Introduction: Rituximab, an anti-cluster of differentiation (CD)-20 monoclonal antibody, is used in the treatment of non-Hodgkin lymphoma (NHL), chronic lymphocytic leukemia, and rheumatoid arthritis. The pharmacokinetics of rituximab have been reported to be target mediated, but this alone may not fully explain the nonlinear decay of its concentrations over time.
Objective: This study aimed to explore the potential role of immunoglobulin (Fc gamma receptor; FcγR) and neonatal Fc receptor (FcRn) in the disposition of rituximab.
Methods: Concentration-time data from 108 patients with NHL, 118 with chronic lymphocytic leukemia, and 90 with rheumatoid arthritis were collected to refine a two-compartment population pharmacokinetic model with target-mediated drug disposition and irreversible binding approximation. Non-specific rituximab elimination was described using an intercompartment FcRn-mediated disposition model. Additionally, rituximab was assumed to bind to FcγR-expressing cells in both central and peripheral compartments; its disposition resulting from these mechanisms was described using quasi-steady-state interaction models.
Results: The FcRn-mediated disposition model provided a satisfactory description of the data and was further improved by incorporating central and peripheral FcγR quasi-steady-state interaction models with steady-state dissociation constants estimated at 586 and 418 nM, respectively. CD19 cell count was related to target-mediated elimination rate constant (p = 1.7 × 10-8) and inversely related to non-specific elimination (assessed by estimated FcRn amount, p = 2.1 × 10-8). In patients with NHL, FcγR levels in central and peripheral compartments increased with baseline metabolic tumor volume (p = 7.0 × 10-6 and p = 5.0 × 10-28, respectively).
Conclusion: The pharmacokinetics of rituximab are mediated both by Fab (target) interactions and by FcγR and FcRn interactions.
Background and objective: Balcinrenone is a novel mineralocorticoid receptor modulator which, based on preclinical data, maintains cardio-renal benefits without increasing hyperkalemia risk. Balcinrenone is developed in combination with dapagliflozin for the treatment of heart failure (HF) with impaired kidney function and chronic kidney disease (CKD). The aim of this work was to apply a population pharmacokinetic (popPK) approach to describe the pharmacokinetics (PK) of balcinrenone, and to quantify the effects of intrinsic and extrinsic factors on balcinrenone PK.
Methods: The assessment was based on data from six clinical studies in healthy participants (NCT03843060, NCT03804645, and NCT04798222), participants with renal impairment (NCT04469907), and participants with HF and CKD (NCT03682497 and NCT04595370) using the immediate-release capsule formulation (chosen for phase 3 studies).
Results: Food state (i.e., taking balcinrenone with or without food), renal function (estimated glomerular filtration rate [eGFR], incorporated using power function of eGFR on apparent clearance), and study type (phase 1 studies with mainly healthy participants or phase 1b/2b studies in patients with HF and CKD) were identified as covariates on balcinrenone exposure (area under the curve at steady-state [AUCss]). The magnitude of the impact of food state on balcinrenone exposure was minor, with a 1.13-fold (95% confidence interval [CI] 1.06-1.21) increase in AUCss when balcinrenone was taken with food compared with in a fasted state. Participants with a lower eGFR were observed to have higher exposure: those with an eGFR of 25 mL/min/1.73 m2 had a 1.44-fold (95% CI 1.22-1.69) increase in balcinrenone AUCss compared with participants with an eGFR of 60 mL/min/1.73 m2. Participants from phase 1 studies were estimated to have a 0.49-fold (95% CI 0.41-0.60) lower exposure compared with patients from phase 1b/2b studies.
Conclusions: Participants with HF and CKD were observed to have approximately 50% lower apparent clearance compared with healthy participants and those with renal impairment, after adjusting for differences in eGFR. This may indicate that factors other than renal function may impact the apparent clearance of balcinrenone. The impact of the covariates on balcinrenone exposure (AUCss) in the intended patient population was less than 50% relative to a reference participant.
Background and aim: Direct oral anticoagulants (DOACs) are now a well-established class of medication for blood clot prevention and treatment. So far, literature evaluating real-world data on the drug-drug interactions (DDIs) between DOACs and other medications in patients with pulmonary embolism (PE) is limited. This study aims to investigate these interactions in patients with PE to address this and improve patient care.
Materials and methods: In a retrospective study, patients' medications were recorded upon hospital discharge and reviewed again 3 months later. A clinical decision support system (AiDKlinik® Release 3.5) was initially used to screen for DDIs and drug-related problems. Subsequently, medications were entered into Lexicomp®, a comprehensive drug interaction database, to gain detailed scientific explanations and references for the identified interactions and their mechanisms. Binary logistic random intercept models were used to identify potential risk factors of drug-anticoagulation interactions.
Results: The 477 included PE patients had a median intake of five drugs. Drug-anticoagulation interactions depended strongly on the number of medications taken (P value < 0.001). However, the association was non-linear, resulting in a saturation effect for a higher number of drugs. The odds ratio for having at least one drug-anticoagulation interaction was 0.40 (95% confidence interval 0.17-0.96; P value = 0.040) in patients with hypertension.
Conclusions: The potential for DDIs with DOACs represents a significant concern. By being aware of the most common interactions, risk factors and avoidance strategies, the safety and efficacy of therapy can be optimized.
Intravenous iron-carbohydrate complexes are a class of nanomedicines that are widely used globally to treat iron deficiency and iron deficiency anemia associated with a wide spectrum of disease states. Despite being widely used in clinical practice for more than seven decades, the understanding of their in vivo disposition including tissue biodistribution and kinetics of the nanoparticle degradation at the cellular level is not well-understood. Moreover, the critical quality attributes that influence in vivo pharmacokinetics have not been fully defined. In particular, the carbohydrate moiety plays an influential role in how the nanoparticulate iron-carbohydrate complex interacts with the biological system. Developing a physiologically based pharmacokinetic (PBPK) model would facilitate a deeper understating of the key nanomedicine attributes that predict in vivo performance. Because endogenous iron metabolism complicates pharmacokinetic modeling for this complex class of drugs, models of gold nanoparticles may provide a substantive roadmap to begin to build a viable PBPK model for iron-carbohydrate nanomedicines. In the future, PBPK models that integrate recent mechanistic data regarding tissue biodistribution and intracellular iron kinetics for parameterization have the potential to improve manufacturing quality and clinical use of these complex drugs.
Zolbetuximab is a first-in-class chimeric (mouse/human) monoclonal antibody targeted to the tight junction protein claudin 18.2 (CLDN18.2), an emerging biomarker in gastric/gastroesophageal junction (G/GEJ) cancer. This review summarizes the clinical pharmacology of zolbetuximab on the basis of available clinical trial data. Population pharmacokinetics (PK) were evaluated using data from eight clinical studies (n = 714). Zolbetuximab PK following intravenous administration was described by a two-compartment model with linear and time-dependent clearance components. On the basis of simulations using the 800/600 mg/m2 every 3 weeks (Q3W) dosing regimen from phase 3 trials, gastrectomy (versus no gastrectomy) was predicted to increase zolbetuximab Ctrough by ≥ 50%, but without apparent effects on the benefit-risk profile of zolbetuximab. No dose adjustments are necessary for individuals with mild/moderate renal impairment or mild hepatic impairment. Zolbetuximab PK was not different among the ethnicities evaluated (White, Asian, Chinese, Japanese, Korean). There were no apparent safety or PK ramifications of zolbetuximab coadministration with oxaliplatin or 5-fluorouracil. The incidence of antidrug antibodies to zolbetuximab was low, with no apparent clinical consequence. Exposure-response analysis suggested that higher zolbetuximab exposures may prolong survival outcomes but may also increase the probability of experiencing gastrointestinal events and infusion-related reactions. A proposed alternative 800/400 mg/m2 every 2 weeks (Q2W) regimen for use in combination with Q2W chemotherapy was shown to have comparable safety and efficacy to the 800/600 mg/m2 Q3W regimen. Zolbetuximab, the first and only approved therapy targeted to CLDN18.2, is a valuable new treatment option for patients with CLDN18.2-positive, locally advanced unresectable or metastatic G/GEJ cancer.
Background: The increasing use of immune checkpoint inhibitors, such as durvalumab, places a significant financial burden on healthcare systems, strains hospital capacities, and contributes to environmental concerns.
Objective: We aimed to develop alternative dosing strategies to optimize durvalumab administration, reduce unnecessary drug use, and ensure sustainable cancer care without sacrificing efficacy.
Methods: Using the population pharmacokinetic model developed by the licensing holder, we designed two alternative dosing strategies for non-small cell lung cancer based on therapeutic drug monitoring. Adjustments were made to the dose or administration interval, following regulatory standards for in silico dose optimization. A pharmacoeconomic evaluation was conducted to estimate potential cost savings from a medical perspective.
Results: Both alternative strategies achieved high exposure levels, with 98.1-99.0% of patients exceeding a predefined efficacy target, surpassing the 95.4% predicted by the license holder for the approved 10 mg/kg 2-weekly regimen. They also reduced overall drug exposure by 7-24% and eliminated drug wastage, resulting in an average annual cost reduction of €25,163 (22.9%) per patient.
Conclusion: Therapeutic drug monitoring-guided adjustments for durvalumab offer a potentially cost-saving way to optimize drug use, reduce healthcare burdens, and lessen environmental impact while ensuring adequate patient exposure. Our proposal's evidence provides a solid basis for a non-inferiority study.
Background and objective: Fidanacogene elaparvovec (BEQVEZ™), an adeno-associated virus-based gene therapy approved for the treatment of hemophilia B, enables endogenous production of factor IX (FIX), preventing bleeding and reducing the need for FIX replacement. Nonlinear mixed-effects models are routinely used for population pharmacokinetic analyses of FIX replacement therapies but have not previously been applied to FIX activity observations from gene therapy trials. A nonlinear mixed-effects modeling approach was used to characterize FIX activity following fidanacogene elaparvovec and/or FIX replacement, identify covariates affecting FIX activity, and estimate the longer-term durability of FIX activity after a single dose of fidanacogene elaparvovec.
Methods: Population modeling using NONMEM® was performed with FIX activity data pooled from 11 clinical trials in participants with hemophilia B (three fidanacogene elaparvovec studies [n = 63]; eight nonacog alfa studies [n = 274]). FIX activity was assessed by one-stage clotting assays.
Results: FIX activity was described by a compartmental model for gene and protein expression and a three-compartment model for FIX disposition. Covariates included age and body weight on gene-therapy-related parameters. Following fidanacogene elaparvovec administration, model-predicted FIX activity reached a median (90% prediction interval) peak of 13.5 (3.12-41.3) IU/dL and remained within 50% of the peak for a median of 8.67 (0.411-15.0) years. At 15 years post-infusion, median predicted FIX activity was 4.11 (1.15-17.6) IU/dL.
Conclusions: Model-based estimates showed that a single dose of fidanacogene elaparvovec elicited long-lasting elevations in FIX activity, suggesting most individuals would not require prophylactic FIX replacement for at least 15 years post-infusion.
Clinicaltrials:
Gov identifier: NCT00364182, NCT01335061, NCT00037557, NCT00093171, NCT00093210, NCT03861273, NCT03307980, NCT02484092.
Background and objectives: The factors that predict colchicine plasma concentrations and the impact on safety and efficacy are under-researched. We aimed to determine the probability of achieving steady-state plasma concentrations within the nominal therapeutic range of 0.5-3 ng/mL.
Methods: Colchicine plasma concentrations from 78 people with gout were analysed using non-linear mixed effects. Body size, kidney function, concomitant drugs, ethnicity, sex, age and adherence were tested as covariates in the model. Simulations were conducted to determine the probability of achieving steady-state minimum, maximum and average concentrations within the therapeutic range of 0.5-3 ng/mL under different doses and for different patient characteristics. We considered colchicine doses that produced > 80% of steady-state average concentrations < 3 ng/mL and > 0.5 ng/mL to have a reasonable probability of safety and efficacy.
Results: A two-compartment pharmacokinetic model with zero-order absorption was the best fit. Body weight, sex and statin use were significant predictors of colchicine pharmacokinetics, reducing the between-subject variance on clearance by about 40%. The model predicted that colchicine dosages of ≤ 1.5 mg daily carry a low risk of toxicity based on the criteria defined here. Efficacious concentrations were achieved for all dosages tested except 0.5 mg daily, where concentrations below the proposed therapeutic range may occur in those with a body weight > 80 kg. Higher colchicine dosages of > 1.5 mg daily may exceed the proposed upper limit of safety in many individuals, particularly those with low body weight who are taking statins.
Conclusion: A model for the pharmacokinetics of colchicine was developed and evaluated. Low-dose regimes (≤ 1.5 mg daily) are not predicted to achieve concentrations above the proposed safety threshold of 3 ng/mL in most people, although concentrations below the lower limit of the therapeutic range may occur in those taking 0.5-mg doses who are > 80 kg in body weight. Higher colchicine dosages of > 1.5 mg daily may exceed the proposed upper limit of safety in individuals with low body weight who are taking statins.
Multiple peaking in pharmacokinetics refers to the occurrence of two or more peaks of drug plasma concentrations following a single dose administration. It complicates interpretation of pharmacokinetics parameters and influences clinical decision-making regarding drug efficacy and bioequivalence. This review re-examines and extends an earlier seminal review on the physicochemical and formulation-related causes and physiological mechanisms of multiple peaking. In addition to the previously discussed mechanisms, factors such as lymphatic drug uptake, enterogastric recycling, hepatoenteric recycling, dual absorption pathways, overdose scenarios, and pharmacobezoar formation have also been identified as contributors to the multiple peaking phenomenon. Furthermore, the role of specialized formulations, particularly pulsatile drug delivery systems (PDDS), has been explored in relation to their impact on this complex pharmacokinetics behavior. Moreover, this review highlights advanced modeling tools, namely physiologically based pharmacokinetic modeling (PBPK), illustrating how they can be applied to decipher complex absorption profiles, and highlights bioequivalence considerations for products exhibiting multiple peaks, such as partial area under the curve (pAUC). Improved identification and modeling of this phenomenon is critical to optimizing drug development, therapeutic monitoring, precision dosing, and regulatory decision-making.
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