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

Association of Vitamin D (D3 & D2) and its 25OHD metabolite (25OHD3 & 25OHD2) exposures with various diseases is an active research area. D3 and D2 dose-equivalency and each form's ability to raise 25OHD concentrations are not well-defined. The current work describes a population pharmacokinetic (PK) model for D2 and 25OHD2 and the use of a previously developed D3-25OHD3 PK model [1] for comparing D3 and D2-related exposures. Public-source D2 and 25OHD2 PK data in healthy or osteoporotic populations, including 17 studies representing 278 individuals (15 individual-level and 18 arm-level units), were selected using search criteria in PUBMED. Data included oral, single and multiple D2 doses (400-100,000 IU/d). Nonlinear mixed effects models were developed simultaneously for D2 and 25OHD2 PK (NONMEM v7.2) by considering 1- and 2-compartment models with linear or nonlinear clearance. Unit-level random effects and residual errors were weighted by arm sample size. Model simulations compared 25OHD exposures, following repeated D2 and D3 oral administration across typical dosing and baseline ranges. D2 parent and metabolite were each described by 2-compartment models with numerous parameter estimates shared with the D3-25OHD3 model [1]. Notably, parent D2 was eliminated (converted to 25OHD) through a first-order clearance whereas the previously published D3 model [1] included a saturable non-linear clearance. Similar to 25OHD3 PK model results [1], 25OHD2 was eliminated by a first-order clearance, which was almost twice as fast as the former. Simulations at lower baselines, following lower equivalent doses, indicated that D3 was more effective than D2 at raising 25OHD concentrations. Due to saturation of D3 clearance, however, at higher doses or baselines, the probability of D2 surpassing D3's ability to raise 25OHD concentrations increased substantially. Since 25OHD concentrations generally surpassed 75 nmol/L at these higher baselines by 3 months, there would be no expected clinical difference in the two forms.

Model-based meta-analysis for development of a population-pharmacokinetic (PPK) model for Vitamin D3 and its 25OHD3 metabolite using both individual and arm-level data.

Clinical studies investigating relationships between D3 and 25OHD3 vary in dosing regimen, assays, demographics, and control of exogenous D3. This leads to uncertain and conflicting exposure-related associations with D3 and 25OHD3. To elucidate this parent-metabolite system, a PPK model was developed to predict mean D3 and 25OHD3 exposure from varied doses and administration routes. Sources of exposure variability related to metabolite baseline, weight, and assay type were explored. Specific search criteria were used in PUBMED to identify public source PK data pertaining to D3 and 25OHD3 in healthy or osteoporotic populations. Overall 57 studies representing 5395 individuals were selected, including 25 individual-level profiles and treatment-arm data. IV, oral, single and multiple dose data were used, with D3 and 25OHD3 dosing. A nonlinear mixed effects model was developed to simultaneously model PK dispositions of D3 and 25OHD3 (NONMEM v7.2), which were described by 2-compartment models with nonlinear and linear clearances, respectively. Proportional and additive assay variances were included on the 25OHD3 prediction. Unit-level random effects were weighted by treatment-arm size. D3 model estimates, relative to bioavailability were: maximum rate of metabolism ([Formula: see text], 1.62 nmol/h), Michaelis-Menten constant ([Formula: see text], 6.39 nmol/L), central volume of distribution ([Formula: see text], 15.5 L), intercompartmental clearance ([Formula: see text], 0.185 L/h), peripheral volume of distribution ([Formula: see text], 2333 L/h), and baseline concentration ([Formula: see text], 3.75 nmol/L). For 25OHD3 ([Formula: see text] = metabolite): [Formula: see text] = 0.0153 L/h, [Formula: see text] = 4.35 L, [Formula: see text] = 6.87 L, [Formula: see text] = 0.0507 L/h. Simulations of 25OHD3 concentration indicated an inverse relationship between 25OHD3 baseline and response, as well as a less than proportional 25OHD3 response. Estimation of assay bias parameters suggested that HPLC-MS and RIA produced similar measurement results, whereas CPBA and CHEMI are over-predictive of 25OHD3 concentration, relative to HPLC-MS.