Hyun-moon Back (1), Byungjeong Song (1), Sudeep Pradhan (1), Younghoon You (1), Eben Jung (1), Jung-woo Chae (2), Hwi-yeol Yun* (1), Kwang-il Kwon* (1)
(1) College of Pharmacy, Chungnam National University, Korea, (2) Department of Pharmacy, Faculty of Science, National University of Singapore, Singapore
Objectives: hERG assay is a one of traditional approaches for evaluating cardiac safety of drug in early drug discovery [1]. But this assay has major limitation that it does not consider PK properties of drug candidates leading to a weak correlation between in vitro (hERG IC50) and in vivo (delta QTcB) tests. For accurate prediction of QT prolongation in early drug development process, more improved evaluation method is required. In this study, we built the model for predicting QT prolongation considering hERG assay and PK parameters as well as in-vivo QT prolongation in guinea pig.
Methods: For making prediction model of QT prolongation, 14-drugs were selected from each of the four groups that were classified high-, moderate-, minor- and no-risk based on hERG assay. PK profiles and QTcB effect of each drug were obtained after IV administration in guinea pig [2]. PK parameters were estimated by non-compartmental analysis using Phoenix WinNonlin 6.4 and QT interval of each drug was corrected by QTcB equations. Using obtained results, QT prediction model was developed both with multivariate analysis and linear mixed effect model using R and NONMEM.
Results: Using multivariate analysis, two equations were developed:
- % changes of QTc interval = -3.72*IC50 + 0.0015*IC50*(AUCall) -0.0053*(AUCall) +29.41
- % changes of QTc interval = -2.31*IC50 – 0.0014*(Cmax) + 28.40
AUC showed better correlation with delta QTcB and hERG IC50 than Cmax in multivariate analysis (R2: 0.46>0.39). Additionally, linear mixed effect model was developed in NONMEM and the final model, delta QTc interval can be estimated from AUC, Cmax and hERG IC50 value. Exponential model for explaining inter-individual variability was used only on AUC (95.8%) and constant coefficient of variance model was used as a residual error model (43.4 %).
Conclusions: Model for predicting delta QT interval considering hERG IC50 value and PK parameters of each drugs was successfully developed. Equations from multivariate analysis were simple but cannot considering variability. The final linear mixed effect model, in vivo QT prolongation can be estimated more accurately considering both hERG IC50 results and PK parameters (AUC, Cmax) of a given drug.
References:
[1] U.S. Department of Health and Human Services Food and Drug Administration. Center for Drug Evaluation and Research. Guidance for Industry, S7B Nonclinical Evaluation of the Potential for Delayed Ventricular Repolarization (QT Interval Prolongation) by Human Pharmaceuticals.
[2] Testai L, Calderone V, Salvadori A, Breschi MC, Nieri P, Martinotti E. QT prolongation in Anaesthetized Guinea-pigs: An Experimental Approach for preliminary screening of torsadogenicity of drugs and drug candidates. J Appl Toxicol (2004) 24:217-222.
Reference: PAGE 25 (2016) Abstr 5888 [www.page-meeting.org/?abstract=5888]
Poster: Drug/Disease modeling - Safety