BACKGROUND AND PURPOSEPreviously, a systems pharmacology model was developed characterizing drug effects on the interrelationship between mean arterial pressure (MAP), cardiac output (CO) and total peripheral resistance (TPR). The present investigation aims to (i) extend the previously developed model by parsing CO into heart rate (HR) and stroke volume (SV) and (ii) evaluate if the mechanism of action (MoA) of new compounds can be elucidated using only HR and MAP measurements. EXPERIMENTAL APPROACHCardiovascular effects of eight drugs with diverse MoAs (amiloride, amlodipine, atropine, enalapril, fasudil, hydrochlorothiazide, prazosin and propranolol) were characterized in spontaneously hypertensive rats (SHR) and normotensive Wistar-Kyoto (WKY) rats following single administrations of a range of doses. Rats were instrumented with ascending aortic flow probes and aortic catheters/radiotransmitters for continuous recording of MAP, HR and CO throughout the experiments. Data were analysed in conjunction with independent information on the time course of the drug concentration following a mechanism-based pharmacokinetic-pharmacodynamic modelling approach. KEY RESULTSThe extended model, which quantified changes in TPR, HR and SV with negative feedback through MAP, adequately described the cardiovascular effects of the drugs while accounting for circadian variations and handling effects. CONCLUSIONS AND IMPLICATIONSA systems pharmacology model characterizing the interrelationship between MAP, CO, HR, SV and TPR was obtained in hypertensive and normotensive rats. This extended model can quantify dynamic changes in the CVS and elucidate the MoA for novel compounds, with one site of action, using only HR and MAP measurements. Whether the model can be applied for compounds with a more complex MoA remains to be established. Abbreviations amp, amplitude; BSL_CO, baseline value of cardiac output; BSL_HR, baseline value of heart rate; BSL_MAP, baseline value of mean arterial pressure; BSL_SV, baseline value of stroke volume; BSL_TPR, baseline value of total peripheral resistance; C, drug concentration in plasma; CO, cardiac output; Emax, maximum effect; FB, negative feedback of mean arterial pressure; FB0, feedback of a typical subject; FB0_MAP, exponent of the power relationship between FB and the individual BSL_MAP; HCTZ, hydrochlorothiazide; hor, horizontal displacement; HR, heart rate; Kin_HR, zero-order production rate constant of HR; Kin_SV, zero-order production rate constant of stroke volume; Kin_TPR, zero-order production rate constant of total peripheral resistance; kout_HR, first-order dissipation rate constant of HR; kout_SV, first-order dissipation rate constant of stroke volume; kout_TPR, first-order dissipation rate constant of total peripheral resistance; LVFT, left ventricular filling time; MAP, mean arterial pressure; MoA, mechanisms of action; MVOF, minimum value of the objective function;

BACKGROUND AND PURPOSEThe homeostatic control of arterial BP is well understood with changes in BP resulting from changes in cardiac output (CO) and/or total peripheral resistance (TPR). A mechanism-based and quantitative analysis of drug effects on this interrelationship could provide a basis for the prediction of drug effects on BP. Hence, we aimed to develop a mechanism-based pharmacokinetic-pharmacodynamic (PKPD) model in rats that could be used to characterize the effects of cardiovascular drugs with different mechanisms of action (MoA) on the interrelationship between BP, CO and TPR. EXPERIMENTAL APPROACHThe cardiovascular effects of six drugs with diverse MoA, (amlodipine, fasudil, enalapril, propranolol, hydrochlorothiazide and prazosin) were characterized in spontaneously hypertensive rats. The rats were chronically instrumented with ascending aortic flow probes and/or aortic catheters/radiotransmitters for continuous recording of CO and/or BP. Data were analysed in conjunction with independent information on the time course of drug concentration using a mechanism-based PKPD modelling approach. KEY RESULTSBy simultaneous analysis of the effects of six different compounds, the dynamics of the interrelationship between BP, CO and TPR were quantified. System-specific parameters could be distinguished from drug-specific parameters indicating that the model developed is drug-independent. CONCLUSIONS AND IMPLICATIONSA system-specific model characterizing the interrelationship between BP, CO and TPR was obtained, which can be used to quantify and predict the cardiovascular effects of a drug and to elucidate the MoA for novel compounds. Ultimately, the proposed PKPD model could be used to predict the effects of a particular drug on BP in humans based on preclinical data. AbbreviationsAmp, amplitude; BSL_CO, baseline value of cardiac output; BSL_MAP, baseline value of MAP; BSL_TPR, baseline value of total peripheral resistance; C, drug concentration in plasma; CO, cardiac output; Emax, maximum effect; FB1, negative feedback of mean arterial pressure on cardiac output; FB2, negative feedback of mean arterial pressure on total peripheral resistance; HCTZ, hydrochlorothiazide; HOR, horizontal displacement; IIV, inter-individual variability; Kin_CO, zero-order production rate constant of cardiac output; Kin_TPR, zero-order production rate constant of total peripheral resistance; kout_CO, first-order dissipation rate constant of cardiac output; kout_TPR, first-order dissipation rate constant of total peripheral resistance; MAP, mean arterial pressure; MC, methylcellulose; MoA, mechanisms of action; MVOF, minimum value of the objective function;

Background Finerenone is a nonsteroidal selective mineralocorticoid receptor antagonist that recently demonstrated efficacy in delaying chronic kidney disease progression and reducing cardiovascular events in patients with chronic kidney disease and type 2 diabetes in FIDELIO-DKD, where 5734 patients were randomized 1:1 to receive either titrated finerenone doses of 10 or 20 mg once daily or placebo, with a median follow-up of 2.6 years. Methods Nonlinear mixed-effects population pharmacokinetic models were used to analyze the pharmacokinetics in FIDELIO-DKD, sparsely sampled in all subjects receiving finerenone. Post-hoc model parameter estimates together with dosing histories allowed the computation of individual exposures used in subsequent parametric time-to-event analyses of the primary kidney outcome. Results The population pharmacokinetic model adequately captured the typical pharmacokinetics of finerenone and its variability. Either covariate effects or multivariate forward-simulations in subgroups of interest were contained within the equivalence range of 80–125% around typical exposure. The exposure-response relationship was characterized by a maximum effect model estimating a low half-maximal effect concentration at 0.166 µg/L and a maximal hazard decrease at 36.1%. Prognostic factors for the treatment-independent chronic kidney disease progression risk included a low estimated glomerular filtration rate and a high urine-to-creatinine ratio increasing the risk, while concomitant sodium-glucose transport protein 2 inhibitor use decreased the risk. Importantly, no sodium-glucose transport protein 2 inhibitor co-medication-related modification of the finerenone treatment effect per se could be identified. Conclusions None of the tested pharmacokinetic covariates had clinical relevance in FIDELIO-DKD. Finerenone effects on kidney outcomes approached saturation towards 20 mg once daily and sodium-glucose transport protein 2 inhibitor use provided additive benefits. Supplementary Information The online version contains supplementary material available at 10.1007/s40262-021-01082-2.

IONIS-FXI RX (BAY2306001) is an antisense oligonucleotide that inhibits the synthesis of coagulation factor XI and has been investigated in healthy volunteers and end-stage renal disease (ESRD) patients. FXI-LICA (BAY2976217) shares the same RNA sequence as IONIS-FXI RX but contains a GalNAc-conjugation that facilitates asialoglycoprotein receptor (ASGPR)-mediated uptake into hepatocytes. FXI-LICA has been studied in healthy volunteers and is currently investigated in ESRD patients on hemodialysis.We present a model-informed bridging approach that facilitates the extrapolation of the dose-exposure-FXI relationship from IONIS-FXI RX to FXI-LICA in ESRD patients and, thus, supports the selection of FX-LICA doses being investigated in ESRD patients. A two-compartment PK model, with mixed first-and zero-order subcutaneous absorption and first-order elimination, was combined with an indirect response model for the inhibitory effect on the FXI synthesis rate via an effect compartment. This PK/PD model adequately described the median trends, as well as the inter-individual variabilities for plasma drug concentration and FXI activity in healthy volunteers of IONIS-FXI RX and FXI-LICA, and in ESRD patients of IONIS-FXI RX . The Accepted ArticleThis article is protected by copyright. All rights reserved model was then used to predict dose dependent steady-state FXI activity following repeat once-monthly doses of FXI-LICA in a virtual ESRD patient population.Under the assumption of similar ASGPR expression in ESRD patients and healthy volunteers, doses of 40mg, 80mg, and 120mg FXI-LICA are expected to cover the target range of clinical interest for steadystate FXI activity in the Phase 2b study of FXI-LICA in ESRD patients undergoing hemodialysis.

Background Finerenone (BAY 94-8862) is a potent non-steroidal, selective mineralocorticoid receptor antagonist being developed for the treatment of patients with type 2 diabetes and chronic kidney disease. Methods We present the population pharmacokinetics and pharmacodynamics (PD) analysis for efficacy and safety markers based on data from two clinical phase IIb studies: ARTS-DN (NCT01874431) and ARTS-DN Japan (NCT01968668). Results The pharmacokinetics of finerenone were adequately characterized, with estimated glomerular filtration rate (eGFR) and body weight as influencing covariates. The area under the plasma concentration-time curve in Japanese patients did not differ from that in the global population, and the investigated pharmacokinetics were dose-and time-linear. In addition, the pharmacokinetic model provided robust individual exposure estimates to study exposure-response. The concentration-effect relationship over time for the efficacy marker urinary albumin:creatinine ratio (UACR) was well-characterized by a maximum effect model indicating saturation at high exposures. For the safety markers, a log-linear model and a power model were identified for serum potassium concentration and eGFR, respectively, indicating attenuation of effect gains at high exposures. There was no apparent ethnic effect on the investigated pharmacokinetic-pharmacodynamic relationships. The model-predicted times to reach the full (99%) steady-state drug effect on UACR, serum potassium, and eGFR were 138, 20, and 85 days, respectively, while the pharmacokinetic half-life was 2-3 h and steady state was achieved after 2 days, indicating timescale separation. Conclusion Our dose-exposure-response modeling and simulation indicates effects were largely saturated at finerenone 20 mg and doses of both 10 and 20 mg once daily appear safe and efficacious at reducing albuminuria.