Quantification of the effect of GLP-1R agonists on body weight using in vitro efficacy information: An extension of the Hall body composition model.

Obesity has become a major public health concern worldwide. Pharmacological interventions with the glucagon-like peptide-1 receptor agonists (GLP-1RAs) have shown promising results in facilitating weight loss and improving metabolic outcomes in individuals with obesity. Quantifying drug effects of GLP-1RAs on energy intake (EI) and body weight (BW) using a QSP modeling approach can further increase the mechanistic understanding of these effects, and support obesity drug development. An extensive literature-based dataset was created, including data from several diet, liraglutide and semaglutide studies and their effects on BW and related parameters. The Hall body composition model was used to quantify and predict effects on EI. The model was extended with (1) a lifestyle change/placebo effect on EI, (2) a weight loss effect on activity for the studies that included weight management support, and (3) a GLP-1R agonistic effect using in vitro potency efficacy information. The estimated reduction in EI of clinically relevant dosages of semaglutide (2.4 mg) and liraglutide (3.0 mg) was 34.5% and 13.0%, respectively. The model adequately described the resulting change in BW over time. At 20 weeks the change in BW was estimated to be -17% for 2.4 mg semaglutide and -8% for 3 mg liraglutide, respectively. External validation showed the model was able to predict the effect of semaglutide on BW in the STEP 1 study. The GLP-1RA body composition model can be used to quantify and predict the effect of novel GLP-1R agonists on BW and changes in underlying processes using early in vitro efficacy information.

Navigating the landscape of parameter identifiability methods: A workflow recommendation for model development.

In pharmacometric modeling, it is often important to know whether the data is sufficiently rich to identify the parameters of a proposed model. While it may be possible to assess this based on the results of a model fit, it is often difficult to disentangle identifiability issues from other model fitting and numerical problems. Furthermore, it can be of value to ascertain identifiability beforehand. This paper compares four methods for parameter identifiability, namely Differential Algebra for Identifiability of SYstems (DAISY), the sensitivity matrix method (SMM), Aliasing, and the Fisher information matrix method (FIMM). We discuss the characteristics of the methods and apply them to a set of applications, consisting of frequently used PK model structures, with suitable dosing regimens and sampling times. These applications were selected to validate the methods and demonstrate their usefulness. While traditional identifiability analysis provides a categorical result [PLoS One, 6, 2011, e27755; CPT Pharmacometrics Syst Pharmacol, 8, 2019, 259; Bioinformatics, 30, 2014, 1440], we argue that in practice a continuous scale better reflects the limitations on the data and is more informative. The methods were generally consistent in their evaluation of the applications. The Fisher information matrix method seemed to provide the most consistent answers. All methods provided information on the parameters that were unidentifiable. Some of the results were unexpected, indicating identifiability issues where none were foreseen, but could be explained upon further analysis. This illustrated the usefulness of identifiability assessment.

Characterisation of cotadutide's dual GLP-1/glucagon receptor agonistic effects on glycaemic control using an in vivo human glucose regulation quantitative systems pharmacology model.

BACKGROUND AND PURPOSE: Cotadutide is a dual GLP-1 and glucagon receptor agonist with balanced agonistic activity at each receptor designed to harness the advantages on promoting liver health, weight loss and glycaemic control. We characterised the effects of cotadutide on glucose, insulin, GLP-1, GIP, and glucagon over time in a quantitative manner using our glucose dynamics systems model (4GI systems model), in combination with clinical data from a multiple ascending dose/Phase 2a (MAD/Ph2a) study in overweight and obese subjects with a history of Type 2 diabetes mellitus (NCT02548585). EXPERIMENTAL APPROACH: The cotadutide PK-4GI systems model was calibrated to clinical data by re-estimating only food related parameters. In vivo cotadutide efficacy was scaled based on in vitro potency. The model was used to explore the effect of weight loss on insulin sensitivity and predict the relative contribution of the GLP-1 and glucagon receptor agonistic effects on glucose. KEY RESULTS: Cotadutide MAD/Ph2a clinical endpoints were successfully predicted. The 4GI model captured a positive effect of weight loss on insulin sensitivity and showed that the stimulating effect of glucagon on glucose production counteracts the GLP-1 receptor-mediated decrease in glucose, resulting in a plateau for glucose decrease around a 200-µg cotadutide dose. CONCLUSION AND IMPLICATIONS: The 4GI quantitative systems pharmacology model was able to predict the clinical effects of cotadutide on glucose, insulin, GLP-1, glucagon and GIP given known in vitro potency. The analyses demonstrated that the quantitative systems pharmacology model, and its successive refinements, will be a valuable tool to support the clinical development of cotadutide and related compounds.

Pharmacokinetics and pharmacodynamics of finerenone in patients with chronic kidney disease and type 2 diabetes: Insights based on FIGARO-DKD and FIDELIO-DKD.

AIMS: To perform dose-exposure-response analyses to determine the effects of finerenone doses. MATERIALS AND METHODS: Two randomized, double-blind, placebo-controlled phase 3 trials enrolling 13 026 randomized participants with type 2 diabetes (T2D) from global sites, each with an estimated glomerular filtration rate (eGFR) of 25 to 90 mL/min/1.73 m2 , a urine albumin-creatinine ratio (UACR) of 30 to 5000 mg/g, and serum potassium ≤ 4.8 mmol/L were included. Interventions were titrated doses of finerenone 10 or 20 mg versus placebo on top of standard of care. The outcomes were trajectories of plasma finerenone and serum potassium concentrations, UACR, eGFR and kidney composite outcomes, assessed using nonlinear mixed-effects population pharmacokinetic (PK)/pharmacodynamic (PD) and parametric time-to-event models. RESULTS: For potassium, lower serum levels and lower rates of hyperkalaemia were associated with higher doses of finerenone 20 mg compared to 10 mg (p < 0.001). The PK/PD model analysis linked this observed inverse association to potassium-guided dose titration. Simulations of a hypothetical trial with constant finerenone doses revealed a shallow but increasing exposure-potassium response relationship. Similarly, increasing finerenone exposures led to less than dose-proportional increasing reductions in modelled UACR. Modelled UACR explained 95% of finerenone's treatment effect in slowing chronic eGFR decline. No UACR-independent finerenone effects were identified. Neither sodium-glucose cotransporter-2 (SGLT2) inhibitor nor glucagon-like peptide-1 receptor agonist (GLP-1RA) treatment significantly modified the effects of finerenone in reducing UACR and eGFR decline. Modelled eGFR explained 87% of finerenone's treatment effect on kidney outcomes. No eGFR-independent effects were identified. CONCLUSIONS: The analyses provide strong evidence for the effectiveness of finerenone dose titration in controlling serum potassium elevations. UACR and eGFR are predictive of kidney outcomes during finerenone treatment. Finerenone's kidney efficacy is independent of concomitant use of SGLT2 inhibitors and GLP-1RAs.

Evaluation of a Cardiovascular Systems Model for Design and Analysis of Hemodynamic Safety Studies.

Early prediction, quantification and translation of cardiovascular hemodynamic drug effects is essential in pre-clinical drug development. In this study, a novel hemodynamic cardiovascular systems (CVS) model was developed to support these goals. The model consisted of distinct system- and drug-specific parameter, and uses data for heart rate (HR), cardiac output (CO), and mean atrial pressure (MAP) to infer drug mode-of-action (MoA). To support further application of this model in drug development, we conducted a systematic analysis of the estimation performance of the CVS model to infer drug- and system-specific parameters. Specifically, we focused on the impact on model estimation performance when considering differences in available readouts and the impact of study design choices. To this end, a practical identifiability analysis was performed, evaluating model estimation performance for different combinations of hemodynamic endpoints, drug effect sizes, and study design characteristics. The practical identifiability analysis showed that MoA of drug effect could be identified for different drug effect magnitudes and both system- and drug-specific parameters can be estimated precisely with minimal bias. Study designs which exclude measurement of CO or use a reduced measurement duration still allow the identification and quantification of MoA with acceptable performance. In conclusion, the CVS model can be used to support the design and inference of MoA in pre-clinical CVS experiments, with a future potential for applying the uniquely identifiable systems parameters to support inter-species scaling.

Dose-Exposure-Response Analysis of the Nonsteroidal Mineralocorticoid Receptor Antagonist Finerenone on UACR and eGFR: An Analysis from FIDELIO-DKD.

BACKGROUND AND OBJECTIVE: Finerenone reduces the risk of kidney failure in patients with chronic kidney disease and type 2 diabetes. Changes in the urine albumin-to-creatinine ratio (UACR) and estimated glomerular filtration rate (eGFR) are surrogates for kidney failure. We performed dose-exposure-response analyses to determine the effects of finerenone on these surrogates in the presence and absence of sodium glucose co-transporter-2 inhibitors (SGLT2is) using individual patient data from the FIDELIO-DKD study. METHODS: Non-linear mixed-effects population pharmacokinetic/pharmacodynamic models were used to quantify disease progression in terms of UACR and eGFR during standard of care and pharmacodynamic effects of finerenone in the presence and absence of SGLT2i use. RESULTS: The population pharmacokinetic/pharmacodynamic models adequately described effects of finerenone exposure in reducing UACR and slowing eGFR decline over time. The reduction in UACR achieved with finerenone during the first year predicted its subsequent effect in slowing progressive eGFR decline. SGLT2i use did not modify the effects of finerenone. The population pharmacokinetic/pharmacodynamic model demonstrated with 97.5% confidence that finerenone was at least 94.1% as efficacious in reducing UACR in patients using an SGLT2i compared with patients not using an SGLT2i based on the 95% confidence interval of the SGLT2i-finerenone interaction from 94.1 to 122%. The 95% confidence interval of the SGLT2i-finerenone interaction for the UACR-mediated effect on chronic eGFR decline was 9.5-144%. CONCLUSIONS: We developed a model that accurately describes the finerenone dose-exposure-response relationship for UACR and eGFR. The model demonstrated that the early UACR effect of finerenone predicted its long-term effect on eGFR decline. These effects were independent of concomitant SGLT2i use.

A novel cardiovascular systems model to quantify drugs effects on the inter-relationship between contractility and other hemodynamic variables.

The use of systems-based pharmacological modeling approaches to characterize mode-of-action and concentration-effect relationships for drugs on specific hemodynamic variables has been demonstrated. Here, we (i) expand a previously developed hemodynamic system model through integration of cardiac output (CO) with contractility (CTR) using pressure-volume loop theory, and (ii) evaluate the contribution of CO data for identification of system-specific parameters, using atenolol as proof-of-concept drug. Previously collected experimental data was used to develop the systems model, and included measurements for heart rate (HR), CO, mean arterial pressure (MAP), and CTR after administration of atenolol (0.3-30 mg/kg) from three in vivo telemetry studies in conscious Beagle dogs. The developed cardiovascular (CVS)-contractility systems model adequately described the effect of atenolol on HR, CO, dP/dtmax, and MAP dynamics and allowed identification of both system- and drug-specific parameters with good precision. Model parameters were structurally identifiable, and the true mode of action can be identified properly. Omission of CO data did not lead to a significant change in parameter estimates compared to a model that included CO data. The newly developed CVS-contractility systems model characterizes short-term drug effects on CTR, CO, and other hemodynamic variables in an integrated and quantitative manner. When the baseline value of total peripheral resistance is predefined, CO data was not required to identify drug- and system-specific parameters. Confirmation of the consistency of system-specific parameters via inclusion of data for additional drugs and species is warranted. Ultimately, the developed model has the potential to be of relevance to support translational CVS safety studies.

Finerenone Dose-Exposure-Response for the Primary Kidney Outcome in FIDELIO-DKD Phase III: Population Pharmacokinetic and Time-to-Event Analysis.

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.

A novel integrated QSP model of in vivo human glucose regulation to support the development of a glucagon/GLP-1 dual agonist.

Glucagon-like peptide-1 (GLP-1) receptor agonists (GLP-1RAs) and dual GLP-1/glucagon receptor agonists improve glycaemic control and cause significant weight loss in patients with type 2 diabetes.1 These effects are driven in part by augmenting glucose-stimulated insulin release (incretin effect), reducing caloric intake and delayed gastric emptying. We developed and externally validated a novel integrated quantitative systems pharmacology (QSP) model to gain quantitative insight into the relative contributions and mechanisms of drugs modulating glucose regulatory pathways. This model (4GI model) incorporates known feedback mechanisms among glucose, GLP-1, glucagon, glucose-dependent insulinotropic peptide (GIP), and insulin after glucose provocation (i.e., food intake) and drug intervention utilizing published nonpharmacological and pharmacological (liraglutide, a GLP-1RA) data. The resulting model accurately describes the aforementioned mechanisms and independently predicts the effects of the GLP-1RAs (dulaglutide and semaglutide) on system dynamics. Therefore, the validated 4GI model represents a quantitative decision-making tool to support the advancement of novel therapeutics and combination strategies modulating these pathways.

Finerenone Dose-Exposure-Serum Potassium Response Analysis of FIDELIO-DKD Phase III: The Role of Dosing, Titration, and Inclusion Criteria.

BACKGROUND: Finerenone is a nonsteroidal selective mineralocorticoid receptor antagonist (MRA) that demonstrated efficacy in delaying the progression of chronic kidney disease (CKD) and reducing cardiovascular events in patients with CKD and type 2 diabetes mellitus in FIDELIO-DKD, where 5734 patients were randomized 1:1 to receive either finerenone or placebo, with a median follow-up of 2.6 years. Doses of finerenone 10 or 20 mg once daily were titrated based on (serum) potassium and estimated glomerular filtration rate. The MRA mode of action increases potassium. METHODS: Nonlinear mixed-effects population pharmacokinetic/pharmacodynamic models were used to analyze the finerenone dose-exposure-response relationship for potassium in FIDELIO-DKD. Individual time-varying exposures from pharmacokinetic analyses were related to the potassium response via a maximal effect, indirect-response model informed by 148,384 serum potassium measurements. RESULTS: Although observed potassium levels decreased with increasing dose (i.e., inverse relation), model-based simulations for a fixed-dose setting (i.e., no dose titration) revealed the intrinsic finerenone dose-exposure-potassium response, with potassium levels increasing in a dose- and exposure-dependent manner, thus explaining the apparent conflict. The potassium limit for inclusion and uptitration from finerenone 10 to 20 mg in FIDELIO-DKD was ≤ 4.8 mmol/L. Modified limits of ≤ 5.0 mmol/L were simulated, resulting in higher hyperkalemia frequencies for both the finerenone and the placebo arms, whereas the relative hyperkalemia risk of a finerenone treatment compared with placebo did not increase. CONCLUSIONS: The analyses demonstrated the effectiveness of finerenone dose titration in managing serum potassium and provide a quantitative basis to guide safe clinical use.

PK/PD modeling of FXI antisense oligonucleotides to bridge the dose-FXI activity relation from healthy volunteers to end-stage renal disease patients.

IONIS-FXIRX (BAY2306001) is an antisense oligonucleotide that inhibits the synthesis of coagulation factor XI (FXI) and has been investigated in healthy volunteers and patients with end-stage renal disease (ESRD). FXI-LICA (BAY2976217) shares the same RNA sequence as IONIS-FXIRX 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 patients with ESRD on hemodialysis. We present a model-informed bridging approach that facilitates the extrapolation of the dose-exposure-FXI relationship from IONIS-FXIRX to FXI-LICA in patients with ESRD and, thus, supports the selection of FX-LICA doses being investigated in patients with ESRD. A two-compartment pharmacokinetic (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/pharmacodynamic model adequately described the median trends, as well as the interindividual variabilities for plasma drug concentration and FXI activity in healthy volunteers of IONIS-FXIRX and FXI-LICA, and in patients with ESRD of IONIS-FXIRX . The 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 patients with ESRD and healthy volunteers, doses of 40 mg, 80 mg, and 120 mg FXI-LICA are expected to cover the target range of clinical interest for steady-state FXI activity in the phase IIb study of FXI-LICA in patients with ESRD undergoing hemodialysis.

A population K-PD model analysis of long-term testosterone inhibition in prostate cancer patients undergoing intermittent androgen deprivation therapy.

Intermittent androgen deprivation therapy with gonadotropin-releasing-hormone (GnRH) agonists can prevent or delay disease progression and development of castration resistant prostate cancer for subpopulations of prostate cancer patients. It may also reduce risk and severity of side effects associated with chemical castration in prostate cancer (PCa) patients. One of the earliest comprehensively documented clinical trials on this was reported in a Canadian patient population treated with leuprorelin preceded by a lead-in with cyproterone acetate. A systems-based mixed effect analysis of testosterone response in active and recovery phases allows inference of new information from this patient population. Efficacy of androgen deprivation therapy is presumed to depend on a treshold value for testosterone at the nadir, below which no additional beneficial effects on PSA reponse can be expected, and occurance of testosterone breakthroughs during active therapy. The present analysis results in a mixed effect model, incorporating GnRH receptor activation, testosterone turnover and feedback mechanisms, describing and predicting testosterone inhibition under intermittent androgen deprivation therapy on the individual and population level, during multiple years of therapy. Testosterone levels in these patients decline over time with an estimated first order rate constant of 0.083 year-1(T1/2 = 8.4 y), with a substantial distribution among this patient population, compared to the general population. PCa patients leaving the trial due to unmanageble PSA relapse appear to have slightly higher testosterone levels at the nadir than sustained responders. These findings are expected to contribute to an increased understanding of the role of testosterone in long term disease progression of prostate cancer.

Population pharmacokinetics and pharmacodynamics of a novel vascular adhesion protein-1 inhibitor using a multiple-target mediated drug disposition model.

ASP8232 is a novel inhibitor of vascular adhesion protein-1 that was under evaluation for reducing residual albuminuria in patients with diabetic kidney disease. To characterize the pharmacokinetics (PK) of ASP8232 and its effect on vascular adhesion protein 1 (VAP-1) plasma activity and VAP-1 concentrations (pharmacodynamics, PD) in an integrated and quantitative manner, a target mediated drug disposition model was developed based on pooled data from four completed clinical trials with ASP8232 in healthy volunteers, and in patients with diabetic kidney disease and diabetic macular edema, respectively. In this model, the binding of ASP8232 to its soluble and membrane-bound target in the central and peripheral compartments were included. The model was able to adequately describe the non-linear PK and PD of ASP8232. The observed difference in PK between healthy volunteers and renally impaired patients could be explained by an effect of baseline estimated glomerular filtration rate on ASP8232 clearance and relative bioavailability. The relationship between ASP8232 concentration and VAP-1 inhibition was successfully established and can be applied to simulate drug exposure and degree of VAP-1 inhibition for any given dose of ASP8232 across the spectrum of renal function.

Mechanism-based modeling of the effect of a novel inhibitor of vascular adhesion protein-1 on albuminuria and renal function markers in patients with diabetic kidney disease.

The vascular adhesion protein-1 (VAP-1) inhibitor ASP8232 reduces albuminuria in patients with type 2 diabetes and chronic kidney disease. A mechanism-based model was developed to quantify the effects of ASP8232 on renal markers from a placebo-controlled Phase 2 study in diabetic kidney disease with 12 weeks of ASP8232 treatment. The model incorporated the available pharmacokinetic, pharmacodynamic (plasma VAP-1 concentration and activity), serum and urine creatinine, serum cystatin C, albumin excretion rate, urinary albumin-to-creatinine ratio, and urine volume information in an integrated manner. Drug-independent time-varying changes and different drug effects could be quantified for these markers using the model. Through simulations, this model provided the opportunity to dissect the relationship and longitudinal association between the estimated glomerular filtration rate and albuminuria and to quantify the pharmacological effects of ASP8232. The developed drug-independent model may be useful as a starting point for other compounds affecting the same biomarkers in a similar time scale.

Population Pharmacokinetic and Exposure-Response Analysis of Finerenone: Insights Based on Phase IIb Data and Simulations to Support Dose Selection for Pivotal Trials in Type 2 Diabetes with Chronic Kidney Disease.

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.

Population pharmacokinetic-pharmacodynamic modelling of the relationship between testosterone and prostate specific antigen in patients with prostate cancer during treatment with leuprorelin.

AIMS: This investigation aimed to quantitatively characterize the relationship between the gonadotropin-releasing hormone agonist leuprorelin, testosterone (T) and prostate specific antigen (PSA) concentrations over time, to aid identification of a target T concentration that optimises the balance of the benefits of T suppression whilst reducing the risk of side effects related to futile over-suppression. METHODS: Data from a single dose study to investigate the effect of leuprorelin in a 6-month depot formulation on T and PSA in prostate cancer patients were analysed using a population pharmacokinetic-pharmacodynamic modelling approach. The developed model was qualified using external data from 3 studies, in which the effect of different formulations of leuprorelin on T and PSA was evaluated in prostate cancer patients. RESULTS: The effect of leuprorelin on the relationship between T and PSA was adequately characterized by the Romero model with minor modifications, combined with a turnover model to describe the delay in response between T and PSA. The data were significantly better described when assuming a minimum PSA level that is independent on the treatment-related reduction in T, as compared to a model with a proportional reduction in PSA and T. CONCLUSIONS: The model-based analysis suggests that on a population level, reducing T concentrations below 35 ng/dL does not result in a further decrease in PSA levels (>95% of the minimal PSA level is reached). More data are required to support this relationship in the lower T and PSA range.

Characterization and Prediction of Cardiovascular Effects of Fingolimod and Siponimod Using a Systems Pharmacology Modeling Approach.

Sphingosine 1-phosphate (S1P) receptor agonists are associated with cardiovascular effects in humans. This study aims to develop a systems pharmacology model to identify the site of action (i.e., primary hemodynamic response variable) of S1P receptor agonists, and to predict, in a quantitative manner, the cardiovascular effects of novel S1P receptor agonists in vivo. The cardiovascular effects of once-daily fingolimod (0, 0.1, 0.3, 1, 3, and 10 mg/kg) and siponimod (3 and 15 mg/kg) were continuously recorded in spontaneously hypertensive rats and Wistar-Kyoto rats. The results were analyzed using a recently developed systems cardiovascular pharmacology model, i.e. the CVS model; total peripheral resistance and heart rate were identified as the site of action for fingolimod. Next, the CVS model was interfaced with an S1P agonist pharmacokinetic-pharmacodynamic (PKPD) model. This combined model adequately predicted, in a quantitative manner, the cardiovascular effects of siponimod using in vitro binding assays. In conclusion, the combined CVS and S1P agonist PKPD model adequately describes the hemodynamic effects of S1P receptor agonists in rats and constitutes a basis for the prediction, in a strictly quantitative manner, of the cardiovascular effects of novel S1P receptor agonists.

Translational pharmacokinetic modeling of fingolimod (FTY720) as a paradigm compound subject to sphingosine kinase-mediated phosphorylation.

A complicating factor in the translational pharmacology of sphingosine 1-phosphate agonists is that they exert their pharmacological effect through their respective phosphate metabolites, which are formed by the enzyme sphingosine kinase (S1PHK). In this investigation, we present a semimechanistic pharmacokinetic model for the interconversion of S1PHK substrates and their respective phosphates in rats and humans with the aim of investigating whether characterization of the rate of phosphorylation in blood platelets constitutes a basis for interspecies scaling using fingolimod as a model compound. Data on the time course of fingolimod and fingolimod-phosphate (fingolimod-P) blood concentrations after intravenous and oral administration of fingolimod and/or fingolimod-P in rats and after oral administration of fingolimod in doses of 0.5, 1.25, and 5 mg once daily in healthy volunteers were analyzed in conjunction with data on the ex vivo interconversion and blood-plasma distribution in rat and human blood, respectively. Integrating the data from the ex vivo and in vivo studies enabled simulation of fingolimod and fingolimod-P concentrations in plasma rather than blood, which are more relevant for characterizing drug effects. Large interspecies differences in the rate of phosphorylation between rats and humans were quantified. In human, phosphorylation of fingolimod in the platelets was four times slower compared with rat, whereas the dephosphorylation rates were comparable in both species. This partly explained the 10-12-fold overprediction of fingolimod-P exposure in human when applying a dose-by-factor approach on the developed rat model. Additionally, differences in presystemic phosphorylation should also be taken into account.

Nonlinear mixed effects modeling of the diurnal blood pressure profile in a multiracial population.

BACKGROUND: Cardiac and cerebrovascular events in hypertensive patients are related to specific features of the 24-hour diurnal blood pressure (BP) profile (i.e., daytime and nighttime BP, nocturnal dip (ND), and morning surge (MS)). This investigation aimed to characterize 24-hour diurnal systolic BP (SBP) with parameters that correlate directly with daytime and nighttime SBP, ND, and MS using nonlinear mixed effects modeling. METHODS: Ambulatory 24-hour SBP measurements (ABPM) of 196 nontreated subjects from three ethnic groups were available. A population model was parameterized in NONMEM to estimate and evaluate the parameters baseline SBP (BSL), nadir (minimum SBP during the night), and change (SBP difference between day and night). Associations were tested between these parameters and patient-related factors to explain interindividual variability. RESULTS: The diurnal SBP profile was adequately described as the sum of 2 cosine functions. The following typical values (interindividual variability) were found: BSL = 139 mm Hg (11%); nadir = 122 mm Hg (14%); change = 25 mm Hg (52%), and residual error = 12 mm Hg. The model parameters correlate well with daytime and nighttime SBP, ND, and MS (R (2) = 0.50-0.92). During covariate analysis, ethnicity was found to be associated with change; change was 40% higher in white Dutch subjects and 26.8% higher in South Asians than in blacks. CONCLUSIONS: The developed population model allows simultaneous estimation of BSL, nadir, and change for all individuals in the investigated population, regardless of individual number of SBP measurements. Ethnicity was associated with change. The model provides a tool to evaluate and optimize the sampling frequency for 24-hour ABPM.