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Usage Information

Determinants of the efficacy of HIV latency-reversing agents and implications for drug and treatment design
Ruian Ke, Jessica M. Conway, David M. Margolis, Alan S. Perelson
Ruian Ke, Jessica M. Conway, David M. Margolis, Alan S. Perelson
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Research Article AIDS/HIV Therapeutics

Determinants of the efficacy of HIV latency-reversing agents and implications for drug and treatment design

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Abstract

HIV eradication studies have focused on developing latency-reversing agents (LRAs). However, it is not understood how the rate of latent reservoir reduction is affected by different steps in the process of latency reversal. Furthermore, as current LRAs are host-directed, LRA treatment is likely to be intermittent to avoid host toxicities. Few careful studies of the serial effects of pulsatile LRA treatment have yet been done. This lack of clarity makes it difficult to evaluate the efficacy of candidate LRAs or predict long-term treatment outcomes. We constructed a mathematical model that describes the dynamics of latently infected cells under LRA treatment. Model analysis showed that, in addition to increasing the immune recognition and clearance of infected cells, the duration of HIV antigen expression (i.e., the period of vulnerability) plays an important role in determining the efficacy of LRAs, especially if effective clearance is achieved. Patients may benefit from pulsatile LRA exposures compared with continuous LRA exposures if the period of vulnerability is long and the clearance rate is high, both in the presence and absence of an LRA. Overall, the model framework serves as a useful tool to evaluate the efficacy and the rational design of LRAs and combination strategies.

Authors

Ruian Ke, Jessica M. Conway, David M. Margolis, Alan S. Perelson

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Usage data is cumulative from August 2025 through August 2026.

Usage JCI PMC
Text version 2,139 63
PDF 231 17
Figure 656 4
Supplemental data 132 1
Citation downloads 309 0
Totals 3,467 85
Total Views 3,552

Usage information is collected from two different sources: this site (JCI) and Pubmed Central (PMC). JCI information (compiled daily) shows human readership based on methods we employ to screen out robotic usage. PMC information (aggregated monthly) is also similarly screened of robotic usage.

Various methods are used to distinguish robotic usage. For example, Google automatically scans articles to add to its search index and identifies itself as robotic; other services might not clearly identify themselves as robotic, or they are new or unknown as robotic. Because this activity can be misinterpreted as human readership, data may be re-processed periodically to reflect an improved understanding of robotic activity. Because of these factors, readers should consider usage information illustrative but subject to change.

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