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Updated: May 14, 2026

A Pacing-Controlled Procedure for the Assessment of Heart Rate-Dependent Diastolic Functions in Murine Heart Failure Models
Published on: July 21, 2023
Age and gender dependent heart rate circadian model development and performance verification on the proarrhythmic
Kamil Fijorek1, Nikunjkumar Patel, Łukasz Klima
1Department of Statistics, Cracow University of Economics, Krakow, Poland. kamil.fijorek@uek.krakow.pl
Background:
There are two main reasons for drug withdrawals at the various levels of the development path - hepatic and cardiac toxicity. The latter one is mainly connected with the proarrhythmic potency and according to the present practice is supposed to be recognized at the pre-clinical (in vitro and animal in vivo) or clinical level (human in vivo studies). There are, although, some limitations to all the above mentioned methods which have led to novel in vitro - in vivo extrapolation methods being introduced. With the use of in silico implemented mathematical and statistical modelling it is possible to translate the in vitro findings into the human in vivo situation at the population level. Human physiology is influenced by many parameters and one of them which needs to be properly accounted for is a heart rate which follows the circadian rhythm. We described such phenomenon statistically which enabled the improved assessment of the drug proarrhythmic potency.
Methods:
A publicly available data set describing the circadian changes of the heart rate of 18 healthy subjects, 5 males (average age 36, range 26-45) and 13 females (average age 34, range 20-50) was used for the heart rate model development. External validation was done with the use of a clinical research database containing heart rate measurements derived from 67 healthy subjects, 34 males and 33 females (average age 33, range 17-72). The developed heart rate model was then incorporated into the ToxComp platform to simulate the impact of circadian variation in the heart rate on QTc interval. The usability of the combined models was assessed with moxifloxacin (MOXI) as a model drug.
Results:
The developed heart rate model fitted well, both to the training data set (RMSE = 128 ms and MAPE = 12.3%) and the validation data set (RMSE = 165 ms and MAPE = 17.1%). Simulations performed at the population level proved that the combination of the IVIVE platform and the population variability description allows for the precise prediction of the circadian variation of drugs proarrhythmic effect.
Conclusions:
It can be concluded that a flexible and practically useful model describing the heart rate circadian variation has been developed and its performance was verified.
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