Raymond Reif1. 1. Leibniz-Institut für Arbeitsforschung an der TU Dortmund, Leibniz Research Centre for Working Environment and Human Factors (IfADo), Ardeystrasse 67, 44139 Dortmund, Germany.
Currently, much effort is invested into the development of non-animal testing strategies to identify the potential of compounds to induce systemic toxicity (Hammad, 2013[9]; Stewart and Marchan, 2012[19]). Organotypical in vitro systems are particularly popular in the fields of kidney (Limonciel et al., 2012[15]; Jennings et al., 2012[11]; Valente et al., 2012[20]), heart (Maayah et al., 2014[16]; Bonifacio et al., 2014[1]), liver (Grinberg et al., 2014[8]; Godoy et al., 2013[7]; Schug et al., 2013[18]) and developmental toxicity (Weng et al., 2014[22]; Waldmann et al., 2014[21]; Krug et al., 2013[14]). However, it is also clear that in vitro systems represent valuable tools to study certain mechanisms and endpoints but do not reach the complexity of organs or organisms (Ghallab, 2013[6]).Recently, Daston et al. (2014[3]) published a concept, how future research on non-animal methodology should be designed to overcome current limitations. The authors recommend two complementary and interconnecting concepts. A first work stream should focus on toxicity characterization. Here, critical biological targets and mechanisms leading to toxic effects should be elucidated based on in vitro systems. For this purpose methods such as high-throughput and high content screening and computational modelling will be applied (Daston et al., 2014[3]). A second work stream should focus on translation into regulation. Specific aims are for example methods for grouping, read-across strategies and in vitro methods to derive no-effect levels. In recent years much has been written about grouping strategies and general concepts to improve chemical risk evaluation (Geenen et al., 2012[5]; Kalkhof et al., 2012[12]; Keller et al., 2009[13]; Renwick, 2004[17]; Zbinden, 1993[23]; Gebel et al., 2014[4]; Calabrese, 2013[2]). The present concept paper of Daston and colleagues (2014[3]) belongs certainly to the most fundamental papers in this field and is a must-read for anyone interested in predictive toxicology and alternative methods. However, the authors neglect one major limitation of their strategy: The concept may lead to reasonable predictions for chemicals with unspecific mechanisms of action, meaning that many mechanisms are simultaneously active that lead to the breakdown of cellular functions. However, the concept may fail for highly specific mechanisms of action. The reason for this limitation is that Daston et al. (2014[3]) in agreement with the SEURAT concept recommend focusing on 'critical biological targets' in in vitro systems only (Jennings et al., 2014[10]). This bears the risk of establishing an illusory in vitro world which lacks critical components of real organs or organisms. Let us assume a compound specifically inhibits reabsorption of bile salts in cholangiocytes in bile ducts. How should this mechanism be recognized in an in vitro system that contains hepatocytes only? Moreover, it cannot be excluded that a compound may alter kidney cells in a way that triggers the attack of immue cells. Can we be sure that this specific mechanism would be identified in an in vitro system containing renal proximal tubular epithelial cells only? A research program to in vitro systems only has a high probability to fail. Therefore, a third work stream is painfully missing in the concept of Daston et al. (2014[3]); namely research that systematically compares mechanisms of toxicity in vitro and in vivo. Do the currently available in vitro systems really recapitulate the mechanisms that finally lead to adverse effects in vivo? Finally, it should not be ignored that many mechanisms leading to toxicity in vivo are far from being fully understood. Further research is needed to identify key mechanisms of toxicity in vivo to be able to establish in vitro systems recapitulating these mechanisms. Although it may seem paradox: the successful development of non-animal methodology requires animal experiments.
Authors: Paul Jennings; Michael Schwarz; Brigitte Landesmann; Silvia Maggioni; Marina Goumenou; David Bower; Martin O Leonard; Jeffrey S Wiseman Journal: Arch Toxicol Date: 2014-11-14 Impact factor: 5.153
Authors: Paul Jennings; Christina Weiland; Alice Limonciel; Katarzyna M Bloch; Robert Radford; Lydia Aschauer; Tara McMorrow; Anja Wilmes; Walter Pfaller; Hans J Ahr; Craig Slattery; Edward A Lock; Michael P Ryan; Heidrun Ellinger-Ziegelbauer Journal: Arch Toxicol Date: 2011-11-29 Impact factor: 5.153
Authors: Anne K Krug; Raivo Kolde; John A Gaspar; Eugen Rempel; Nina V Balmer; Kesavan Meganathan; Kinga Vojnits; Mathurin Baquié; Tanja Waldmann; Roberto Ensenat-Waser; Smita Jagtap; Richard M Evans; Stephanie Julien; Hedi Peterson; Dimitra Zagoura; Suzanne Kadereit; Daniel Gerhard; Isaia Sotiriadou; Michael Heke; Karthick Natarajan; Margit Henry; Johannes Winkler; Rosemarie Marchan; Luc Stoppini; Sieto Bosgra; Joost Westerhout; Miriam Verwei; Jaak Vilo; Andreas Kortenkamp; Jürgen Hescheler; Ludwig Hothorn; Susanne Bremer; Christoph van Thriel; Karl-Heinz Krause; Jan G Hengstler; Jörg Rahnenführer; Marcel Leist; Agapios Sachinidis Journal: Arch Toxicol Date: 2012-11-21 Impact factor: 5.153
Authors: Zaid H Maayah; Mushtaq Ahmad Ansari; Mohamed A El Gendy; Mohammed N Al-Arifi; Hesham M Korashy Journal: Arch Toxicol Date: 2013-11-19 Impact factor: 5.153
Authors: Patricio Godoy; Nicola J Hewitt; Ute Albrecht; Melvin E Andersen; Nariman Ansari; Sudin Bhattacharya; Johannes Georg Bode; Jennifer Bolleyn; Christoph Borner; Jan Böttger; Albert Braeuning; Robert A Budinsky; Britta Burkhardt; Neil R Cameron; Giovanni Camussi; Chong-Su Cho; Yun-Jaie Choi; J Craig Rowlands; Uta Dahmen; Georg Damm; Olaf Dirsch; María Teresa Donato; Jian Dong; Steven Dooley; Dirk Drasdo; Rowena Eakins; Karine Sá Ferreira; Valentina Fonsato; Joanna Fraczek; Rolf Gebhardt; Andrew Gibson; Matthias Glanemann; Chris E P Goldring; María José Gómez-Lechón; Geny M M Groothuis; Lena Gustavsson; Christelle Guyot; David Hallifax; Seddik Hammad; Adam Hayward; Dieter Häussinger; Claus Hellerbrand; Philip Hewitt; Stefan Hoehme; Hermann-Georg Holzhütter; J Brian Houston; Jens Hrach; Kiyomi Ito; Hartmut Jaeschke; Verena Keitel; Jens M Kelm; B Kevin Park; Claus Kordes; Gerd A Kullak-Ublick; Edward L LeCluyse; Peng Lu; Jennifer Luebke-Wheeler; Anna Lutz; Daniel J Maltman; Madlen Matz-Soja; Patrick McMullen; Irmgard Merfort; Simon Messner; Christoph Meyer; Jessica Mwinyi; Dean J Naisbitt; Andreas K Nussler; Peter Olinga; Francesco Pampaloni; Jingbo Pi; Linda Pluta; Stefan A Przyborski; Anup Ramachandran; Vera Rogiers; Cliff Rowe; Celine Schelcher; Kathrin Schmich; Michael Schwarz; Bijay Singh; Ernst H K Stelzer; Bruno Stieger; Regina Stöber; Yuichi Sugiyama; Ciro Tetta; Wolfgang E Thasler; Tamara Vanhaecke; Mathieu Vinken; Thomas S Weiss; Agata Widera; Courtney G Woods; Jinghai James Xu; Kathy M Yarborough; Jan G Hengstler Journal: Arch Toxicol Date: 2013-08-23 Impact factor: 5.153
Authors: Tanja Waldmann; Eugen Rempel; Nina V Balmer; André König; Raivo Kolde; John Antonydas Gaspar; Margit Henry; Jürgen Hescheler; Agapios Sachinidis; Jörg Rahnenführer; Jan G Hengstler; Marcel Leist Journal: Chem Res Toxicol Date: 2014-01-21 Impact factor: 3.739
Authors: Vaibhav Shinde; Lisa Hoelting; Sureshkumar Perumal Srinivasan; Johannes Meisig; Kesavan Meganathan; Smita Jagtap; Marianna Grinberg; Julia Liebing; Nils Bluethgen; Jörg Rahnenführer; Eugen Rempel; Regina Stoeber; Stefan Schildknecht; Sunniva Förster; Patricio Godoy; Christoph van Thriel; John Antonydas Gaspar; Jürgen Hescheler; Tanja Waldmann; Jan G Hengstler; Marcel Leist; Agapios Sachinidis Journal: Arch Toxicol Date: 2016-05-17 Impact factor: 5.153