PAGE 2013; Glasgow Towards the prediction of cardiovascular effects in human Nelleke Snelder , Bart Ploeger, Olivier Luttringer, Dean Rigel, Fumin Fu, Michael Beil, Donald Stanski and Meindert Danhof n.snelder@lapp.nl 1
fingolimod • Fingolimod is effective in the treatment of multiple sclerosis • In 2010 fingolimod was approved at a dose of 0.5 mg Freedoms trial: patients with MS Event fingolimod 0.5 mg placebo (N=425) (N=418) • A dose of 0.5 mg resulted in: Hypertension 26 (6.1 %) 16 (3.8 %) • A small increase in blood pressure Bradycardia 9 (2.1 %) 3 (0.7 %) • 1-2 mm Hg after 2 months • A transient bradycardia • 8 bpm at 5 hours after the 1st dose (attenuation after 6 hours) • Are cardiovascular effects of relevance for fingolimod? • Is the effect reversible? • What are the long term effects? • Can early selection of follow-up compounds be improved? Introduction 2
Effect of fingolimod on the CVS Vasocontriction/dilation Angiogenesis • Sphingosine-1-phosphate (S1P) is a major regulator of vascular Airway resistance S1P3 / S1P1 S1P1? and immune systems Barrier function Vascular Endothelium S1P1/ Bronchial smooth S1P3 muscle S1P3 (S1P1, S1P2?) S1P S1P S1P3 (S1P1, S1P3 (S1P1 in S1P2?) humans?) • Fingolimod is a S1P agonist Atrial myocytes Vascular smooth • Subtypes S1P1, S1P3, muscle S1P4 and S1P5 Heart-rate Vascular tone AV Conduction • The mechanism of action needs further investigation Introduction 3
Hypothesis: a better understanding of the mechanism of action of compounds can result from a quantitative understanding of the system • Physiological principles of BP regulation Mean Arterial Total Peripheral Cardiac Output = x Pressure (MAP) Resistance (TPR) (CO) = x Cardiac Output (CO) Heart Rate (HR) Stroke Volume (SV) • Several feedback mechanism: • Baroreflex system • Renin-Angiotensin-Aldosterone System • Preclinical research may contribute to a quantitative understanding of the cardiovascular system (CVS) Introduction 4
Objectives 1) Development of a systems pharmacology model characterizing the effects of drugs on the interrelationship between BP, TPR, CO, HR and SV ⇒ Drug-independent CVS model 2) Characterization of the effect of fingolimod on the CVS using the developed systems pharmacology model ⇒ A better understanding of mechanisms leading to cardiovascular effects following administration of fingolimod Objectives 5
CVS model PAGE 2013 Glasgow 6
Collect preclinical data from different drugs acting on CVS to identify system specific parameters Compounds: • Effect on HR Effect on TPR Effect on SV atropine (M2 receptor antagonist) amlodipine (calcium channel blocker) amiloride (diuretic) propanolol (non-selective β blocker) enalapril (ACE-inhibitor) enalapril (ACE-inhibitor) fasudil (rho-kinase inhibitor) HCTZ (diuretic) prazosin (selective α 1 blocker) 2-3 rats per compound Electical swivel Study design: • Baseline Baseline Baseline measurements measurements measurements A different dose each day A different dose each day A different dose each day Washout Washout Washout arterial Ascending radiotransmitter aortic flow probe Day 1 Day 1 Day 1 Days 6-7 Days 6-7 Days 6-7 Day 2-5 Day 2-5 Day 2-5 BP, CO and HR are measured BP, CO and TPR measured BP, CO and TPR measured BP, CO and TPR measured CVS model 7
System-specific Model = • Linked turnover model with SV SV * (1 - HR_SV * LN(HR/BSL_ HR)) T HR differential equations for HR, = ⋅ CO HR SV K in_HR k out_HR SV and TPR linked by negative = ⋅ MAP CO TPR feedback through MAP - FB • Direct inverse relationship MA M AP P between HR and SV - - FB FB SV T • Circadian rhythm: two cosine TP PR R T K in_TPR functions, one influencing HR K in_SV k out_SV k out_TPR and one influencing TPR • Handling effect: exponentially decreasing functions influencing K in_HR and K in_TPR • Differences between hypertensive and normotensive rats: • Different baseline • The feedback was found to be dependent on the baseline blood pressure CVS model 8
TPR SV CO HR M AP m m HG /(m L/m in) m L/beat m L/m in beats/m in m m HG 2.3 2.5 2.7 0.22 0.26 0.30 4 0 40 50 60 70 150 250 120 140 0 Negative effect on HR 12 T im e (h ) 24 36 9
TPR SV CO HR M AP m m HG /(m L/m in) m L/beat m L/m in beats/m in m m HG 1.2 1.8 0.22 0.24 70 80 90 320 360 400 100 130 0 Negative effect on TPR 12 T im e (h ) 24 36 10
Drug-specific Model EFF_HR = SV SV * (1 - HR_SV * LN(HR/BSL_ HR)) T C HR = ⋅ CO HR SV • PKPD modelling approach (NONMEM): K in_HR k out_HR = ⋅ MAP CO TPR PK models from literature - FB MA M AP P - - FB FB • Drug effects on HR, SV or TPR SV T C T TP PR R K in_SV k out_SV K in_TPR k out_TPR EFF_TPR EFF_SV • Best drug effect models: Compound Effect site Drug effect model E max with E max fixed to 1 amiloride SV amlodipine TPR E max with E max fixed to 1 atropine HR Linear E max with E max fixed to 1 enalapril TPR and SV E max with E max fixed to 1 fasudil TPR HCTZ SV E max with E max fixed to 1 prazosin TPR Power propranolol HR No effect • The effect of ACE inhibitors is delayed. This was described by an effect compartment model CVS model 11
Adequate description of the effect of amlodipine hypertensive rats Veh icle 0.3 m g/kg 1 m g/kg 3 m g/kg 10 m g/kg 180 HG Effect on all five endpoints AP 140 m M can be described by a single m 100 drug effect on TPR in 400 Derived Measured beats/m HR 250 in 90 L/m CO 50 70 m 0.30 L/beat SV 0.20 m in) 3.0 L/m TPR /(m Individual prediction 2.0 HG Population prediction (n=38) m 1.0 m • Observations (colored per rat) 0 12 24 36 48 60 72 84 96 108 132 156 T im e (h ) CVS model 12
Adequate description of the effect of amlodipine normotensive rats Veh icle 0.3 m g/kg 1 m g/kg 3 m g/kg 10 m g/kg 100 HG AP m M m Effect of amlodipine 80 described adequately in normotensive rats Derived Measured in 400 beats/m HR 250 in 160 CO L/m m 120 0.45 L/beat SV 0.35 m 1.0 in) L/m TPR /(m 0.7 Individual prediction HG m Population prediction (n=38) 0.4 m 0 12 24 36 48 60 72 84 96 108 132 156 • Observations (colored per rat) T im e (h ) CVS model 13
Conclusions and Future perspective CVS model • A systems pharmacology model was developed to describe the interrelationship between MAP, CO, HR, SV and TPR • The developed systems pharmacology model can be used to quantify cardiovascular drug effects of novel compounds • Can the CVS model be used to elucidate the mechanism of action of novel compounds? CVS model 14
Application of the developed drug- independent CVS model to fingolimod PAGE 2013 Glasgow 15
Prediction of the effect of fingolimod on the CVS Experimental design: MAP 160 • Dose: 0, 0.1, 0.3, 1, 3 and 10 mg/kg 150 • MD administration (4 weeks) mmHg 140 • Hypertensive and normotensive rats 130 • 32 rats Measured: MAP, HR and CO 120 • 0 400 800 1200 Time (h) TPR TPR HR 1.8 mmHG/(mL/min) 360 1.6 beats/min 340 1.4 320 1.2 300 1.0 280 0 400 800 1200 0 400 800 1200 Time (h) Time (h) CO SV SV 0.50 120 0.45 110 mL/beat mL/min 0.40 100 0.35 90 0.30 80 0.25 0 400 800 1200 0 400 800 1200 Time (h) Time (h) Example of a typical hyeprtensive rat (10 mg/kg) Effect of fingolimod on the CVS 16
Prediction of the effect of fingolimod on the CVS Hypothesis 1: effect is on HR • The CVS model was used to predict the effect of fingolimod MAP MAP 160 160 • System-specific parameters were fixed 150 150 mmHg mmHg 140 140 130 130 120 120 0 400 800 1200 0 400 800 1200 Time (h) Time (h) TPR TPR TPR TPR HR HR EFF_HR 1.8 1.8 450 mmHG/(mL/min) mmHG/(mL/min) 360 1.6 beats/min beats/min 1.5 400 340 = SV SV * (1 - HR_SV * LN(HR/BSL_ HR)) T HR C = ⋅ 1.4 CO HR SV 320 350 K in_HR k out_HR = ⋅ 1.2 MAP CO TPR 1.2 300 300 - 0.9 1.0 280 FB 0 0 400 400 800 800 1200 1200 0 0 400 400 800 800 1200 1200 MA AP P Time (h) Time (h) Time (h) Time (h) M - - FB FB CO CO SV SV SV SV 0.50 0.50 140 120 0.45 0.45 125 110 mL/beat mL/beat mL/min mL/min SV T TP PR R C T 0.40 0.40 K in_SV k out_SV K in_TPR k out_TPR 110 100 0.35 0.35 95 90 0.30 0.30 80 0.25 80 0.25 0 0 400 400 800 800 1200 1200 0 0 400 400 800 800 1200 1200 Time (h) Time (h) Time (h) Time (h) The CVS model indicates that it is not likely that the primary effect of fingolimod is on HR Effect of fingolimod on the CVS 17
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