% IMPORTANT: The following is UTF-8 encoded.  This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.

@ARTICLE{vanVliet:137647,
      author       = {van Vliet, Erwin and Daneshian, Mardas and Beilmann, Mario
                      and Davies, Anthony and Fava, Eugenio and Fleck, Roland and
                      Julé, Yvon and Kansy, Manfred and Kustermann, Stefan and
                      Macko, Peter and Mundy, William R and Roth, Adrian and Shah,
                      Imran and Uteng, Marianne and van de Water, Bob and Hartung,
                      Thomas and Leist, Marcel},
      title        = {{C}urrent approaches and future role of high content
                      imaging in safety sciences and drug discovery.},
      journal      = {Alternatives to animal experimentation},
      volume       = {31},
      number       = {4},
      issn         = {1868-596X},
      address      = {Heidelberg},
      publisher    = {Springer},
      reportid     = {DZNE-2020-03969},
      pages        = {479-493},
      year         = {2014},
      abstract     = {High content imaging combines automated microscopy with
                      image analysis approaches to simultaneously quantify
                      multiple phenotypic and/or functional parameters in
                      biological systems. The technology has become an important
                      tool in the fields of safety sciences and drug discovery,
                      because it can be used for mode-of-action identification,
                      determination of hazard potency and the discovery of
                      toxicity targets and biomarkers. In contrast to conventional
                      biochemical endpoints, high content imaging provides insight
                      into the spatial distribution and dynamics of responses in
                      biological systems. This allows the identification of
                      signaling pathways underlying cell defense, adaptation,
                      toxicity and death. Therefore, high content imaging is
                      considered a promising technology to address the challenges
                      for the 'Toxicity testing in the 21st century' approach.
                      Currently, high content imaging technologies are frequently
                      applied in academia for mechanistic toxicity studies and in
                      pharmaceutical industry for the ranking and selection of
                      lead drug compounds or to identify/confirm mechanisms
                      underlying effects observed in vivo. A recent workshop
                      gathered scientists working on high content imaging in
                      academia, pharmaceutical industry and regulatory bodies with
                      the objective to compile the state-of-the-art of the
                      technology in the different institutions. Together they
                      defined technical and methodological gaps, proposed quality
                      control measures and performance standards, highlighted cell
                      sources and new readouts and discussed future requirements
                      for regulatory implementation. This review summarizes the
                      discussion, proposed solutions and recommendations of the
                      specialists contributing to the workshop.},
      keywords     = {Animal Testing Alternatives / Animals / Drug Discovery:
                      methods / Hazardous Substances / Imaging, Three-Dimensional:
                      methods / Models, Biological / Pharmaceutical Preparations /
                      Predictive Value of Tests / Reproducibility of Results /
                      Toxicity Tests: methods / Hazardous Substances (NLM
                      Chemicals) / Pharmaceutical Preparations (NLM Chemicals)},
      cin          = {AG Fava 1},
      ddc          = {610},
      cid          = {I:(DE-2719)1013016},
      pnm          = {342 - Disease Mechanisms and Model Systems (POF3-342)},
      pid          = {G:(DE-HGF)POF3-342},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:25027442},
      doi          = {10.14573/altex.1405271},
      url          = {https://pub.dzne.de/record/137647},
}