Clinical Trial Simulation

Antiviral therapy achieves is almost perfectly effective for HIV and hepatitis C. Yet, treatments for many other viruses including SARS-CoV-2, influenza, CMV, HSV-2 and Ebola lead to highly variable therapeutic responses among infected persons. We develop mathematical models which merge viral and immune dynamics, with drug pharmacokinetic and pharmacodynamic properties to accurately recapitulate results from clinical trials, explaining counterintuitive observed results, and predicting optimal treatment strategies.

HIV cure is a major unmet medical need. Current antiretroviral therapies (ART) eliminate HIV replication in CD4+ T cells, prevent progression to AIDS, and allow a normal lifespan. Yet, ART does not eradicate persistent viruses in an anatomically dispersed reservoir of latently infected cells. Therefore, people living with HIV must take ART for their lifetime. We are developing models to explain fundamental mechanisms which sustain the reservoir. We are also working to optimize multiple new therapeutic strategies designed to eradicate latently infected cells.

We developed mathematical models which capture the timing and intensity of innate, humoral and cellular immune responses against SARS-CoV-2 to explain the extraordinary variability in virologic and clinical outcomes. We are currently developing approaches to fit models to newly available multi-scale, non-linear immune response data gathered throughout infection.

Herpes simplex virus-2 (HSV-2) is the leading cause of genital ulcers, a risk factor for HIV acquisition, and a cause of severe disease in immunosuppressed individuals and infants. There is no effective vaccine for HSV-2. Licensed antiviral therapies are only partially effective. The accessibility of mucosal tissues where HSV-2 replicates allow frequent sampling to measure viral loads and spatial features of cellular immune responses, enabling a unique window into viral infection micro-environments. Through a combination of human studies, animal models, and mathematical modeling, we aim to characterize the extremely rapid interactions between replicating virus and tissue-resident immune cells.

We develop models linking viral load within an infected individual to spread in the general population. We applied these models to household transmission data for multiple human herpes viruses including CMV, EBV, HHV6, and HHV8. We are using similar approaches to SARS-CoV-2 to understand drivers of super spreader events and to estimate the impact of masking, antiviral treatments and vaccines on transmission. We also assisted with modeling community spread of SARS-CoV-2 in King County during the COVID-19 pandemic.

We are developing models which link mechanisms of viral replication and intensifying immune responses with viral evolution within infected individuals and in the general population. These models are intended to explain viral mutation and immune selection pressures driving HIV evolution and the repeated emergence of highly mutated SARS-CoV-2 variants of concern.

Viral infections are a major cause of mortality in cancer patients following stem cell transplantation and chemotherapy. We are developing models to characterize how immune responses with variable effectiveness, lead to different viral dynamic patterns and evolution between immunocompetent and immunosuppressed individuals.