Model-based meta-analysis for comparing Vitamin D2 and D3 parent-metabolite pharmacokinetics

Population Pharmacokinetic Model of Vitamin D3 and Metabolites in Chronic Kidney Disease Patients with Vitamin D Insufficiency and Deficiency

Vitamin D insufficiency and deficiency are highly prevalent in patients with chronic kidney disease (CKD), and their pharmacokinetics are not well described. The primary study objective was to develop a population pharmacokinetic model of oral cholecalciferol (VitD3) and its three major metabolites, 25-hydroxyvitamin D3 (25D3), 1,25-dihydroxyvitamin D3 (1,25D3), and 24,25-dihydroxyvitamin D3 (24,25D3), in CKD patients with vitamin D insufficiency and deficiency. CKD subjects (n = 29) were administered one dose of oral VitD3 (5000 I.U.), and nonlinear mixed effects modeling was used to describe the pharmacokinetics of VitD3 and its metabolites. The simultaneous fit of a two-compartment model for VitD3 and a one-compartment model for each metabolite represented the observed data. A proportional error model explained the residual variability for each compound. No assessed covariate significantly affected the pharmacokinetics of VitD3 and metabolites. Visual predictive plots demonstrated the adequate fit of the pharmacokinetic data of VitD3 and metabolites. This is the first reported population pharmacokinetic modeling of VitD3 and metabolites and has the potential to inform targeted dose individualization strategies for therapy in the CKD population. Based on the simulation, doses of 600 International Unit (I.U.)/day to 1000 I.U./day for 6 months are recommended to obtain the target 25D3 concentration of between 30 and 60 ng/mL. These simulation findings could potentially contribute to the development of personalized dosage regimens for vitamin D treatment in patients with CKD.

Pharmacokinetic analysis across studies to drive knowledge-integration: A tutorial on individual patient data meta-analysis (IPDMA)

Answering challenging questions in drug development sometimes requires pharmacokinetic (PK) data analysis across different studies, for example, to characterize PKs across diverse regions or populations, or to increase statistical power for subpopulations by combining smaller size trials. Given the growing interest in data sharing and advanced computational methods, knowledge integration based on multiple data sources is increasingly applied in the context of model-informed drug discovery and development. A powerful analysis method is the individual patient data meta-analysis (IPDMA), leveraging systematic review of databases and literature, with the most detailed data type of the individual patient, and quantitative modeling of the PK processes, including capturing heterogeneity of variance between studies. The methodology that should be used in IPDMA in the context of population PK analysis is summarized in this tutorial, highlighting areas of special attention compared to standard PK modeling, including hierarchical nested variability terms for interstudy variability, and handling between-assay differences in limits of quantification within a single analysis. This tutorial is intended for any pharmacological modeler who is interested in performing an integrated analysis of PK data across different studies in a systematic and thorough manner, to answer questions that transcend individual primary studies.

Novel Approach for the Approximation of Vitamin D3 Pharmacokinetics from In Vivo Absorption Studies

The changing environment and modified lifestyles have meant that many vitamins and minerals are deficient in a significant portion of the human population. Therefore, supplementation is a viable nutritional approach, which helps to maintain health and well-being. The supplementation efficiency of a highly hydrophobic compound such as cholecalciferol (logP > 7) depends predominantly on the formulation. To overcome difficulties associated with the evaluation of pharmacokinetics of cholecalciferol, a method based on the short time absorption data in the clinical study and physiologically based mathematical modeling is proposed. The method was used to compare pharmacokinetics of liposomal and oily formulations of vitamin D3. The liposomal formulation was more effective in elevating calcidiol concentration in serum. The determined AUC value for liposomal vitamin D3 formulation was four times bigger than that for the oily formulation.

Physiologically Based Pharmacokinetic Modeling of Vitamin D3 and Metabolites in Vitamin D-Insufficient Patients

A physiologically based pharmacokinetic (PBPK) model of vitamin D3 and metabolites [25(OH)D3, 1,25(OH)2D3, and 24,25(OH)2D3] is presented. In this study, patients with 25(OH)D3 plasma concentrations below 30 ng/ml were studied after a single dose of 5000 I.U. (125 µg) cholecalciferol, provided with 5000 I.U. daily cholecalciferol supplementation until vitamin D replete [25(OH)D3 plasma concentrations above 30 ng/ml], and had serial plasma samples were collected at each phase for 14 days. Total concentrations of vitamin D3 and metabolites were measured by ultra-high performance liquid chromatography tandem mass spectrometry. A nine-compartment PBPK model was built using MATLAB to represent the triphasic study nature (insufficient, replenishing, and sufficient). The stimulatory and inhibitory effect of 1,25(OH)2D3 were incorporated by fold-changes in the primary metabolic enzymes CYP27B1 and CYP24A1, respectively. Incorporation of dynamic adipose partition coefficients for vitamin D3 and 25(OH)D3 and variable enzymatic reactions aided in model fitting. Measures of model predictions agreed well with data from metabolites, with 97%, 88%, and 98% of the data for 25(OH)D3, 24,25(OH)2D3, and 1,25(OH)2D3, respectively, within twofold of unity (fold error values between 0.5 and 2.0). Bootstrapping was performed and optimized parameters were reported with 95% confidence intervals. This PBPK model could be a useful tool for understanding the connections between vitamin D and its metabolites under a variety of clinical situations. SIGNIFICANCE STATEMENT: This study developed a physiologically based pharmacokinetic (PBPK) model of vitamin D3 and metabolites for patients moving from an insufficient to a repleted state over a period of 16 weeks.

Applications of Model-Based Meta-Analysis in Drug Development

Model-based meta-analysis (MBMA) is a quantitative approach that leverages published summary data along with internal data and can be applied to inform key drug development decisions, including the benefit-risk assessment of a treatment under investigation. These risk-benefit assessments may involve determining an optimal dose compared against historic external comparators of a particular disease indication. MBMA can provide a flexible framework for interpreting aggregated data from historic reference studies and therefore should be a standard tool for the model-informed drug development (MIDD) framework.In addition to pairwise and network meta-analyses, MBMA provides further contributions in the quantitative approaches with its ability to incorporate longitudinal data and the pharmacologic concept of dose-response relationship, as well as to combine individual- and summary-level data and routinely incorporate covariates in the analysis.A common application of MBMA is the selection of optimal dose and dosing regimen of the internal investigational molecule to evaluate external benchmarking and to support comparator selection. Two case studies provided examples in applications of MBMA in biologics (durvalumab + tremelimumab for safety) and small molecule (fenebrutinib for efficacy) to support drug development decision-making in two different but well-studied disease areas, i.e., oncology and rheumatoid arthritis, respectively.Important to the future directions of MBMA include additional recognition and engagement from drug development stakeholders for the MBMA approach, stronger collaboration between pharmacometrics and statistics, expanded data access, and the use of machine learning for database building. Timely, cost-effective, and successful application of MBMA should be part of providing an integrated view of MIDD.

Vitamin D in the time of the coronavirus (COVID-19) pandemic - a clinical review from a public health and public mental health perspective

Individuals with serious mental disorders (SMD) may have a higher risk of vitamin D (VIT-D) deficiency. They also experience higher mortality because of coronavirus disease 2019 (COVID-19) infection. Therefore, we have conducted a comprehensive review to examine the significance of VIT-D for public health and public mental health during the ongoing COVID-19 pandemic. This review had three specific aims, from a global perspective to (a) create a profile of VIT-D and review the epidemiology of VIT-D deficiency, (b) explore VIT-D deficiency as risk factor for SMD and COVID-19 infections and (c) examine the effectiveness of VIT-D supplementation for both conditions. We found that, in terms of SMD, the evidence from laboratory and observational studies points towards some association between VIT-D deficiency and depression or schizophrenia. Mendelian randomisation studies, however, suggest no, or reverse, causality. The evidence from intervention studies is conflicting. Concerning COVID-19 infection, on proof of principle, VIT-D could provide a plausible defence against the infection itself and against an adverse clinical course. But data from observational studies and the first preliminary intervention studies remain conflicting, with stronger evidence that VIT-D may mitigate the clinical course of COVID-19 infection rather than the risk of infection in the first place. From a public health and public mental health point of view, based on the currently limited knowledge, for individuals with SMD, the benefits of VIT-D optimisation through supplementation seem to outweigh the risks. VIT-D supplementation, however, should not substitute for vaccination or medical care for COVID-19 infection.

Vitamin D Metabolism and Guidelines for Vitamin D Supplementation

Vitamin D is essential for bone health and is known to be involved in immunomodulation and cell proliferation. Vitamin D status remains a significant health issue worldwide. However, there has been no clear consensus on vitamin D deficiency and its measurement in serum, and clinical practice of vitamin D deficiency treatment remains inconsistent. The major circulating metabolite of vitamin D, 25-hydroxyvitamin D (25(OH)D), is widely used as a biomarker of vitamin D status. Other metabolic pathways are recognised as important to vitamin D function and measurement of other metabolites may become important in the future. The utility of free 25(OH)D rather than total 25(OH)D needs further assessment. Data used to estimate the vitamin D intake required to achieve a serum 25(OH)D concentration were drawn from individual studies which reported dose-response data. The studies differ in their choice of subjects, dose of vitamin D, frequency of dosing regimen and methods used for the measurement of 25(OH)D concentration. Baseline 25(OH)D, body mass index, ethnicity, type of vitamin D (D₂ or D₃) and genetics affect the response of serum 25(OH)D to vitamin D supplementation. The diversity of opinions that exist on this topic are reflected in the guidelines. Government and scientific societies have published their recommendations for vitamin D intake which vary from 400-1000 IU/d (10-25 μg/d) for an average adult. It was not possible to establish a range of serum 25(OH)D concentrations associated with selected non-musculoskeletal health outcomes. To recommend treatment targets, future studies need to be on infants, children, pregnant and lactating women.