We propose a multi-metric flexible Bayesian framework to support efficient interim decision-making in multi-arm multi-stage phase II clinical trials.
Proposing and comparing methods of estimation for cluster-randomized test-negative design trials.
Human and mosquito movement can lead to underestimation of the intervention effect in trials of vector interventions; as such, the protective efficacy of Wolbachia is likely even higher than reported in the primary trial results.
Note: This was originally the transcript of a 3-minute abstract presentation I gave during World TB Day 2023. I think it’s a nice, layman’s summary of some of the work I have been doing regarding decision-making.
De-risking decision-making for clinical trials in TB therapeutics How do YOU make decisions?
Let’s say your friends wanted to get tacos for lunch. [Bear with me for this analogy.] The most important step, without argument, is to identify a restaurant that has tacos on the menu.
Introgression of wMel into A. aegypti populations is effective in reducing the focal transmission of dengue virus, leading to reduced case incidence.
My postdoctoral research at UCSF has focused on the development of a Bayesian-supported framework for decision-making in adaptive Phase II trials; work performed in collaboration with the UNITE4TB public-private consortium to advance Phase II clinical trial design and identify novel tuberculosis (TB) therapeutics. TB is the leading cause of death from an infectious disease worldwide. Though treatable and curable, current therapeutic regimens have been ineffective in controlling the spread of TB.
Introgression of wMel into A. aegypti populations was effective in reducing the incidence of symptomatic dengue and resulted in fewer hospitalizations for dengue among the participants.
Vector-borne diseases are a growing threat to global health. I help develop statistical methods to rigorously evaluate the impact of novel preventive interventions.