Table 4.

Sensitivity Analysis.

	ka = 4.5	ka = 3.09	ka = 0.375
Objective Function	10169	10169	10170
Parameter	Estimate (SE) [95% CI]
CLij=θ1 × SNPθ2 × (ageij/47) θ3 × (albij/4.1) θ4 × (hgbij/12.5) θ5
θ1	26.2 (0.7) [24.8, 27.6]	26.2 (0.7) [24.8, 27.6]	26.6 (0.7) [25.2, 28.1]
θ2	0.71 (0.05) [0.61, 0.81]	0.71 (0.05) [0.61, 0.81]	0.73 (0.05) [0.63, 0.83]
θ3	−0.26 (0.08) [−0.42, −0.1]	−0.26 (0.08) [−0.42, −0.10]	−0.26 (0.07) [−0.40, −0.12]
θ4	0.35 (0.12) [0.11, 0.59]	0.35 (0.12) [0.11, 0.59]	0.36 (0.12) [0.12, 0.60]
θ5	−0.29 (0.09) [−0.47, −0.11]	−0.29 (0.09) [−0.47, −0.11]	−0.30 (0.09) [−0.48, −0.12]
Vi= θ6
θ6	3726 (844) [2072, 5379]	3730 (788) [2185, 5275]	3633 (628) [2401, 4864]
ωCL (%CV)	40.8 (1.9) [37.1, 44.5]	40.8 (1.8) [37.2, 44.4]	41.2 (1.6) [38.0, 44.4]
ωV (%CV)	65.3 (22.2) [21.7, 108.9]	65.4 (21.4) [23.6, 107.3]	65.0 (6.4) [52.5, 77.5]
σprop (%CV)	31.8 (1.2) [29.4, 34.2]	31.8 (1.2) [29.4, 34.2]	31.8 (1.2) [29.4, 34.2]
σadd (ng/ml)	0.52 (0.38) [0, 1.26]	0.52 (0.38) [0, 1.26]	0.52 (0.37) [0, 1.25]

Pharmacokinetic (PK) parameter estimates for models assuming k_a to be 4.5, 3.09, 0.375 (left to right). Estimates are presented as mean (standard error) [Wald 95% confidence interval]. SNP is coded continuously as 1, 2, 3 for 0, 1, and 2 mutations, respectively. The age_ij, alb_ij, and hgb_ij represent covariates values for subject i at time j. CL and V are population PK parameters for clearance and volume of distribution in the base model. The ω _CL and ω _V are the between-subject variance components for clearance and volume of distribution, respectively, presented as %CV. The σ_prop and σ_add represent the proportional and additive residual errors in the combined residual error model, presented as %CV and the standard deviation, respectively. The θs denote model parameters as typically used in statistical models.