TestAVec researchers discover the accuracy of liver model through in depth machine learning

TestAVec researchers, lead by CSO Michael Themis, have just published a paper validating the iPSC derived liver model employed by the company.

hInGeTox uses iPS cells and turns these cells into liver cells through a stepwise differentiation protocol. Researchers took the transcriptome of these cells and fed the data through machine learning algorithms to show in depth, the validity of these models as true surrogates for liver cells. The analysis revealed that these liver cells closely resemble primary hepatocytes, found in patients as well as exhibiting a lower similarity of various cancers than that of existing liver models.

This proves the usefulness of this model for understanding drug toxicity and providing a naïve background for genotoxicity studies.

You can read the paper under Open Access agreement in Cells. Transcriptomic Profiling of iPS Cell-Derived Hepatocyte-like Cells Reveals Their Close Similarity to Primary Liver Hepatocytes.

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