Rational Design of Mouse Models for Cancer Research Marietta Landgraf, Jacqui A. McGovern, Peter Friedl, Dietmar W. Hutmacher  Trends in Biotechnology  Volume 36, Issue 3, Pages 242-251 (March 2018) DOI: 10.1016/j.tibtech.2017.12.001 Copyright © 2017 Elsevier Ltd Terms and Conditions

Figure 1 Key Figure: Schematic Representation of the Modularity of the Innovative Mouse Model Platform The modular platform allows the generation of specific models for various human cancer types. By designing application-specific tissue-engineered constructs (TECs) and introducing either ectopic or orthotopic tumours into genetically modified and/or humanized mice, various stages and conditions of a certain disease can be modelled. Trends in Biotechnology 2018 36, 242-251DOI: (10.1016/j.tibtech.2017.12.001) Copyright © 2017 Elsevier Ltd Terms and Conditions

Figure 2 Convergence of Biology, Engineering and Medicine to Generate an Innovative Mouse Model Platform. To build a mouse model platform the contribution of several disciplines is essential. Complementary and naturally intersecting areas such as biology, engineering and medicine form key modules for advanced in vivo models. This interdisciplinary approach is indispensable when aiming for mouse models with improved predictive capacity as well as translatability from bench to bedside. Trends in Biotechnology 2018 36, 242-251DOI: (10.1016/j.tibtech.2017.12.001) Copyright © 2017 Elsevier Ltd Terms and Conditions

Figure 3 Proposed Pipeline for Rapid Prototyping and Benchmarking of Mouse Models. Every model evolving out of the mouse model platform needs to be validated against a set of clinical data at critical model-specific milestones. The clinical data should contain stage-matched information about the efficacy or failure of relevant treatment outcomes for the modelled disease. If the validation reveals insufficient predictive value of the mouse model, it should be re-designed and re-evaluated. This approach will result in a benchmarked mouse model with known predictive power and weaknesses, which in turn will allow a rapid translation of this knowledge and results to the clinic. Trends in Biotechnology 2018 36, 242-251DOI: (10.1016/j.tibtech.2017.12.001) Copyright © 2017 Elsevier Ltd Terms and Conditions