title: Translational value of mouse models in oncology drug development.
abstract: Much has been written about the advantages and disadvantages of various oncology model systems, with the overall finding that these models lack the predictive power required to translate preclinical efficacy into clinical activity. Despite assertions that some preclinical model systems are superior to others, no single model can suffice to inform preclinical target validation and molecule selection. This perspective provides a balanced albeit critical view of these claims of superiority and outlines a framework for the proper use of existing preclinical models for drug testing and discovery. We also highlight gaps in oncology mouse models and discuss general and pervasive model-independent shortcomings in preclinical oncology work, and we propose ways to address these issues.
authors.affiliation: Department of Molecular Oncology at Genentech, Inc., South San Francisco, California, USA.
authors.forename: Stephen E
authors.initials: SE
authors.lastname: Gould
authors.affiliation: Department of Molecular Oncology at Genentech, Inc., South San Francisco, California, USA.
authors.forename: Melissa R
authors.initials: MR
authors.lastname: Junttila
authors.affiliation: Department of Molecular Oncology at Genentech, Inc., South San Francisco, California, USA.
authors.forename: Frederic J
authors.initials: FJ
authors.lastname: de Sauvage
mesh_terms: D000818:Animals; D045744:Cell Line, Tumor; D004195:Disease Models, Animal; D015195:Drug Design; D004345:Drug Industry; D005818:Genetic Engineering; D006801:Humans; D007107:Immune System; D051379:Mice; D008822:Mice, Transgenic; D009368:Neoplasm Transplantation; D009369:Neoplasms / Q000276:immunology / Q000628:therapy; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D057170:Translational Research, Biomedical / Q000379:methods*