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iBET, AbbVie and IPO team-up to improve predictivity of ex-vivo tumour models

Development of innovative and predictive 3D cell models for solid tumors

Anti-cancer drug discovery and development has been hindered by high rates of failure in clinical trials, partially due to the use of low-predictive models during pre-clinical studies. These traditional cell models usually do not account for tumour architecture, microenvironment and heterogeneity or for the role of the immune system in tumour progression and response to therapy.

Over the past 10 years, researchers from iBET, in collaboration with researchers from AbbVie and IPOLFG, have been investigating the development of innovative and predictive three-dimensional (3D) cell models for different cancer types, such as colon, ovarian and lung.

In a recent research paper published in MDPI Cancers, we describe a simple method for fast establishment of colorectal cancer patient-derived explant cultures. This tumour model is able to maintain key features of the colorectal cancer microenvironment and genetics during long-term ex-vivo cultures, supporting its potential applicability in pre- and co-clinical settings. Additionally, researchers also established a non-destructive, reliable analytical tool enabling drug development studies in patient-derived models, as described in Nature Scientific Reports.

These publications build upon iBET’s expertise in cancer research as highlighted in a comprehensive guide on co-culture approaches for the representation of heterotypic cell-cell interactions within tumours.

Alongside the development of advanced 3D cell culture models, iBET researchers are also involved in the development of antibodies for immunotherapy, characterization and recapitulation of the tumour microenvironment and development of computational models to study diffusion of antibodies in solid tumours.

The fruitful collaboration between iBET and AbbVie began in 2011, in the scope of IMI-funded project PREDECT, a European Consortium addressing novel laboratory models for preclinical evaluation of drug efficacy in common solid tumours.

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