Combining an in silico proarrhythmic risk assay with a tPKPD model to predict QTc interval prolongation in the anesthetized guinea pig assay

Autor: 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, Blanca Rodriguez
Jazyk: angličtina
Rok vydání: 2020
Předmět:
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
Zdroj: Toxicology and Applied Pharmacology
ISSN: 1096-0333
0041-008X
Popis: 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.
Databáze: OpenAIRE
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