1. Combining an in silico proarrhythmic risk assay with a tPKPD model to predict QTc interval prolongation in the anesthetized guinea pig assay
- Author
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Jin Zhai, Mary Jo Wildey, Elisa Passini, John Imredy, Frederick Sannajust, Kevin Fitzgerald, Anne Chain, Sebastian Polak, Christopher P. Regan, Pierre Morissette, Patrick Fanelli, Jeffrey Travis, and Blanca Rodriguez
- Subjects
0301 basic medicine ,ICH, The International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use ,TN, True Negative ,PPV, Positive Predictive Value ,Pharmacology ,TdP, Torsade de Pointes ,Toxicology ,Membrane Potentials ,0302 clinical medicine ,HTS, High Throughput Screening ,QTcVdW, Van de Water's Heart Rate QT-corrected Interval ,In Silico modeling ,Medicine ,Translational PKPD modeling ,NCEs, New Chemical Entities ,CTD90, Ca2+-Transient Duration at 90% repolarization ,education.field_of_study ,Anesthetized Cardiovascular Guinea Pig ,HR, Heart Rate ,PNV, Predictive Negative Value ,Safety pharmacology ,ECG, Electrocardiogram ,FIH, First in Human ,IKr, rapidly-activating delayed rectifier potassium current ,AP, Action Potential ,QTc, Heart Rate corrected QT Interval ,PX, PatchXpress® ,030220 oncology & carcinogenesis ,Electrophysiologic Techniques, Cardiac ,FP, False Positive ,LVP, Left Ventricular Pressure ,Anti-Arrhythmia Agents ,In silico ,Population ,Guinea Pigs ,QT interval ,Models, Biological ,Article ,Ventricular action potential ,Cell Line ,CVGP, Cardiovascular Anesthetized Guinea Pig ,GP, Guinea Pig ,03 medical and health sciences ,hERG, Human Ether-a-go-go Related Gene ,Pharmacokinetics ,In vivo ,Animals ,Humans ,Computer Simulation ,education ,QT corrected interval ,BP, Blood Pressure ,business.industry ,M5P, M5 trees automated pruning model ,tPKPD, thranslational pharmacokinetic/pharmacodynamic ,FLIPR, Fluorescent Imaging Plate Reader ,Arrhythmias, Cardiac ,ORd, O'Hara Rudy model ,Electrophysiological Phenomena ,030104 developmental biology ,HEK293 Cells ,Models, Chemical ,Pharmacodynamics ,Torsade de Pointes ,EMw, Electromechanical window ,FN, False Negative ,TP, True Positive ,Calcium ,Calcium Channels ,LOO, Leave-One-Out ,business ,APD90, Action Potential Duration at 90% repolarization - Abstract
Human-based in silico models are emerging as important tools to study the effects of integrating inward and outward ion channel currents to predict clinical proarrhythmic risk. The aims of this study were 2-fold: 1) Evaluate the capacity of an in silico model to predict QTc interval prolongation in the in vivo anesthetized cardiovascular guinea pig (CVGP) assay for new chemical entities (NCEs) and; 2) Determine if a translational pharmacokinetic/pharmacodynamic (tPKPD) model can improve the predictive capacity. In silico simulations for NCEs were performed using a population of human ventricular action potential (AP) models. PatchXpress® (PX) or high throughput screening (HTS) ion channel data from respectively n = 73 and n = 51 NCEs were used as inputs for the in silico population. These NCEs were also tested in the CVGP (n = 73). An M5 pruned decision tree-based regression tPKPD model was used to evaluate the concentration at which an NCE is liable to prolong the QTc interval in the CVGP. In silico results successfully predicted the QTc interval prolongation outcome observed in the CVGP with an accuracy/specificity of 85%/73% and 75%/77%, when using PX and HTS ion channel data, respectively. Considering the tPKPD predicted concentration resulting in QTc prolongation (EC5%) increased accuracy/specificity to 97%/95% using PX and 88%/97% when using HTS. Our results support that human-based in silico simulations in combination with tPKPD modeling can provide correlative results with a commonly used early in vivo safety assay, suggesting a path toward more rapid NCE assessment with reduced resources, cycle time, and animal use., Highlights • Cardiac electrophysiological in silico model predicts QTc interval prolongation in the guinea pig. • PKPD model predicts relevant QTc interval prolongation concentration in guinea pig. • Combining the models improves the accuracy of predicting guinea pig QTc effects. • Combining models accelerates assessment of QTc with lower resources and animal use.
- Published
- 2020