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- W1749952893 abstract "The majority of animal models of cancer have performed poorly in terms of predicting clinical performance of new therapeutics, which are most often first evaluated in patients with advanced, metastatic disease. The development and use of metastatic models of cancer may enhance clinical translatability of preclinical studies focused on the development of nanotechnology-based drug delivery systems and macromolecular therapeutics, potentially accelerating their clinical implementation. It is recognized that the development and use of such models are not without challenge. Preclinical imaging tools offer a solution by allowing temporal and spatial characterization of metastatic lesions. This paper provides a review of imaging methods applicable for evaluation of novel therapeutics in clinically relevant models of advanced cancer. An overview of currently utilized models of oncology in small animals is followed by image-based development and characterization of visceral metastatic cancer models. Examples of imaging tools employed for metastatic lesion detection, evaluation of anti-tumor and anti-metastatic potential and biodistribution of novel therapies, as well as the co-development and/or use of imageable surrogates of response, are also discussed. While the focus is on development of macromolecular and nanotechnology-based therapeutics, examples with small molecules are included in some cases to illustrate concepts and approaches that can be applied in the assessment of nanotechnologies or macromolecules." @default.
- W1749952893 created "2016-06-24" @default.
- W1749952893 creator A5010085701 @default.
- W1749952893 creator A5014844829 @default.
- W1749952893 creator A5057874572 @default.
- W1749952893 creator A5086834252 @default.
- W1749952893 date "2015-12-01" @default.
- W1749952893 modified "2023-09-25" @default.
- W1749952893 title "Preclinical imaging and translational animal models of cancer for accelerated clinical implementation of nanotechnologies and macromolecular agents" @default.
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