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Open Access
Applications of tumor chip technology
Lab on a chip, 2018-09, Vol.18 (19), p.2893-2912
2018

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Autor(en) / Beteiligte
Titel
Applications of tumor chip technology
Ist Teil von
  • Lab on a chip, 2018-09, Vol.18 (19), p.2893-2912
Ort / Verlag
England: Royal Society of Chemistry
Erscheinungsjahr
2018
Link zum Volltext
Quelle
MEDLINE
Beschreibungen/Notizen
  • Over the past six decades the inflation-adjusted cost to bring a new drug to market has been increasing constantly and doubles every 9 years - now reaching in excess of $2.5 billion. Overall, the likelihood of FDA approval for a drug (any disease indication) that has entered phase I clinical trials is a mere 9.6%, with the approval rate for oncology far below average at only 5.1%. Lack of efficacy or toxicity is often not revealed until the later stages of clinical trials, despite promising preclinical data. This indicates that the current in vitro systems for drug screening need to be improved for better predictability of in vivo outcomes. Microphysiological systems (MPS), or bioengineered 3D microfluidic tissue and organ constructs that mimic physiological and pathological processes in vitro , can be leveraged across preclinical research and clinical trial stages to transform drug development and clinical management for a range of diseases. Here we review the current state-of-the-art in 3D tissue-engineering models developed for cancer research, with a focus on tumor-on-a-chip, or tumor chip, models. From our viewpoint, tumor chip systems can advance innovative medicine to ameliorate the high failure rates in anti-cancer drug development and clinical treatment. By surpassing the predictive accuracy of conventional 2D cell culture models, tumor chips can reduce reliance on animal models in line with the 3Rs initiative and eliminate false positive selection of ineffective or toxic drugs earlier in the drug development pipeline, saving time and resources. Most importantly, better predictability of human drug response will reduce human risk and improve patient outcomes.

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