I am a Scientific Director in the Quantitative Medicine Program at the Critical Path Institute (C-Path), and I use statistical modeling and R programming to better understand disease progression and accelerate the medical product development process. I received my Ph.D. in molecular and cellular biology with a minor focus in statistics from the University of Arizona. Since joining C-Path in August of 2020, I have worked with the Transplant Therapeutics Consortium, leading the analyses to support the regulatory endorsement of the iBox Scoring System as a clinical trial endpoint in kidney transplantation, the development of a sample size calculator using the iBox Scoring System as an endpoint in prospective clinical trials, and the development of disease progression models in kidney transplantation. I also work with the Huntington’s disease (HD) consortium, where I have been helping develop and refine models of HD disease progression and patient dropout, as well as the Polycystic Kidney Disease consortium, where I am supervising development of a joint model of total kidney volume and estimated glomerular filtration rate. I have also made key contributions to various other Quantitative Medicine team efforts, such as researching the statistics behind platform trials, randomized delayed start, response adaptive randomization, and other innovative trial design methods for model-informed drug development tools. My PhD work was inspired by evolutionary theory, where I used linear and nonlinear regression models, both simple and mixed, to help understand how new genes arise.