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Population pharmacokinetics of sifalimumab, an investigational anti-interferon-α monoclonal antibody, in systemic lupus erythematosus.

Narwal R, Roskos LK, Robbie GJ - Clin Pharmacokinet (2013)

Bottom Line: Population pharmacokinetic modeling of sifalimumab was performed using a non-linear mixed effects modeling approach with NONMEM VII software.Although the above-mentioned covariates were statistically significant, they did not explain variability in pharmacokinetic parameters to any relevant extent (<7 %).Although the population pharmacokinetic analysis identified some statistically significant covariates, they explained <7 % between-subject variability in pharmacokinetic parameters indicating that these covariates are not clinically relevant.

View Article: PubMed Central - PubMed

Affiliation: Clinical Pharmacology and DMPK (CPD), MedImmune, LLC One MedImmune Way, Gaithersburg, MD, 20878, USA, narwalr@medimmune.com.

ABSTRACT

Background and objectives: Sifalimumab is a fully human immunoglobulin G1κ monoclonal antibody that binds to and neutralizes a majority of the subtypes of human interferon-α. Sifalimumab is being evaluated as a treatment for systemic lupus erythematosus (SLE). The primary objectives of this analysis were (a) to develop a population pharmacokinetic model for sifalimumab in SLE; (b) to identify and quantitate the impact of patient/disease characteristics on pharmacokinetic variability; and (c) to evaluate fixed versus body weight (WT)-based dosing regimens.

Methods: Sifalimumab serum concentration-time data were collected from a phase Ib study (MI-CP152) designed to evaluate the safety and tolerability of sifalimumab in adult patients with SLE. Sifalimumab was administered every 14 days as a 30- to 60-minute intravenous infusion with escalating doses of 0.3, 1.0, 3.0, and 10 mg/kg and serum concentrations were collected over 350 days. A total of 120 patients provided evaluable pharmacokinetic data with a total of 2,370 serum concentrations. Sifalimumab serum concentrations were determined using a validated colorimetric enzyme-linked immunosorbent assay (ELISA) with a lower limit of quantitation of 1.25 μg/mL. Population pharmacokinetic modeling of sifalimumab was performed using a non-linear mixed effects modeling approach with NONMEM VII software. Impact of patient demographics, clinical indices, and biomarkers on pharmacokinetic parameters were explored using a stepwise forward selection and backward elimination approach. The appropriateness of the final model was tested using visual predictive check (VPC). The impact of body WT-based and fixed dosing of sifalimumab was evaluated using a simulation approach. The final population model was utilized for phase IIb dosing projections.

Results: Sifalimumab pharmacokinetics were best described using a two-compartment linear model with first order elimination. Following intravenous dosing, the typical clearance (CL) and central volume of distribution (V 1) were estimated to be 176 mL/day and 2.9 L, respectively. The estimates (coefficient of variation) of between-subject variability for CL and V 1 were 28 and 31 %, respectively. Patient baseline body WT, interferon gene signature from 21 genes, steroid use, and sifalimumab dose were identified as significant covariates for CL, whereas only baseline body WT was a significant covariate for V 1 and peripheral volume of distribution (V 2). Although the above-mentioned covariates were statistically significant, they did not explain variability in pharmacokinetic parameters to any relevant extent (<7 %). Thus, no dosing adjustments are necessary. VPC confirmed good predictability of the final population pharmacokinetic model. Simulation results demonstrate that both fixed and body WT-based dosing regimens yield similar median steady state concentrations and overall variability. Fixed sifalimumab doses of 200, 600, and 1,200 mg monthly (with a loading dose at Day 14) were selected for a phase IIb clinical trial.

Conclusion: A two-compartment population pharmacokinetic model adequately described sifalimumab pharmacokinetics. The estimated typical pharmacokinetic parameters were similar to other monoclonal antibodies without target mediated elimination. Although the population pharmacokinetic analysis identified some statistically significant covariates, they explained <7 % between-subject variability in pharmacokinetic parameters indicating that these covariates are not clinically relevant. The population pharmacokinetic analysis also demonstrated the feasibility of switching to fixed doses in phase IIb clinical trials of sifalimumab.

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Final model goodness-of-fit plots for sifalimumab serum concentrations. The thin black line (diagonal and horizontal) and thick black line represent line of unity and loess fit, respectively
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Fig1: Final model goodness-of-fit plots for sifalimumab serum concentrations. The thin black line (diagonal and horizontal) and thick black line represent line of unity and loess fit, respectively

Mentions: The final population pharmacokinetic parameters are presented in Table 2. The estimated values of CL, V1, V2, and Q for a typical/standard patient were about 176 mL/day, 2.9 L, 2.12 L and 171 mL/day, respectively. The estimates (coefficient of variation) of between-subject variability associated with CL, V1, V2, and Q were 28, 31, 58, and 71 %, respectively. The η-shrinkage was estimated to be 4 % (CL), 12 % (V1), 16 % (V2), and 39 % (Q). The ε-shrinkage was 6 %. The condition number was 382. All pharmacokinetic parameters were estimated with good precision, as reflected by relative standard errors. The performance of the final model fit is represented by goodness-of-fit plots as shown in Fig. 1. Figure 1a, b show good agreement between observed and model predicted [population predicted (PRED)/individual predicted (IPRED)] sifalimumab serum concentrations. The plots of conditional weighted residual (CWRES) versus the PRED concentrations (Fig. 1c) or time (Fig. 1d) do not show any obvious pattern.Table 2


Population pharmacokinetics of sifalimumab, an investigational anti-interferon-α monoclonal antibody, in systemic lupus erythematosus.

Narwal R, Roskos LK, Robbie GJ - Clin Pharmacokinet (2013)

Final model goodness-of-fit plots for sifalimumab serum concentrations. The thin black line (diagonal and horizontal) and thick black line represent line of unity and loess fit, respectively
© Copyright Policy - OpenAccess
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3824374&req=5

Fig1: Final model goodness-of-fit plots for sifalimumab serum concentrations. The thin black line (diagonal and horizontal) and thick black line represent line of unity and loess fit, respectively
Mentions: The final population pharmacokinetic parameters are presented in Table 2. The estimated values of CL, V1, V2, and Q for a typical/standard patient were about 176 mL/day, 2.9 L, 2.12 L and 171 mL/day, respectively. The estimates (coefficient of variation) of between-subject variability associated with CL, V1, V2, and Q were 28, 31, 58, and 71 %, respectively. The η-shrinkage was estimated to be 4 % (CL), 12 % (V1), 16 % (V2), and 39 % (Q). The ε-shrinkage was 6 %. The condition number was 382. All pharmacokinetic parameters were estimated with good precision, as reflected by relative standard errors. The performance of the final model fit is represented by goodness-of-fit plots as shown in Fig. 1. Figure 1a, b show good agreement between observed and model predicted [population predicted (PRED)/individual predicted (IPRED)] sifalimumab serum concentrations. The plots of conditional weighted residual (CWRES) versus the PRED concentrations (Fig. 1c) or time (Fig. 1d) do not show any obvious pattern.Table 2

Bottom Line: Population pharmacokinetic modeling of sifalimumab was performed using a non-linear mixed effects modeling approach with NONMEM VII software.Although the above-mentioned covariates were statistically significant, they did not explain variability in pharmacokinetic parameters to any relevant extent (<7 %).Although the population pharmacokinetic analysis identified some statistically significant covariates, they explained <7 % between-subject variability in pharmacokinetic parameters indicating that these covariates are not clinically relevant.

View Article: PubMed Central - PubMed

Affiliation: Clinical Pharmacology and DMPK (CPD), MedImmune, LLC One MedImmune Way, Gaithersburg, MD, 20878, USA, narwalr@medimmune.com.

ABSTRACT

Background and objectives: Sifalimumab is a fully human immunoglobulin G1κ monoclonal antibody that binds to and neutralizes a majority of the subtypes of human interferon-α. Sifalimumab is being evaluated as a treatment for systemic lupus erythematosus (SLE). The primary objectives of this analysis were (a) to develop a population pharmacokinetic model for sifalimumab in SLE; (b) to identify and quantitate the impact of patient/disease characteristics on pharmacokinetic variability; and (c) to evaluate fixed versus body weight (WT)-based dosing regimens.

Methods: Sifalimumab serum concentration-time data were collected from a phase Ib study (MI-CP152) designed to evaluate the safety and tolerability of sifalimumab in adult patients with SLE. Sifalimumab was administered every 14 days as a 30- to 60-minute intravenous infusion with escalating doses of 0.3, 1.0, 3.0, and 10 mg/kg and serum concentrations were collected over 350 days. A total of 120 patients provided evaluable pharmacokinetic data with a total of 2,370 serum concentrations. Sifalimumab serum concentrations were determined using a validated colorimetric enzyme-linked immunosorbent assay (ELISA) with a lower limit of quantitation of 1.25 μg/mL. Population pharmacokinetic modeling of sifalimumab was performed using a non-linear mixed effects modeling approach with NONMEM VII software. Impact of patient demographics, clinical indices, and biomarkers on pharmacokinetic parameters were explored using a stepwise forward selection and backward elimination approach. The appropriateness of the final model was tested using visual predictive check (VPC). The impact of body WT-based and fixed dosing of sifalimumab was evaluated using a simulation approach. The final population model was utilized for phase IIb dosing projections.

Results: Sifalimumab pharmacokinetics were best described using a two-compartment linear model with first order elimination. Following intravenous dosing, the typical clearance (CL) and central volume of distribution (V 1) were estimated to be 176 mL/day and 2.9 L, respectively. The estimates (coefficient of variation) of between-subject variability for CL and V 1 were 28 and 31 %, respectively. Patient baseline body WT, interferon gene signature from 21 genes, steroid use, and sifalimumab dose were identified as significant covariates for CL, whereas only baseline body WT was a significant covariate for V 1 and peripheral volume of distribution (V 2). Although the above-mentioned covariates were statistically significant, they did not explain variability in pharmacokinetic parameters to any relevant extent (<7 %). Thus, no dosing adjustments are necessary. VPC confirmed good predictability of the final population pharmacokinetic model. Simulation results demonstrate that both fixed and body WT-based dosing regimens yield similar median steady state concentrations and overall variability. Fixed sifalimumab doses of 200, 600, and 1,200 mg monthly (with a loading dose at Day 14) were selected for a phase IIb clinical trial.

Conclusion: A two-compartment population pharmacokinetic model adequately described sifalimumab pharmacokinetics. The estimated typical pharmacokinetic parameters were similar to other monoclonal antibodies without target mediated elimination. Although the population pharmacokinetic analysis identified some statistically significant covariates, they explained <7 % between-subject variability in pharmacokinetic parameters indicating that these covariates are not clinically relevant. The population pharmacokinetic analysis also demonstrated the feasibility of switching to fixed doses in phase IIb clinical trials of sifalimumab.

Show MeSH
Related in: MedlinePlus