Population Pharmacokinetic/Pharmacodynamic Analysis of Nociceptive Pain Models Following an Oral Pregabalin Dose Administration to Healthy Subjects

Incorporating new approach methods (NAMs) data in dose-response assessments: The future is now!

Regulatory dose-response assessments traditionally rely on in vivo data and default assumptions. New Approach Methods (NAMs) present considerable opportunities to both augment traditional dose-response assessments and accelerate the evaluation of new/data-poor chemicals. This review aimed to determine the potential utilization of NAMs through a unified conceptual framework that compartmentalizes derivation of toxicity values into five sequential Key Dose-response Modules (KDMs): (1) point-of-departure (POD) determination, (2) test system-to-human (e.g. inter-species) toxicokinetics and (3) toxicodynamics, (4) human population (intra-species) variability in toxicodynamics, and (5) toxicokinetics. After using several "traditional" dose-response assessments to illustrate this framework, a review is presented where existing NAMs, including in silico, in vitro, and in vivo approaches, might be applied across KDMs. Further, the false dichotomy between "traditional" and NAMs-derived data sources is broken down by organizing dose-response assessments into a matrix where each KDM has Tiers of increasing precision and confidence: Tier 0: Default/generic values, Tier 1: Computational predictions, Tier 2: Surrogate measurements, and Tier 3: Direct measurements. These findings demonstrated that although many publications promote the use of NAMs in KDMs (1) for POD determination and (5) for human population toxicokinetics, the proposed matrix of KDMs and Tiers reveals additional immediate opportunities for NAMs to be integrated across other KDMs. Further, critical needs were identified for developing NAMs to improve in vitro dosimetry and quantify test system and human population toxicodynamics. Overall, broadening the integration of NAMs across the steps of dose-response assessment promises to yield higher throughput, less animal-dependent, and more science-based toxicity values for protecting human health.

Towards optimization of dexamethasone therapy in the maintenance phase of pediatric acute lymphoblastic leukemia: A population pharmacokinetic and pharmacodynamic study of dexamethasone and metabolite

Dexamethasone is crucial in pediatric acute lymphoblastic leukemia (ALL) treatment, however, studies regarding the pharmacokinetics of dexamethasone and its metabolites are scarce. Our study conducted a comprehensive pharmacokinetic-pharmacodynamic analysis of dexamethasone and metabolite, examining their association with dexamethasone-induced toxicity. Peak and trough concentrations were collected during the maintenance phase from pediatric ALL patients who received oral dexamethasone (6mg/m2/day). NONMEM was used to study the population pharmacokinetics including covariates. Pharmacokinetic (PK) and pharmacodynamic (PD) correlations between drug and its active metabolite exposure and adverse effects were examined. 382 samples (dexamethasone: n = 191; 6β-hydroxydexamethasone: n = 191) from 104 children (age range 3.0 -18.8 years) were collected. A one-compartment model described the data best. The estimated apparent dexamethasone total clearance was 26 L/h/70 kg with 18 % inter-individual variability, and an apparent volume of distribution of 123 L/70 kg, yielding a half-life of 3.3 h. Covariate analysis demonstrated that when asparaginase was co-administered, there was a 50 % reduction in both the clearance of dexamethasone and the extent to which dexamethasone was metabolized to 6β-hydroxydexamethasone. A statistically significant but weak positive correlation was observed between dexamethasone drug exposure and fasting hunger scores. Dexamethasone exposure significantly increased with asparaginase co-administration by inhibition of the CYP3A4 pathway. Our study found a statistically significant but weak positive correlation between dexamethasone exposure and increased hunger. These results support the need for more studies on how to personalize dexamethasone dosing in pediatric ALL treatment and adjust doses to limit side effects, especially in case of co-medication.

Population Pharmacokinetic Model of Intravenous Immunoglobulin in Patients Treated for Various Immune System Disorders

PURPOSE

Intravenous immunoglobulin (IVIG) is used to treat various immune system disorders, but the factors influencing its disposition are not well understood. This study aimed to estimate the population pharmacokinetic parameters of IVIG and to investigate the effect of genetic polymorphism of the FCGRT gene encoding the neonatal Fc receptor (FcRn) and clinical variability on the pharmacokinetic properties of IVIG in patients with immune system disorders.

METHODS

Patients were recruited from 4 hospitals in Malaysia. Clinical data were recorded, and blood samples were taken for pharmacokinetic and genetic studies. Population pharmacokinetic parameters were estimated by nonlinear mixed-effects modeling in Monolix. Age, weight, baseline immunoglobulin G concentration, ethnicity, sex, genotype, disease type, and comorbidity were investigated as potential covariates. Models were evaluated using the difference in objective function value, goodness-of-fit plots, visual predictive checks, and bootstrap analysis.

FINDINGS

A total of 292 blood samples were analyzed from 79 patients. The IVIG concentrations were best described by a 2-compartment model with linear elimination. Weight was found to be an important covariate for volume of distribution in the central compartment (Vc), volume of distribution in the peripheral compartment (Vp), and clearance in the central compartment, whereas disease type was found to be an important covariate for Vp. Goodness-of-fit plots indicated that the model fit the data adequately. Genetic polymorphism of the FCGRT gene encoding the neonatal Fc receptor did not affect the pharmacokinetic properties of IVIG.

IMPLICATIONS

This study supports the use of dosage based on weight as per current practice. The study findings highlight that Vp is significantly influenced by the type of disease being treated with IVIG. This relationship suggests that different disease types, particularly inflammatory and autoimmune conditions, may alter tissue permeability and fluid distribution due to varying degrees of inflammation. Increased inflammation can lead to enhanced permeability and retention of IVIG in peripheral tissues, reflecting higher Vp values.

Pharmacokinetics of Enteral Lormetazepam in Mechanically Ventilated ICU Patients with COVID-19: An Adjunct Sedative Study

BACKGROUND AND OBJECTIVE

During the coronavirus disease 2019 (COVID-19) pandemic, sedative prescriptions surged, leading to shortages of midazolam. This study investigates lormetazepam as an adjunct sedative alternative to midazolam for mechanically ventilated patients with COVID-19. We aimed to determine the clinical pharmacokinetics (PK) of enterally administered lormetazepam and provide dosing recommendations.

METHODS

Critically ill patients with acute respiratory distress syndrome (ARDS) or COVID-19 requiring mechanical ventilation were enrolled in April 2020. Lormetazepam 2 mg every 12 h was administered enterally. Blood samples were collected to quantify lormetazepam and its glucuronide. PK analysis was conducted using a one-compartment model with the Edsim++ KinPop plugin.

RESULTS

The primary PK parameters (means ± coefficient of variation [CV] %) for absorption constant (Ka), volume of distribution (Vd/F), and clearance (CL/F) were 6.4 h-1, 207 L/70 kg, and 14.5 L/h/kg0.75, respectively. Vd/F and CL/F median values were 2.64 L/kg and 2.53 mL/kg/min, respectively, with a half-life of 10.7 h. Lormetazepam's median ratio to its glucuronide was 11.5. Trough-guided dosing suggested alternatives of 0.92 mg three times daily, 1.62 mg twice daily, or 5.36 mg once daily.

CONCLUSION

This is the first study to report a validated PK model for enterally administered lormetazepam as a sedative adjunct in critically ill adults on mechanical ventilation for ARDS and COVID-19. The model was internally validated using a bootstrap procedure. Adequate lormetazepam concentrations were achieved at prescribed doses, with no significant alterations in clearance or half-life. This population model may aid in dose optimization and sedation management for future intensive care unit (ICU) patients.

Informing the risk assessment related to lactation and drug exposure: A physiologically based pharmacokinetic lactation model for pregabalin

Breastfeeding is important in childhood development, and medications are often necessary for lactating individuals, yet information on the potential risk of infant drug exposure through human milk is limited. Establishing a lactation modeling framework can advance our understanding of this topic and potentiate clinical decision making. We expanded the modeling framework previously developed for sotalol using pregabalin as a second prototypical probe compound with similar absorption, distribution, metabolism, and elimination (ADME) properties. Adult oral models were developed in PK-Sim® and used to build a lactation model in MoBi® to simulate drug transfer into human milk. The adult model was applied to breastfeeding pediatrics (ages 1 to 23 months) and subsequently integrated with the lactation model to simulate infant drug exposure according to age, size, and breastfeeding frequency. Physiologically based pharmacokinetic (PBPK) model simulations captured the data used for verification both in adults and pediatrics. Lactation simulations captured observed milk and plasma data corresponding to doses of 150 mg administered twice daily to lactating individuals, and estimated a relative infant dose (RID) of approximately 7% of the maternal dose. The infant drug exposure simulations showed peak plasma concentrations of 0.44 μg/mL occurring within the first 2 weeks of life, followed by gradual decline with age after week four. The modeling framework performs well for this second prototypical drug and warrants expansion to other drugs for further validation. PBPK modeling and simulation approaches together with clinical lactation data could ultimately help inform infant drug exposure risk assessments to guide clinical decision making.

Pregabalin for chemotherapy-induced neuropathy: background and rationale for further study

Chemotherapy-induced neuropathy is difficult to manage, and the pain associated with neuropathy is poorly responsive to gabapentin in a randomized trial. Duloxetine is the only drug that has been found to be effective in reducing pain from chemotherapy neuropathy. In this qualitative review, the use of pregabalin for chemotherapy-induced neuropathy is discussed including the rationale and pharmacological reasons why pregabalin should be considered in a large, randomized placebo-controlled trial.

Pharmacological Probes to Validate Biomarkers for Analgesic Drug Development

There is an urgent need for analgesics with improved efficacy, especially in neuropathic and other chronic pain conditions. Unfortunately, in recent decades, many candidate analgesics have failed in clinical phase II or III trials despite promising preclinical results. Translational assessment tools to verify engagement of pharmacological targets and actions on compartments of the nociceptive system are missing in both rodents and humans. Through the Innovative Medicines Initiative of the European Union and EFPIA, a consortium of researchers from academia and the pharmaceutical industry was established to identify and validate a set of functional biomarkers to assess drug-induced effects on nociceptive processing at peripheral, spinal and supraspinal levels using electrophysiological and functional neuroimaging techniques. Here, we report the results of a systematic literature search for pharmacological probes that allow for validation of these biomarkers. Of 26 candidate substances, only 7 met the inclusion criteria: evidence for nociceptive system modulation, tolerability, availability in oral form for human use and absence of active metabolites. Based on pharmacokinetic characteristics, three were selected for a set of crossover studies in rodents and healthy humans. All currently available probes act on more than one compartment of the nociceptive system. Once validated, biomarkers of nociceptive signal processing, combined with a pharmacometric modelling, will enable a more rational approach to selecting dose ranges and verifying target engagement. Combined with advances in classification of chronic pain conditions, these biomarkers are expected to accelerate analgesic drug development.