Resumen
Drug-induced liver injury (DILI) is a patient-specific, multifactorial pathophysiological process that needs to be recapitulated in
current in vitro models as best as possible, to improve safety assessment in the drug development process and diagnostics
applications. Given the multifactorial mechanisms of DILI, which contribute to drug attrition in development and in the clinical
practice, there is a need for new liver models that improve physiological relevance and more accurately predict and diagnose
human drug-induced hepatotoxicity. Our aim is to develop and validate a new biomimetic 3D cellular liver model from an
integrated approach, based on printable hydrogels and different cell sources, and able to better recapitulate the hepatic
functionality in vitro. Our proposed printable systems mimic the native liver microenvironment and will allow a high-throughput
prediction of drug toxicity. We will develop physiologically relevant hydrogels from a combination of solubilized liver
decellularized extracellular matrix and hyaluronic acid, which will provide printability by enzymatic crosslinking. Our material
systems will be optimized to reproduce the native liver microenvironment with special emphasis in fine tuning mechanical
properties, improving in vitro hepatocyte functions and maintaining liver-specific phenotype over longer periods. Hybrid bioinks
will be developed for automatic bioprinting, looking for scalability, reproducibility and high-throughput toxicity studies. The
protocols optimized with porcine tissue will be adapted to human tissue obtained from the biobank for a more compatible
technology. We will test and develop our liver models using different hepatic cell sources, including induced pluripotent stem
cells (iPSCs) from different human donors. Liver cells alone or in co-culture with other non-parenchymal cells will be
encapsulated within the hydrogels and their functionality will be assessed by different omics technologies (trasncriptomics,
metabonomics, etc.). This is a breakthrough approach that will also be used to enhance the functional maturity of iPSCs derived
hepatocyte-like cells (HLCs) and improve the performance of cell liver models. Finally, we will validate the potential of the
platform to predict hepatotoxic events, by evaluating the effects induced by drug model compounds (hepatotoxic and
nonhepatotoxic) after acute and chronic exposure, which is a more relevant scenario for therapeutics. This will allow us to design
screening applications that consider the variability of human responses to drugs and also personalised diagnostics and prognosis
of DILI in the clinical setting.
