Quantitative pharmacokinetic-pharmacodynamic modelling of baclofen-mediated cardiovascular effects using BP and heart rate in rats

Abstract

Background and purpose: While the molecular pathways of baclofen toxicity are understood, the relationships between baclofen-mediated perturbation of individual target organs and systems involved in cardiovascular regulation are not clear. Our aim was to use an integrative approach to measure multiple cardiovascular-relevant parameters [CV: mean arterial pressure (MAP), systolic BP, diastolic BP, pulse pressure, heart rate (HR); CNS: EEG; renal: chemistries and biomarkers of injury] in tandem with the pharmacokinetic properties of baclofen to better elucidate the site(s) of baclofen activity.

Experimental approach: Han-Wistar rats were administered vehicle or ascending doses of baclofen (3, 10 and 30 mg·kg(-1) , p.o.) at 4 h intervals and baclofen-mediated changes in parameters recorded. A pharmacokinetic-pharmacodynamic model was then built by implementing an existing mathematical model of BP in rats.

Key results: Final model fits resulted in reasonable parameter estimates and showed that the drug acts on multiple homeostatic processes. In addition, the models testing a single effect on HR, total peripheral resistance or stroke volume alone did not describe the data. A final population model was constructed describing the magnitude and direction of the changes in MAP and HR.

Conclusions and implications: The systems pharmacology model developed fits baclofen-mediated changes in MAP and HR well. The findings correlate with known mechanisms of baclofen pharmacology and suggest that similar models using limited parameter sets may be useful to predict the cardiovascular effects of other pharmacologically active substances.

Figure 1

Linear plasma concentration‐time plots following three ascending doses of baclofen. Panels show: (A) measured levels of baclofen in rat plasma following administration of 3, 10 and 30 mg·kg⁻¹, p.o.; (B) best fit for plasma concentrations following administration of 3, 10 and 30 mg·kg⁻¹, p.o. baclofen.

Figure 2

BPs, heart rate, QA interval and CBT measured continuously for 24 h using radiotelemetry in conscious rats. Rats were treated with vehicle or baclofen at 3, 10 and 30 mg·kg⁻¹, p.o. in an ascending dose paradigm. Dashed line indicates time of compound administration at 0, 4 and 8 h. Panels show effects of vehicle, baclofen, p.o. on: (A) systolic BP; (B) diastolic BP; (C) mean arterial BP (MAP) (D) pulse pressure; (E) heart rate; (F) core body temperature. Data points correspond to means ± SEM. Significant changes in responses are denoted by * P < 0.05, baclofen from vehicle.

Figure 3

EEG measured continuously for 24 h using radiotelemetry in conscious rats. Rats were treated with vehicle and baclofen at 3, 10 and 30 mg·kg⁻¹. Dashed line indicates time of compound administration. Panels show effects of vehicle and baclofen administration on: (A) EEG δ; (B) EEG θ; (C) EEG α; (D) EEG β; € EEG γ. Data points correspond to means ± SEM. Significant changes in responses are denoted by *P < 0.05.

Figure 4

Schematic of different PKPD models used to fit the baclofen‐mediated cardiovascular response. Haemodynamic model utilized in analysis of the data. Model 1 assumes baclofen acts on TPR alone. Model 2 assumes site of action is HR alone. Model 3 assumes drug effect on SV alone. Model 4 allows for drug effect on all endpoints simultaneously. An effect compartment is included to account for differences from plasma exposure at each of the endpoints individually.

Figure 5

Best fits of the CV population models to HR and MAP observations. Panels (A–B) show HR and MAP best fits resulting from a fit to TPR alone. Panels (C–D) show HR and MAP fits for baclofen effect on HR alone. Panels (E–F) show HR and MAP from drug effect on SV alone. Panels (G–H) show HR and MAP resulting from simultaneous effect on HR, SV and TPR.

Figure 6

Individual predictions versus the observations of HR and MAP for best fit of Model 4. Each point represents the model prediction for that individual compared against the actual observed data that was measured at that time point.