Literature DB >> 21426031

In vitro safety pharmacology profiling: what else beyond hERG?

Jacques Hamon1, Steven Whitebread, Valerie Techer-Etienne, Helene Le Coq, Kamal Azzaoui, Laszlo Urban.   

Abstract

One of the main reasons for drug failures in clinical development, or postmarket launch, is lacking or compromised safety margins at therapeutic doses. Organ toxicity with poorly defined mechanisms and adverse drug reactions associated with on- and off-target effects are the major contributors to safety-related shortfalls of many clinical drug candidates. Therefore, to avoid high attrition rates in clinical trials, it is imperative to test compounds for potential adverse reactions during early drug discovery. Beyond a small number of targets associated with clinically acknowledged adverse drug reactions, there is little consensus on other targets that are important to consider at an early stage for in vitro safety pharmacology assessment. We consider here a limited number of safety-related targets, from different target families, which were selected as part of in vitro safety pharmacology profiling panels integrated in the drug-development process at Novartis. The best way to assess these targets, using a biochemical or a functional readout, is discussed. In particular, the importance of using cell-based profiling assays for the characterization of an agonist action at some GPCRs is highlighted. A careful design of in vitro safety pharmacology profiling panels allows better prediction of potential adverse effects of new chemical entities early in the drug-discovery process. This contributes to the selection of the best candidate for clinical development and, ultimately, should contribute to a decreased attrition rate.

Entities:  

Mesh:

Substances:

Year:  2009        PMID: 21426031     DOI: 10.4155/fmc.09.51

Source DB:  PubMed          Journal:  Future Med Chem        ISSN: 1756-8919            Impact factor:   3.808


  15 in total

1.  Dark chemical matter as a promising starting point for drug lead discovery.

Authors:  Anne Mai Wassermann; Eugen Lounkine; Dominic Hoepfner; Gaelle Le Goff; Frederick J King; Christian Studer; John M Peltier; Melissa L Grippo; Vivian Prindle; Jianshi Tao; Ansgar Schuffenhauer; Iain M Wallace; Shanni Chen; Philipp Krastel; Amanda Cobos-Correa; Christian N Parker; John W Davies; Meir Glick
Journal:  Nat Chem Biol       Date:  2015-10-19       Impact factor: 15.040

Review 2.  Reducing safety-related drug attrition: the use of in vitro pharmacological profiling.

Authors:  Joanne Bowes; Andrew J Brown; Jacques Hamon; Wolfgang Jarolimek; Arun Sridhar; Gareth Waldron; Steven Whitebread
Journal:  Nat Rev Drug Discov       Date:  2012-12       Impact factor: 84.694

Review 3.  The determination and interpretation of the therapeutic index in drug development.

Authors:  Patrick Y Muller; Mark N Milton
Journal:  Nat Rev Drug Discov       Date:  2012-08-31       Impact factor: 84.694

4.  Preclinical evaluation of BAY 1075553, a novel (18)F-labelled inhibitor of prostate-specific membrane antigen for PET imaging of prostate cancer.

Authors:  Ralf Lesche; Georg Kettschau; Alexey V Gromov; Niels Böhnke; Sandra Borkowski; Ursula Mönning; Christa Hegele-Hartung; Olaf Döhr; Ludger M Dinkelborg; Keith Graham
Journal:  Eur J Nucl Med Mol Imaging       Date:  2013-08-17       Impact factor: 9.236

5.  A bioluminescence method for direct measurement of phosphodiesterase activity.

Authors:  Antoine Younès; Yevgeniya O Lukyanenko; Alexey E Lyashkov; Edward G Lakatta; Steven J Sollott
Journal:  Anal Biochem       Date:  2011-05-30       Impact factor: 3.365

Review 6.  A guide to picking the most selective kinase inhibitor tool compounds for pharmacological validation of drug targets.

Authors:  Joost C M Uitdehaag; Folkert Verkaar; Husam Alwan; Jos de Man; Rogier C Buijsman; Guido J R Zaman
Journal:  Br J Pharmacol       Date:  2012-06       Impact factor: 8.739

Review 7.  Using human genetics to improve safety assessment of therapeutics.

Authors:  Keren J Carss; Aimee M Deaton; Alberto Del Rio-Espinola; Dorothée Diogo; Mark Fielden; Diptee A Kulkarni; Jonathan Moggs; Peter Newham; Matthew R Nelson; Frank D Sistare; Lucas D Ward; Jing Yuan
Journal:  Nat Rev Drug Discov       Date:  2022-10-19       Impact factor: 112.288

8.  Concordance and predictive value of two adverse drug event data sets.

Authors:  Aurel Cami; Ben Y Reis
Journal:  BMC Med Inform Decis Mak       Date:  2014-08-22       Impact factor: 2.796

9.  Machine learning guided association of adverse drug reactions with in vitro target-based pharmacology.

Authors:  Robert Ietswaart; Seda Arat; Amanda X Chen; Saman Farahmand; Bumjun Kim; William DuMouchel; Duncan Armstrong; Alexander Fekete; Jeffrey J Sutherland; Laszlo Urban
Journal:  EBioMedicine       Date:  2020-06-18       Impact factor: 8.143

10.  In silico mechanistic profiling to probe small molecule binding to sulfotransferases.

Authors:  Virginie Y Martiny; Pablo Carbonell; David Lagorce; Bruno O Villoutreix; Gautier Moroy; Maria A Miteva
Journal:  PLoS One       Date:  2013-09-06       Impact factor: 3.240

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.