- Technical notes
- Beta cells for disease modeling
- Efficient generation of hiPSC-derived disease model for primary hyperoxaluria type 1
- Edited hiPS cell lines for disease modeling
- Power medium for intrinsic clearance studies
- Exploring the potential of a hiPSC-derived hepatocyte disease model for NASH using bioinformatics
- Selection guides
Combining hiPSC-derived hepatocytes and bioinformatics—investigating the potential to model non-alcoholic steatohepatitis (NASH)
Human induced pluripotent stem cells (hiPSCs) provide an unlimited cell source for differentiation into specialized cell types that can then be used in a large variety of applications, such as the assessment of compound toxicity, disease modeling, and (ultimately) regenerative medicine. For these applications, it is of utmost importance that the hiPSC-derived cell types possess equivalent features to their in vivo counterparts.
In this webinar, Dr. Gustav Holmgren describes a study that demonstrates the potential of using hiPSC-derived hepatocytes (hiPS-HEPs) as an important component in generating in vitro models of metabolic diseases such as NASH. The webinar will cover the following topics:
- Application of translational bioinformatics to biomarker discovery and evaluation
- Introduction to NASH and challenges in its modeling
- Evaluation of maturity and functionality of hiPS-HEPs compared to primary hepatocytes
- Induction of an inflammatory state upon lipid accumulation and ER stress
- Demonstration of 2D and 3D co-culture for creating a model for NASH
About the presenter
Gustav Holmgren, PhD
Dr. Gustav Holmgren is a bioinformatician and cell biologist with more than 10 years of experience in human pluripotent stem cell culture and differentiation. He received his PhD in Medical Science in 2016 for his work on In vitro toxicity testing using human pluripotent stem cells and their derivates. Currently, he holds a postdoctoral position in the Translational Bioinformatics group at University of Skövde, Sweden. This group is carrying out bioinformatic studies on stem cell differentiation, in vitro systems for disease modeling, toxicity assessment, and biomarker discovery by utilizing technologies such as next-generation sequencing (NGS) and mass spectrometry together with large-scale data analysis, integration of multi-omics data, and deep learning. Gustav's current project focuses on the analysis of various biological samples using single-cell RNA-seq, with the aim to characterize different cell types and identify vulnerable subpopulations, for example, those affected by toxic drug exposure.
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