitude and fluctuating viral load signals. Methods We analyzed longitudinal data from 29 ART-suppressed, SIV-infected rhesus macaques treated with AZD5582 in combination with other agents (e.g., SIV antibodies, N-803, and/or MT807R1). We used a nonlinear mixed-effect modeling framework to fit an ensemble of mechanistic viral-dynamics models to the plasma SIV RNA and SIV CA-DNA measurements. We performed model selection using Bayesian information criteria and parameter identifiability checks, ultimately using the best models’ parameter estimates to infer the AZD5582 mode of action and treatment response mechanisms. Results The viral-dynamics model ensemble successfully reproduced the viral dynamics observed, specifically the AZD5582-associated increase in plasma SIV RNA and the changes in SIV DNA levels. Parameter estimates from the top-performing models consistently indicated that cells reactivated by AZD exhibited lower viral production and a significantly reduced death rate, ranging from 32 to 89% less than other infected cells. Conclusion Mechanistic modeling provides an explanation for the limited reduction in the viral reservoir despite the strong latency reversal achieved by AZD5582. The model revealed that reactivated cells behave differently from fully productively infected cells. This finding suggests that combining AZD5582 with other type of latency reversing treatment may improve the overall effectiveness and robustness of the drug. Funding Source R01 OD011095, R01 AI028433, R01 AI152703, U54 HL143541, UM1-AI164561, Los Alamos National Laboratory 20220791PRD2. Topic Categories Computational and Systems Immunology (COMP)