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.

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.

Population pharmacokinetic analysis of rivaroxaban in children and comparison to prospective physiologically-based pharmacokinetic predictions.

Rivaroxaban has been investigated in the EINSTEIN-Jr program for the treatment of acute venous thromboembolism (VTE) in children aged 0 to 18 years and in the UNIVERSE program for thromboprophylaxis in children aged 2 to 8 years with congenital heart disease after Fontan-procedure. Physiologically-based pharmacokinetic (PBPK) and population pharmacokinetic (PopPK) modeling were used throughout the pediatric development of rivaroxaban according to the learn-and-confirm paradigm. The development strategy was to match pediatric drug exposures to adult exposure proven to be safe and efficacious. In this analysis, a refined pediatric PopPK model for rivaroxaban based on integrated EINSTEIN-Jr data and interim PK data from part A of the UNIVERSE phase III study was developed and the influence of potential covariates and intrinsic factors on rivaroxaban exposure was assessed. The model adequately described the observed pediatric PK data. PK parameters and exposure metrics estimated by the PopPK model were compared to the predictions from a previously published pediatric PBPK model for rivaroxaban. Ninety-one percent of the individual post hoc clearance estimates were found within the 5th to 95th percentile of the PBPK model predictions. In patients below 2 years of age, however, clearance was underpredicted by the PBPK model. The iterative and integrative use of PBPK and PopPK modeling and simulation played a major role in the establishment of the bodyweight-adjusted rivaroxaban dosing regimen that was ultimately confirmed to be a safe and efficacious dosing regimen for children aged 0 to 18 years with acute VTE in the EINSTEIN-Jr phase III study.

An Integrated Population Pharmacokinetic Analysis to Characterize Levonorgestrel Pharmacokinetics After Different Administration Routes.

To compare the pharmacokinetics (PK) of the progestin levonorgestrel for various routes of administration, an integrated population PK analysis was performed. This analysis integrated data from 10 clinical pharmacology studies and resulted in a single, comprehensive population PK model (and its applications) describing the PK of levonorgestrel and its variability for 6 levonorgestrel-containing contraceptives: 3 intrauterine systems (IUSs; levonorgestrel [LNG]-IUS 20 [Mirena® ], LNG-IUS 12 [Kyleena® ], and LNG-IUS 8 [Jaydess® /Skyla® ]); 2 oral contraceptives (the progestin-only pill [Microlut® /Norgeston® ] and the combined oral contraceptive [Miranova® ]); and a subdermal implant (Jadelle® ). The levonorgestrel-containing contraceptives administered orally or as an implant act mainly via their systemic (unbound) levonorgestrel exposure, whereas levonorgestrel administered via an IUS is released directly into the uterine cavity, resulting in lower systemic levonorgestrel concentrations. The integrated population PK analysis revealed that the combined oral contraceptive led to the highest levonorgestrel exposure, followed by the progestin-only pill and the implant, which led to similar levonorgestrel exposure, and the IUSs, which led to the lowest levonorgestrel exposure (in decreasing order: LNG-IUS 20, LNG-IUS 12, and LNG-IUS 8). The difference was even more distinct at the end of the indicated duration of use of 3 years (LNG-IUS 8) and 5 years (LNG-IUS 20 and LNG-IUS 12). Comparing the 3 IUSs and the implant, in vivo release rates were highest for the implant, followed by LNG-IUS 20, then LNG-IUS 12, and were lowest for LNG-IUS 8. This is in line with the comparison of the total levonorgestrel concentrations.

A cross-species translational pharmacokinetic-pharmacodynamic evaluation of core body temperature reduction by the TRPM8 blocker PF-05105679.

PF-05105679 is a moderately potent TRPM8 blocker which has been evaluated for the treatment of cold pain sensitivity. The TRPM8 channel is responsible for the sensation of cold environmental temperatures and has been implicated in regulation of core body temperature. Consequently, blockade of TRPM8 has been suggested to result in lowering of core body temperature. As part of the progression to human studies, the effect of PF-05105679 on core body temperature has been investigated in animals. Safety pharmacology studies showed that PF-05105679 reduced core body temperature in a manner that was inversely related to body weight of the species tested (greater exposure to PF-05105679 was required to lower temperature by 1°C in higher species). Based on an allometric (body weight) relationship, it was hypothesized that PF-05105679 would not lower core body temperature in humans at exposures that could exhibit pharmacological effects on cold pain sensation. On administration to humans, PF-05105679 was indeed effective at reversing the cold pain sensation associated with the cold pressor test in the absence of effects on core body temperature.

Adenoviral vectors expressing siRNAs for discovery and validation of gene function.

RNA interference is a powerful tool for studying gene function and for drug target discovery in diverse organisms and cell types. In mammalian systems, small interfering RNAs (siRNAs), or DNA plasmids expressing these siRNAs, have been used to down-modulate gene expression. However, inefficient transfection protocols, in particular, for primary cell types, have hampered the use of these tools in disease-relevant cellular assays. To be able to use this technology for genome-wide function screening, a more robust transduction protocol, resulting in a longer duration of the knock-down effect, is required. Here, we describe the validation of adenoviral vectors that express hairpin RNAs that are further processed to siRNAs. Infection of cell lines, or primary human cells, with these viruses leads to an efficient, sequence-specific, and prolonged reduction of the corresponding target mRNA, resulting in a reduction of the encoded protein level in the cell. For knock-down of one of the targets, GalphaS, we have measured inhibition of ligand-dependent, G-protein-coupled signaling. It is expected that this technology will prove to be of great value in target validation and target discovery efforts.