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We previously showed that human pluripotent stem cells (hiPSCs) provide a suitable model to study metabolic diseases upon hepatocyte-like cell (HLC) differentiation. In particular, HLCs have been used to model cholesterol metabolism regulation, by mimicking the main disease features in vitro. Human iPSCs can be generated from urine samples of patients with a well-described phenotype and carrying specific genotypes. This non-invasive approach allowed the study of LDLR- and PCSK9-mediated autosomal dominant hypercholesterolemia (ADH) as well as PCSK9-mediated familial hypobetalipoproteinemia (FHBL). While the direct link between hiPSCs and patients, as well as the abundance of HLCs provide promising advantages of such strategy, it is impaired mainly by the neonatal characteristic of HLCs as well as the difficulty to perform high throughput studies for pharmacological investigations.

Therefore, to overcome these burdens, we choose to :
1. Differentiate hiPSCs into HLCs in a 3D environment to enhance their maturation;
2. Adapt our 3D differentiation process to a 96 wells format to make it compatible for drug
screening.



Grégory MAUBON

Grégory MAUBON is Chief Data Officer and digital coordinator at HCS Pharma, a biotech startup focused in high content screening and complex diseases. He manages IT missions and leads digital usages linked to company needs. He is also a Augmented Reality Evangelist (presenter and lecturer) since 2008, where he created www.augmented-reality.fr and founded in 2010 RA'pro (the augmented reality promotion association). He helped many companies (in several domains) to define precisely their augmented reality needs and supported them in the implementation.

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