Literature DB >> 19778217

hERG in vitro interchange factors--development and verification.

Barbara Wiśniowska1, Sebastian Polak.   

Abstract

Literature data analysis shows that the hERG interactions experiments carried out in different conditions with use of different in vitro systems for the same substance can result with different IC50 values. One of the initial components of the proposed drug development supporting system is a set of extrapolation factors enabling the unrestricted choice of some elements of the experimental procedure without resultin significant depreciation. Therefore the main objective of this work was to develop the extrapolation factors allowing inter-system (HEK, CHO, XO) and inter-temperature (room and physiological) IC50 values comparison based on the collected and analyzed hERG IC50 data. The efficiency of the obtained factors was then verified in comparison with the native HEK IC50 values at the physiological temperature. Low values of all the error estimates for the proposed factors evidence their good predictive value which, in turn, ground their application during drug candidates' cardiotoxic risk evaluation or further in silico modeling. Utilization of the proposed factors during drug development process allows a more flexible choice of experimental model to exploit in the electrophysiological investigations, as well as makes it possible to experiment in ambient temperature, which is more convenient. The factors also facilitate data comparisons and allow one to draw reasonable conclusions for further extrapolation.

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Year:  2009        PMID: 19778217     DOI: 10.1080/15376510902777194

Source DB:  PubMed          Journal:  Toxicol Mech Methods        ISSN: 1537-6516            Impact factor:   2.987


  6 in total

1.  Tuning HERG out: antitarget QSAR models for drug development.

Authors:  Rodolpho C Braga; Vinicius M Alves; Meryck F B Silva; Eugene Muratov; Denis Fourches; Alexander Tropsha; Carolina H Andrade
Journal:  Curr Top Med Chem       Date:  2014       Impact factor: 3.295

2.  Towards Bridging Translational Gap in Cardiotoxicity Prediction: an Application of Progressive Cardiac Risk Assessment Strategy in TdP Risk Assessment of Moxifloxacin.

Authors:  Nikunjkumar Patel; Oliver Hatley; Alexander Berg; Klaus Romero; Barbara Wisniowska; Debra Hanna; David Hermann; Sebastian Polak
Journal:  AAPS J       Date:  2018-03-14       Impact factor: 4.009

3.  The open-access dataset for insilico cardiotoxicity prediction system.

Authors:  Sebastian Polak; Barbara Wisniowska; Kamil Fijorek; Anna Glinka; Miłosz Polak; Aleksander Mendyk
Journal:  Bioinformation       Date:  2011-06-06

4.  Early identification of hERG liability in drug discovery programs by automated patch clamp.

Authors:  Timm Danker; Clemens Möller
Journal:  Front Pharmacol       Date:  2014-09-02       Impact factor: 5.810

5.  General Principles for the Validation of Proarrhythmia Risk Prediction Models: An Extension of the CiPA In Silico Strategy.

Authors:  Zhihua Li; Gary R Mirams; Takashi Yoshinaga; Bradley J Ridder; Xiaomei Han; Janell E Chen; Norman L Stockbridge; Todd A Wisialowski; Bruce Damiano; Stefano Severi; Pierre Morissette; Peter R Kowey; Mark Holbrook; Godfrey Smith; Randall L Rasmusson; Michael Liu; Zhen Song; Zhilin Qu; Derek J Leishman; Jill Steidl-Nichols; Blanca Rodriguez; Alfonso Bueno-Orovio; Xin Zhou; Elisa Passini; Andrew G Edwards; Stefano Morotti; Haibo Ni; Eleonora Grandi; Colleen E Clancy; Jamie Vandenberg; Adam Hill; Mikiko Nakamura; Thomas Singer; Liudmila Polonchuk; Andrea Greiter-Wilke; Ken Wang; Stephane Nave; Aaron Fullerton; Eric A Sobie; Michelangelo Paci; Flora Musuamba Tshinanu; David G Strauss
Journal:  Clin Pharmacol Ther       Date:  2019-11-10       Impact factor: 6.903

6.  Toward in vivo-relevant hERG safety assessment and mitigation strategies based on relationships between non-equilibrium blocker binding, three-dimensional channel-blocker interactions, dynamic occupancy, dynamic exposure, and cellular arrhythmia.

Authors:  Hongbin Wan; Gianluca Selvaggio; Robert A Pearlstein
Journal:  PLoS One       Date:  2020-11-04       Impact factor: 3.240

  6 in total

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