Population PK analysis of Sym004 and the influence of variations in base model structure on covariate model building
Janet R. Wade (1), Rik Schoemaker (1), Lene Alifrangis (2)
(1) Occams, The Netherlands, (2) Symphogen A/S, Denmark
Objectives: Sym004 is a mixture of two synergistic full-length anti-EGFR antibodies (futuximab & modotuximab) that bind to 2 separate non-overlapping epitopes and inhibit the sustained growth of cancer cells.
1. Develop a population (pop) PK model for Sym004 and evaluate the potential for covariates to explain the inter-individual variability (IIV) in the model.
2. Evaluate if the Sym004 covariate model depended on the presence/absence of correlations between the IIV parameters.
3. Evaluate if the Sym004 pop PK model could also describe the PK of the 2 constituent antibodies.
Methods: PK data were from 136 patients from 2 trials in advanced solid tumours, SCCHN and mCRC (Sym004-01 and -02). Sym004 (0.4-18 mg/kg) was dosed by IV infusion weekly or every 2nd week or as a 9 mg/kg loading dose followed by 6 mg/kg weekly. Modelling was done in NONMEM v7.3 (FOCEI). Covariate model building was performed by evaluating each covariate one by one and then building a full final model with all covariates whose point estimates were outside the arbitrary range of 0.8 to 1.25 and whose 90% confidence intervals did not overlap the null value [1]. Finally the structure of the base and final Sym004 Pop PK BLOCK(3) models were applied to each Sym004 constituent antibody.
Results: A 2-compartment model with linear and non-linear elimination and a priori inclusion of body weight on CL, VMAX, V1 and V2 was used. IIV was on CL, VMAX and V1. Correlations between the 3 IIV parameters were -0.277, 0.334 and 0.396. Residual variability comprised an additive plus proportional error model.
Covariate model building was performed with diagonal and BLOCK(3) omega structures. Covariates were tested on CL, VMAX, V1 and V2. Final Sym004 BLOCK(3) and diagonal models included 6 and 9 covariates, respectively, above the influence of weight.
Application of the base and final Sym004 pop PK BLOCK(3) models to Sym004 constituent antibodies found only minor differences in parameter values.
Conclusions: The final Sym004 pop PK covariate model structure depended upon the underlying statistical model structure despite low correlations between the IIV parameters [2]. Effort should be made to define when a covariate effect is clinically meaningless (no effect), clinically irrelevant (small effect) and clinically important (larger effect) during the planning of analyses.
The minor differences in the parameter estimates for the two Sym004 constituent antibodies for both base and final pop PK models supports analysing the combination, Sym004.
References:
[1] Gastonguay MR. Full Covariate Models as an Alternative to Methods Relying on Statistical Significance for Inferences about Covariate Effects: A Review of Methodology and 42 Case Studies. PAGE 20 (2011) Abstr 2229 [www.page-meeting.org/?abstract=2229].
[2] JR Wade, SL Beal and NC Sambol (1994). Interaction between the choice of structural, statistical and covariate models in population pharmacokinetic analysis. J. Pharmacokin Biopharm, 22, 165-177.
