Principal Scientist
Applied BioMath
Kimiko McGirr PhD is a Principal Scientist at AppliedBioMath passionate about leveraging mathematical modeling for drug development. Kimiko earned her PhD in Bioinformatics and Computational Biology with an NIH Big Data to Knowledge Certificate from the University of North Carolina at Chapel Hill in 2020. Under the mentorship of Henrik Dohlman and Timothy Elston, her research identified the origin and targets of feedback loops regulating yeast MAPK phosphorylation in response to osmotic stress by integrating machine learning, ODE systems modeling, and experimental techniques. Prior to her doctoral work, Kimiko earned her BS in Molecular and Cellular Biology from Johns Hopkins University in 2015. During that time, her research endeavors investigated a variety of signaling mechanisms in yeast, Arabidopsis, and mice, inspiring her to understand signaling at a systems-level. Recently, her interests have been in using models to help design antibody-drug conjugates, assessing both efficacy and toxicity.