Nont Kosaisawe

About Nont Kosaisawe

I am a cellular biologist with expertise in imaging, working with live-cell imaging and high-content imaging to study cell signaling and accelerate drug discovery.

I completed an M.D. degree with first-class honor from Mahidol University in Thailand, in 2013. After graduation, I started working as an internal medicine intern at Phranangklao Hospital, the largest hospital in western Bangkok, Thailand's capital city. Right from the start, I realized the reality that medical decisions are made on coarse-level information. For example, many colon cancer patients receive the same chemotherapeutic regimen because they have the same clinical staging. Even though it has been shown for years, any single tumor mass can contain thousands of sub-clonal populations. At this critical juncture, I realized that if I wanted to make a real impact on medical care, I needed precise statistical data to guide medical decisions

This realization brought back one of the questions that keep bugging my mind; how does a cell integrate intracellular and extracellular information to make a decision? I concluded that the only way to answer this question is to visually “see” information being processed inside an individual cell. I joined Albeck Lab at UC Davis as a Ph.D. student and spent five years studying the effect of metabolic conditions on growth signaling pathways response in real-time. I combined a time-lapse live-cell microscopy technique with kinase live biosensors to visualize kinase activities in real time over a period of days. I developed a customized MATLAB algorithm to automatically identify and track hundreds of thousands of individual cells from time-lapse videos. I discovered that the mitochondrial ATP production rate in mammalian cells is not constant and varies from cell to cellI am compiling a database of single-cell growth-signal response patterns under 200+ metabolic conditions with more than 1 million data points. I am also building an autoencoder-based time series clustering algorithm to reveal growth signal patterns in different metabolic states. I hope that this study will guide us to a metabolic environment that might make cancer
susceptible to targeted therapy.

After graduation, I joined Genentech, World's first biotech company, as a senior imaging specialist and continued my passion for cellular imaging. Currently, I am working on developing and implementing image-based phenotypic screening, specifically Cell Painting, for drug discovery.