Abstract
BackgroundDrug development considering individual varieties among patients becomes crucial to improve clinical development success rates and save healthcare costs. As a useful tool to predict individual phenomena and correlations among drug characteristics and individual varieties, recently, whole-body physiologically based pharmacokinetic (WB- PBPK) models are getting more attention. WB-PBPK models generally have a lot of drug-related parameters that need to be estimated, and the estimations are difficult because the observed data are limited. Furthermore, parameter estimation in WB-PBPK models may cause overfitting when applying to individual clinical data such as urine/feces drug excretion for each patient in which Cluster Newton Method (CNM) is applicable for parameter estimation. In order to solve this issue, we came up with the idea of constraint-based perturbation analysis of the CNM. The effectiveness of our approach is demonstrated in the case of irinotecan WB-PBPK model using common organ-specific tissue-plasma partition coefficients (Kp) among the patients as constraints in WB-PBPK parameter estimation.ResultsWe find strong correlations between age, renal clearance and liver functions in irinotecan WB-PBPK model with personalized physiological parameters by observing the distributions of optimized values of strong convergence drug-related parameters using constraint-based perturbation analysis on CNM. The constraint-based perturbation analysis consists of the following three steps: (1) Estimation of all drug-related parameters for each patient; the parameters include organ-specific Kp. (2) Fixing suitable values of Kp for each organ among all patients identically. (3) Re-estimation of all drug-related parameters other than Kp by using the fixed values of Kp as constraints of CNM.ConclusionsConstraint-based perturbation analysis could yield new findings when using CNM with appropriate constraints. This method is a new technique to find suitable values and important insights that are masked by CNM without constraints.
Highlights
Drug development considering individual varieties among patients becomes crucial to improve clinical development success rates and save healthcare costs
Constraint-based perturbation analysis could yield new findings when using Cluster Newton Method (CNM) with appropriate constraints. This method is a new technique to find suitable values and important insights that are masked by CNM without constraints
Estimations of suitable values of tissue-plasma partition coefficient (Kp) for irinotecan WB-physiologically-based pharmacokinetic (PBPK) regardless of individual varieties We estimated the individual varieties of some drugrelated parameters by using whole-body physiologically- based pharmacokinetic (WB-PBPK) model with personalized physiological parameters and individual
Summary
Drug development considering individual varieties among patients becomes crucial to improve clinical development success rates and save healthcare costs. WB-PBPK models generally have a lot of drugrelated parameters that need to be estimated, and the estimations are difficult because the observed data are limited. Parameter estimation in WB-PBPK models may cause overfitting when applying to individual clinical data such as urine/feces drug excretion for each patient in which Cluster Newton Method (CNM) is applicable for parameter estimation. Considering the healthcare costs and the burden on patients, improvements of clinical development success rates and methods for a cost-efficient drug development are urgently needed. Because efficacy or safety issues often make drug developments unsuccessful, individual optimized doses have the potential to help clinical development success [1]. The determination of individually optimized doses involves very high costs because clinical trials are generally needed
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