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  Models of Models: A Translational Route for Cancer Treatment and Drug Development

Ogilvie, L. A., Kovachev, A., Wierling, C., Lange, B. M. H., & Lehrach, H. (2017). Models of Models: A Translational Route for Cancer Treatment and Drug Development. Frontiers in Oncology, 7: 7:219. doi:10.3389/fonc.2017.00219.

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Item Permalink: http://hdl.handle.net/21.11116/0000-0000-F699-E Version Permalink: http://hdl.handle.net/21.11116/0000-0000-F69A-D
Genre: Journal Article

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© 2017 Ogilvie, Kovachev, Wierling, Lange and Lehrach

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 Creators:
Ogilvie, L. A.1, Author
Kovachev, A.1, Author
Wierling, C.1, Author
Lange, B. M. H.1, Author
Lehrach, H.1, 2, Author              
Affiliations:
1Alacris Theranostics GmbH, Berlin, Germany, ou_persistent22              
2Emeritus Group of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_2385697              

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Free keywords: computational model genetically engineered mouse models mechanistic modeling model optimization preclinical models transgenic mice
 Abstract: Every patient and every disease is different. Each patient therefore requires a personalized treatment approach. For technical reasons, a personalized approach is feasible for treatment strategies such as surgery, but not for drug-based therapy or drug development. The development of individual mechanistic models of the disease process in every patient offers the possibility of attaining truly personalized drug-based therapy and prevention. The concept of virtual clinical trials and the integrated use of in silico, in vitro, and in vivo models in preclinical development could lead to significant gains in efficiency and order of magnitude increases in the cost effectiveness of drug development and approval. We have developed mechanistic computational models of large-scale cellular signal transduction networks for prediction of drug effects and functional responses, based on patient-specific multi-level omics profiles. However, a major barrier to the use of such models in a clinical and developmental context is the reliability of predictions. Here we detail how the approach of using "models of models" has the potential to impact cancer treatment and drug development. We describe the iterative refinement process that leverages the flexibility of experimental systems to generate highly dimensional data, which can be used to train and validate computational model parameters and improve model predictions. In this way, highly optimized computational models with robust predictive capacity can be generated. Such models open up a number of opportunities for cancer drug treatment and development, from enhancing the design of experimental studies, reducing costs, and improving animal welfare, to increasing the translational value of results generated.

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Language(s): eng - English
 Dates: 2017-09-012017-09-192017
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: DOI: 10.3389/fonc.2017.00219
ISSN: 2234-943X (Print)
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Title: Frontiers in Oncology
Source Genre: Journal
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Publ. Info: Lausanne : Frontiers Media
Pages: - Volume / Issue: 7 Sequence Number: 7:219 Start / End Page: - Identifier: ISSN: 2234-943X
CoNE: /journals/resource/2234-943X