Complex Cellular Phenotype Analysis
Dr. LOO Lit Hsin
Senior Principal Investigator

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Group Members
Dr. LOO Lit HsinPrincipal Investigator
Dr. BASU SreetamaPostdoctoral Fellow
Dr. MILLER James AlastairPostdoctoral Fellow
Dr. HTWE Su SuPostdoctoral Fellow
Ms. LEE Jia Ying JoeyResearch Officer
Mr. FU Shufeng OscarResearch Officer
Ms. KONG Jia WenResearch Officer
Mr. CAIN Paul EdwardSoftware Engineer

Research Overview

Our research is focused on the development of in vitro and computational models for predicting the toxicity and/or targets of chemical compounds. We develop novel cellular phenotypic profiling methods and tools that can automatically classify the effects of compounds with diverse or even unknown chemical structures. These technologies allow us to build highly accurate and scalable in vitro cell-based models for predicting organ-specific toxicities. Our models can be used as high-throughput alternatives to animal testing.

Our current projects include:

Toxicity prediction based on phenotypic profiles:
We have developed an approach to predict xenobiotic toxicity using high-throughput imaging of cultured human cells, quantitative phenotypic profiling, and machine learning models. We have applied this approach to human proximal tubular cells (PTCs) in collaboration with Dr. Daniele Zink from the Institute of Bioengineering and Nanotechnology (IBN, A*STAR), and built the first high-throughput in vitro model for nephrotoxicity prediction.

Toxicity prediction based on inflammation and signaling markers:
We have also developed predictive nephrotoxicity models based on the gene expression levels of two pro-inflammatory cytokines, namely interleukin (IL)-6 and -8. These models can accurately predict the toxicity of xenobiotics in both primary human PTCs and induced pluripotent stem cells (iPSC)-derived PTC-like cells.

Single-cell phenotypic profiling:
We develop image and data analysis tools to extract biological information from microscopy images generated from high-throughput, cell-based screening experiments. These tools include the "cellXpress" software platform and the Protein Localization Analysis and Search Tools (PLAST).

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