Vladimir Piotrovsky
Advanced PK-PD Modeling and Simulation, Johnson & Johnson Pharmaceutical R&D, Beerse, Belgium
Non-cardiovascular drugs may exhibit effects on biomarkers known as vital signs, like heart rate (HR), blood pressure (BP), electrocadiogram (ECG), etc., that limits the drug dose and sometimes even results in the drug development failure. Particularly, the prolongation of the QT interval may cause a potentially fatal arrhythmia known as torsade de pointes. From the point of view of data analysis, vital signs have common properties: high inter- and intraindividual variability, diurnal rhythm, substantial gender differences. Moreover, at multiple administration, a tolerance to drug effects may develop resulting in a decrease in its magnitude.
Having this similarity in mind, the following operational model can be used for “simple” biomarkers (HR, BP, but not QT):
Y = BSL * (1 + DIURNAL + DRUG.EFF) + ERR
where BSL is the “true” baseline value of the variable Y; DIURNAL and DRUG.EFF are the diurnal variability and drug effect component of the model, respectively; ERR is the residual error. DIURNAL and DRUG.EFF are expressed in terms of changes relative to the baseline value. “True” baseline means it corresponds to zero values of DIURNAL and DRUF.EFF, and this does not necessarily coinsides with the predose level of Y. The drug concentration (in plasma or “effect-compartment”) enters DRUG.EFF in the form of Hill equation or other suitable PD model, which can also include a tolerance
In case of the QT interval, the above model should be updated with a term describing the intrinsic dependence of QT on RR interval:
QT = BSL * (CORR + DIURNAL + DRUG.EFF) + ERR
where a “correction” term CORR adapts QT according to changes in RR. The latter may change due to physical activity, diurnal rhythm, drug effects, and at random. Proper correction is a key issue in evaluating drug effects on QT interval. A conventional approach is based on an assumption of universal correction for all individuals. This contradicts, however, to recent findings [1].
The model is suggested, which uncludes the power correction formula with the exponent parameter subject to interindividual variability. This is implemented via mixed effects. DIURNAL and DRUF.EFF are implemented using bi-cosine and Hill function, respectively. Examples of drugs exhibiting significant QT prolongation and those having negligible/limited effect are given.
References
[1] Malik M., Camm AJ. Drug Safety 2001, 24:323-351.
Reference: PAGE 12 () Abstr 427 [www.page-meeting.org/?abstract=427]
Poster: poster