Tin Phan

INFORME uses information-theoretic design with mixed-effects modeling to adaptively schedule measurements, reducing the number of scans needed for patient-specific treatment response prediction.

The paper develops a mechanistic model linking CD8+ T cell expansion sensitivity to HIV post-treatment control, showing strong correlations with Ki-67 and TCF-1 levels.

This paper develops a generalized resource-allocation growth law to model prostate cancer responses to intermittent androgen deprivation therapy, showing it predicts treatment outcomes and adapts to different schedules.

This study quantifies AZD5582's effect on SIV reservoirs in macaques, showing it reactivates 25% of latent cells per dose and clears 60-79% of reactivated cells.

The paper models viral rebound after nirmatrelvir-ritonavir treatment, finding that target cell preservation and incomplete viral clearance drive rebound, with extended treatment reducing this risk.

The paper uses dynamic models to analyze viral rebound after HIV-1 treatment interruption, showing effector cell expansion rate distinguishes post-treatment controllers from non-controllers.