Mechanism-based PKPD modeling of cardiovascular effects in conscious rats - an application to fingolimod
N. Snelder (1,2), B.A. Ploeger (1), O. Luttringer (3), D.F. Rigel (4), F. Fu (4), M. Beil (4), D.R. Stanski (3) and M. Danhof (1,2)
(1) Division of Pharmacology, Leiden Academic Centre for Drug Research, Leiden, The Netherlands; (2) LAP&P Consultants BV, Leiden, The Netherlands; (3) Modeling and simulation department, Novartis, Basel, Switzerland; (4) Cardiovascular and Metabolism Research, Novartis Institutes for BioMedical Research, Novartis Pharmaceuticals Corporation, East Hanover, New Jersey, USA
Objectives
Fingolimod (FTY720; Gilenya (trade name)) is a sphingosine 1-phosphate (S1P) receptor modulator, which is effective in the treatment of multiple sclerosis[1]. In 2010 fingolimod was approved for treatment of patients with relapsing forms of multiple sclerosis at a dose of 0.5 mg. However, early in clinical development a dose-dependent mild increase in blood pressure of 5-6 mmHG was observed at the supra-therapeutic doses of 1.25 and 5 mg. The mechanism of action (MoA) underlying this effect was not fully understood. In general, cardiovascular safety issues in drug development occur often. In this context, an adequate understanding of the cadiovascular system (CVS) which regulates blood pressure in both preclinical species and human is pivotal to efficiently anticipate clinical effects of drugs on blood pressure and ultimately improve translational drug research. The development of such a translational pharmacodynamic (PD) model requires a mechanistic understanding of blood pressure regulation. The physiological principles of the CVS including BP regulation are well characterized and the homeostatic principles of the CVS are thoroughly understood. Briefly, mean arterial pressure (MAP) equals the product of cardiac output (CO) and total peripheral resistance (TPR) and CO equals the product of heart rate (HR) and stroke volume (SV). However, drug effects on this interrelationship have not been analyzed in a mechanism-based and quantitative manner. This investigation aimed 1) to describe, in a mechanism-based and quantitative manner, the effects of drugs with different MoA on the interrelationship between BP, TPR, CO, HR and SV and 2) to describe the effect of fingolimod on the CVS and to get a better understanding of mechanisms leading to blood pressure changes following administration of fingolimod using the developed drug-independent model.
Methods
The cardiovascular effects of 8 drugs with diverse MoA's, (amlodipine, fasudil, enalapril, propranolol, hydrochlorothiazide, prazosin, amiloride and atropine) following a single administration of a range of different doses were characterized in spontaneously hypertensive (SHR) and normotensive (WKY) rats. In addition, the effect of fingolimod following multiple administrations (maximal 4 weeks) of doses of 0, 0.1, 0.3, 1, 3 and 10 mg/kg were characterized in SHR and WKY rats. The rats were chronically instrumented with ascending aortic flow probes and/or aortic catheters/radiotransmitters for continuous recording of BP, HR and SV. Data were analyzed in conjunction with independent information on the time course of drug concentration using a mechanism-based PKPD modeling approach. The interrelationship between MAP, TPR, CO, HR and SV is expressed by the formulas 1) MAP=CO*TPR and 2) CO=HR*SV. Previously, we have developed a mechanism-based linked turnover model to describe the inter-relationship between MAP, CO and TPR[2]. This model consisted of two differential equations, one for CO and one for TPR, which were linked by negative feedback through MAP. Following a top-down modeling approach this model was extended in two ways. I) HR and SV were included in the model. The extended model consisted of three linked turnover equations involving the basic parameters of the CVS, TPR, HR and SV all linked by negative feedback through MAP. II) the circadian rhythm, which was observed in all 5 parameters of the CVS, was described by two cosine functions, one influencing HR and one influencing TPR. Linear, log-linear, power, Emax and Sigmoid Emax models were evaluated to describe the drug effects on TPR, HR or SV. Subsequently, the developed drug-independent model was applied to identify the site of action of fingolimod and to describe the effect of fingolimod on the 5 parameters of the CVS. To this extend the system-parameters were fixed and only drug-specific parameters were estimated.
Results
By simultaneous analysis of the effects of 8 different compounds with diverse MoA's, the dynamics of the interrelationship between BP, TPR, CO, HR and SV were quantified. System-specific parameters could be distinguished from drug-specific parameters (all correlations < 0.95) indicating that the developed model is drug-independent. Model based hypothesis testing on the basis of the developed mechanism-based CVS model revealed that the increase in BP in rats, which was observed after treatment with fingolimod, is mediated by a primary effect of fingolimod on TPR. The effect of fingolimod on TPR was described by a combination of a fast (effect on the production rate of TPR (Kin_TPR) and slow effect on TPR (disease modifying effect on the dissipation rate of TPR (kout_TPR). Both effects were found to be proportional to the baseline and the slow effect resulted in a permanent increase in BP as compared to the baseline at start of treatment. The slow effect was dependent on disease state (baseline TPR). This explains why the slow effect does not occur in WKY rats, which have a lower baseline TPR. Through the feedback-mechansims the drug effect on TPR results in an increase in MAP and TPR and a decrease in CO, HR and SV.
Conclusions
A system-specific model characterizing the interrelationship between BP, TPR, CO, HR and SV in rats has been obtained, which was used to quantify and predict cardiovascular drug effects and to elucidate the MoA for the effect of fingolimod. Ultimately, the proposed PKPD model may allow prediction of BP effects in humans based on preclinical evaluations of drug effect. It should be noted that the identified set of system parameters is specific for SHR and WKY rats. Consequently, applications of the developed model, using the identified set of system parameters, are limited to SHR and WKY rats. However, an advantage of a mechanism-based model is that it allows accurate extrapolation between different rat strains and from one species to another[3,4] as the structure of the model is expected to be the same in all species. Therefore, future research will include the application of the developed drug-independent model to predict the clinical response based on preclinical data for fingolimod and other compounds. To this end the developed drug-independent model will be scaled to human and validated on human MAP and CO measurements.
References
[1] Cohen JA, Barkhof F, Comi G, Hartung HP, Khatri BO, Montalban X (2010). Oral fingolimod or intramuscular interferon for relapsing multiple sclerosis. N Engl J Med. 362(5): 402-15.
[2] Snelder N, Ploeger BA, Luttringer O, Rigel DF, Webb RL, Feldman D, Fu F, Beil M, Jin L, Stanski DR and Danhof M. PKPD modeling of the interrelationship between mean arterial blood pressure, cardiac output and total peripheral resistance in conscious rats (Submitted for publication)
[3] Danhof M, de Lange EC, Della Pasqua OE, Ploeger BA, Voskuyl RA (2008). "Mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) modeling in translational drug research." Trends Pharmacol Sci. 29(4): 186-191.
[4] Ploeger BA, van der Graaf PH, Danhof M (2009). "Incorporating receptor theory in mechanism-based pharmacokinetic-pharmacodynamic (PK-PD) modeling." Drug Metab Pharmacokinet. 24(1): 3-15.
