Reassessing the Conduct of Patch Clamp Cardiac Ion Channel Assays to Improve Nonclinical Data Translation to Clinical ECG Changes and Proarrythmia Risk.

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作者:Alvarez Baron Claudia, Zhao Jun, Guo Donglin, Mistry Sabyasachy, De Palma Ryan, Ismaiel Omnia A, Wu Wendy W
The Comprehensive in vitro Proarrhythmia Assay (CiPA) initiative proposes integrating multi-cardiac ion channel pharmacology to improve the prediction of drug-induced Torsade de Pointes (TdP) risk. However, several studies under CiPA have demonstrated misalignment between nonclinical and clinical data. One study showed ECG changes induced by chloroquine, lopinavir, and ritonavir suggestive of Ca(V)1.2 and Na(V)1.5 channel block. However, ion channel data used to design the clinical study showed no such interactions. Another study reported TdP cases in patients treated with vanoxerine, a drug with literature data demonstrating similar block potencies for hERG and Ca(V)1.2 channels suggesting lower TdP risk than selective hERG blockers. Finally, astemizole, risperidone, and clarithromycin-"intermediate TdP risk" CiPA drugs-were reported to have hERG-active metabolites, yet hERG data for metabolites were not integrated when developing in silico human myocyte models for risk prediction. To increase the confidence of using nonclinical data in regulatory decision-making, the sources of these inconsistent nonclinical-clinical findings and data gap for metabolites need to be addressed. Here the effects of chloroquine, lopinavir, ritonavir, and vanoxerine on hERG, Ca(V)1.2, and/or Na(V)1.5 channels were studied using protocols consistent with ICH S7B Q&A 2.1 best practices. hERG block potencies for astemizole, risperidone, clarithromycin plus their major metabolites were also determined. The results showed improved alignment between ion channel block profiles and drug-induced ECG changes and proarrhythmia, underscoring the importance of using physiologically relevant experimental protocols, accounting for ion channel-active metabolites, and continuing to build the knowledge base of arrhythmogenesis mechanisms. Data may be found at: https://osf.io/7rfua/.

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