The Current Status of Alternatives to Animal Testing and Predictive Toxicology Methods Using Liver Microfluidic Biochips

Prot, Jean‐Matthieu; Leclerc, Éric

doi:10.1007/s10439-011-0480-5

Cited by 27 publications

(14 citation statements)

References 86 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…This will require further advances in the field of physiology-based pharmacokinetic modeling (Blaauboer et al, 2012; Leist et al, 2012b; Louisse et al, 2012; Prot and Leclerc, 2012). …”

Section: Metabolomics In Vitromentioning

confidence: 99%

Metabolomics in toxicology and preclinical research

Ramı́rez

2013

ALTEX

178

117

View full text Add to dashboard Cite

Summary Metabolomics, the comprehensive analysis of metabolites in a biological system, provides detailed information about the biochemical/physiological status of a biological system, and about the changes caused by chemicals. Metabolomics analysis is used in many fields, ranging from the analysis of the physiological status of genetically modified organisms in safety science to the evaluation of human health conditions. In toxicology, metabolomics is the -omics discipline that is most closely related to classical knowledge of disturbed biochemical pathways. It allows rapid identification of the potential targets of a hazardous compound. It can give information on target organs and often can help to improve our understanding regarding the mode-of-action of a given compound. Such insights aid the discovery of biomarkers that either indicate pathophysiological conditions or help the monitoring of the efficacy of drug therapies. The first toxicological applications of metabolomics were for mechanistic research, but different ways to use the technology in a regulatory context are being explored. Ideally, further progress in that direction will position the metabolomics approach to address the challenges of toxicology of the 21st century. To address these issues, scientists from academia, industry, and regulatory bodies came together in a workshop to discuss the current status of applied metabolomics and its potential in the safety assessment of compounds. We report here on the conclusions of three working groups addressing questions regarding 1) metabolomics for in vitro studies 2) the appropriate use of metabolomics in systems toxicology, and 3) use of metabolomics in a regulatory context.

show abstract

“…This will require further advances in the field of physiology-based pharmacokinetic modeling (Blaauboer et al, 2012; Leist et al, 2012b; Louisse et al, 2012; Prot and Leclerc, 2012). …”

Section: Metabolomics In Vitromentioning

confidence: 99%

Metabolomics in toxicology and preclinical research

Ramı́rez

2013

ALTEX

178

117

View full text Add to dashboard Cite

show abstract

“…A spectrum of related designs that organize hepatocytes into cord‐like structures surrounded by microchannels that control molecular and fluid transport and maintain tissue‐like structure/function have been described (Fig. ) . These hepatocentric models were geared toward applications in drug development—metabolism, toxicity, and, possibly, bile transport or small‐molecule drugs (“ADME/Tox”)—though are currently being deployed to create organoid‐like hepatocyte‐NPC structures .…”

Section: In Vitro Modelsmentioning

confidence: 99%

Engineering liver

2014

View full text Add to dashboard Cite

Interest in “engineering liver” arises from multiple communities: therapeutic replacement; mechanistic models of human processes; and drug safety and efficacy studies. An explosion of micro- and nano-fabrication, biomaterials, microfluidic, and other technologies potentially afford unprecedented opportunity to create microphysiological models of human liver, but engineering design principles for how to deploy these tools effectively towards specific applications, including how to define the essential constraints of any given application (including available sources of cells, acceptable cost, and user-friendliness) are still emerging. Arguably less appreciated is the parallel growth in computational systems biology approaches towards these same problems – particularly, in parsing complex disease processes from clinical material, building models of response networks, and in how to interpret the growing compendium of data on drug efficacy and toxicology in patient populations. Here, we provide insight into how the complementary paths of “engineering liver” – experimental and computational – are beginning to interplay towards greater illumination of human disease states and technologies for drug development.

show abstract

“…Consequently, new effective in vitro alternative methods to animal testing are required, some examples of which have already been proposed (Prot and Leclerc, 2012;Rodrigues et al, 2013).…”

Section: Introductionmentioning

confidence: 99%