Population pharmacokinetic-pharmacodynamic modeling of biological agents: when modeling meets reality

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.

Individualized Dosing of Therapeutic Monoclonal Antibodies-a Changing Treatment Paradigm?

The introduction of monoclonal antibodies (mAbs) to the treatment of inflammatory bowel disease (IBD) was an important medical milestone. MAbs have been demonstrated as safe and efficacious treatments of IBD. However, a large percentage of patients either fail to respond initially or lose response to therapy after a period of treatment. Although there are factors associated with poor treatment outcomes in IBD, one cause for treatment failure may be low mAb exposure. Consequently, gastroenterologists have begun using therapeutic drug monitoring (TDM) to guide dose adjustment. However, while beneficial, TDM does not provide sufficient information to effectively adjust doses. The pharmacokinetics (PK) and pharmacodynamics (PD) of mAbs are complex, with numerous factors impacting on mAb PK and PD. The concept of dashboard-guided dosing based on Bayesian PK models allows physicians to combine TDM with factors influencing mAb PK to individualize therapy more effectively. One issue with TDM has been the slow turnaround of assay results, either necessitating an additional clinic visit for a sample or reacting to TDM results at a subsequent, rather than the current, dose. New point-of-care (POC) assays for mAbs are being developed that would potentially allow physicians to determine drug concentration quickly. However, work remains to understand how to determine what target exposure is needed for an individual patient, and whether the combination of POC assays and dashboards presents a safe approach with substantial outcome benefit over the current standard of care.

Dashboards for Therapeutic Monoclonal Antibodies: Learning and Confirming

Inflammatory diseases (ID) are incurable, progressive diseases. Literature evidence cites increasing incidence of these diseases worldwide. When treatments with chemical immunosuppressive agents fail, patients are often treated with monoclonal antibodies (MAbs). However, MAb failure rates are generally high, with approximately half the patients being discontinued within 4 years, necessitating switching to another MAb. One potential cause of treatment failure is subtherapeutic exposure. Several studies demonstrated associations between trough MAb concentrations and clinical response, supporting the notion that improving drug exposure may result in improved outcomes. MAbs exhibit complex and highly variable pharmacokinetics in ID patients with numerous factors affecting clearance. Bayesian-guided dosing with dashboard systems is a new tool being investigated in the treatment of ID to reduce variability in exposure. Simulations suggest dashboards will be effective at maintaining patients at target troughs. However, when patients are dosed using doses or intervals outside those listed in prescribing information, there is concern that patients may have drug exposures beyond or below the ranges found to be safe and efficacious. This manuscript reviews the rationale behind dashboard development, evaluations of expected performance, and a simulated assessment of MAb exposure with dashboard-based dosing versus dosing based on the prescribing information. We introduce the concept of pharmacologic equivalence-if patients are dosed based on individual pharmacokinetics, the resulting exposure is consistent with exposures achieved using labeled dosing. We further show that dashboard-based dosing results in observed exposures that are generally contained within the range of exposures achieved with labeled dosing.

Model Evaluation of Continuous Data Pharmacometric Models: Metrics and Graphics

This article represents the first in a series of tutorials on model evaluation in nonlinear mixed effect models (NLMEMs), from the International Society of Pharmacometrics (ISoP) Model Evaluation Group. Numerous tools are available for evaluation of NLMEM, with a particular emphasis on visual assessment. This first basic tutorial focuses on presenting graphical evaluation tools of NLMEM for continuous data. It illustrates graphs for correct or misspecified models, discusses their pros and cons, and recalls the definition of metrics used.

Pharmacokinetic and pharmacodynamic characterization of a novel formulation containing co-formulated interferons alpha-2b and gamma in healthy male volunteers

Background

More potent antitumor activity is desired in Interferon (IFN)-treated cancer patients. This could be achieved by combining IFN alpha and IFN gamma. The aim of this work was to characterize the pharmacokinetics and pharmacodynamics of a novel formulation containing a co-formulated combination of IFNs alpha-2b and gamma (CIGB-128-A).

Methods

A group of nine healthy male subjects received intramuscularly 24.5 × 10⁶ IU of CIGB-128-A. IFN concentrations were evaluated for 48 h. Serum neopterin, beta2-microglobulin (β₂M) and 2′–5′ oligoadenylate synthetase (2′–5′ OAS), classical IFN-inducible serum markers, were measured during 192 h by enzyme immunoassay and body temperature was used as pharmacodynamic variable as well.

Results

Concerning pharmacokinetics, serum IFNs’ profiles were better fitted to a mono-compartmental model with consecutive zero order and first order absorption, one bioavailability value. No interferences by simultaneous administered IFNs were observed in their typical similar systemic profiles. Neopterin and β₂M time profiles showed a delay that was efficiently linked to pharmacokinetics by means of a zero order absorption rate constant. Neopterin level was nine-fold higher than initial values, 48 h post-administration, an increment not described before. At this time, mean serum β₂M peaked around the double from baseline. Serum concentrations of the enzyme 2′–5′ OAS was still elevated on the 8 day post-injection. The formulation was well tolerated. Most frequent adverse reactions were fever, headache, arthralgia and lymphopenia, mostly mild.

Conclusions

The administration of co-formulated IFN alpha-2b and IFN gamma likely provides improved pharmacodynamic properties that may be beneficial to treat several malignancies.

Trial registration

Cuban Public Registry of Clinical Trials RPCEC00000118, May 24, 2011.

Adalimumab and pharmacokinetics: Impact on the clinical prescription for inflammatory bowel disease

Anti-tumor necrosis factor (TNF) drugs are widely prescribed for inflammatory disease. A loss of response to adalimumab is frequent and the pharmacokinetics of anti-TNF therapy have important implications for patient management. Individual factors such as albumin, body weight, and disease severity based on the C-reactive protein level influence drug metabolism. Adalimumab trough levels are associated with clinical remission. On the other hand, the detection of antibodies is associated with clinical relapse. Immunosuppressive therapy could reduce antibody formation although the clinical impact is not proven. New algorithms are available to provide personalized treatment and adapt the dosage. More data are needed on dose de-escalation.

Assessment of hemoglobin responsiveness to epoetin alfa in patients on hemodialysis using a population pharmacokinetic pharmacodynamic model

A population pharmacokinetic pharmacodynamic (PK/PD) model describing the effect of epoetin alfa on hemoglobin (Hb) response in hemodialysis patients was developed. Epoetin alfa pharmacokinetics was described using a linear 2-compartment model. PK parameter estimates were similar to previously reported values. A maturation-structured cytokinetic model consisting of 5 compartments linked in a catenary fashion by first-order cell transfer rates following a zero-order input process described the Hb time course. The PD model described 2 subpopulations, one whose Hb response reflected epoetin alfa dosing and a second whose response was unrelated to epoetin alfa dosing. Parameter estimates from the PK/PD model were physiologically reasonable and consistent with published reports. Numerical and visual predictive checks using data from 2 studies were performed. The PK and PD of epoetin alfa were well described by the model.

Developing Exposure/Response Models for Anticancer Drug Treatment: Special Considerations

Anticancer agents often have a narrow therapeutic index (TI), requiring precise dosing to ensure sufficient exposure for clinical activity while minimizing toxicity. These agents frequently have complex pharmacology, and combination therapy may cause schedule-specific effects and interactions. We review anticancer drug development, showing how integration of modeling and simulation throughout development can inform anticancer dose selection, potentially improving the late-phase success rate. This article has a companion article in Clinical Pharmacology & Therapeutics with practical examples.

Dashboard systems: implementing pharmacometrics from bench to bedside

In recent years, there has been increasing interest in the development of medical decision-support tools, including dashboard systems. Dashboard systems are software packages that integrate information and calculations about therapeutics from multiple components into a single interface for use in the clinical environment. Given the high cost of medical care, and the increasing need to demonstrate positive clinical outcomes for reimbursement, dashboard systems may become an important tool for improving patient outcome, improving clinical efficiency and containing healthcare costs. Similarly the costs associated with drug development are also rising. The use of model-based drug development (MBDD) has been proposed as a tool to streamline this process, facilitating the selection of appropriate doses and making informed go/no-go decisions. However, complete implementation of MBDD has not always been successful owing to a variety of factors, including the resources required to provide timely modeling and simulation updates. The application of dashboard systems in drug development reduces the resource requirement and may expedite updating models as new data are collected, allowing modeling results to be available in a timely fashion. In this paper, we present some background information on dashboard systems and propose the use of these systems both in the clinic and during drug development.

Pharmacokinetic-pharmacodynamic modelling of the analgesic and antihyperalgesic effects of morphine after intravenous infusion in human volunteers

Using a modelling approach, this study aimed to (i) examine whether the pharmacodynamics of the analgesic and antihyperalgesic effects of morphine differ; (ii) investigate the influence of demographic, pain sensitivity and genetic (OPRM1) variables on between-subject variability of morphine pharmacokinetics and pharmacodynamics in human experimental pain models. The study was a randomized, double-blind, 5-arm, cross-over, placebo-controlled study. The psychophysical cutaneous pain tests, electrical pain tolerance (EPTo) and secondary hyperalgesia areas (2HA) were studied in 28 healthy individuals (15 males). The subjects were chosen based on a previous trial where 100 subjects rated (VAS) their pain during a heat injury (47°C, 7 min., 12.5 cm(2) ). The 33% lowest- and highest pain-sensitive subjects were offered participation in the present study. A two-compartment linear model with allometric scaling for weight provided the best description of the plasma concentration-time profile of morphine. Changes in the EPTo and 2HA responses with time during the placebo treatment were best described by a linear model and a quadratic model, respectively. The model discrimination process showed clear evidence for adding between-occasion variability (BOV) on baseline and the placebo slope for EPTo and 2HA, respectively. The sensitivity covariate was significant on baseline EPTo values and genetics as a covariate on the placebo slope for 2HA. The analgesic and antihyperalgesic effects of morphine were pharmacologically distinct as the models had different effect site equilibration half-lives and different covariate effects. Morphine had negligible effect on 2HA, but significant effect on EPTo.

Basic concepts in population modeling, simulation, and model-based drug development: part 3-introduction to pharmacodynamic modeling methods

Population pharmacodynamic (PD) models describe the time course of drug effects, relating exposure to response, and providing a more robust understanding of drug action than single assessments. PD models can test alternative dose regimens through simulation, allowing for informed assessment of potential dose regimens and study designs. This is the third paper in a three-part series, providing an introduction into methods for developing and evaluating population PD models. Example files are available in the Supplementary Data.