Dong-Jun Bae (1), Sang-Yeob Kim (1,2), Sang Mun Bae (1), Ae-Kyung Hwang (3), Kwan Cheol Pak (4), SeokKyu Yoon (4), Hyeong-Seok Lim (4)
(1) ASAN Institute for Life Sciences, Asan Medical Center, Seoul, Republic of Korea, (2) Department of Convergence Medicine, University of Ulsan College of Medicine, Seoul, Republic of Korea, (3) Pharmacokinetic and Pharmacogenetic Laboratory, Clinical Research Center, Asan Medical Center, Seoul, Republic of Korea, (4) Department of Clinical Pharmacology and Therapeutics, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Republic of Korea
Objectives:
The PBPK approach is known to be superior to traditional allometric approach when it comes to predictability of human PK based on preclinical animal PK experiment[1].
The purposes of the present study were to measure the serial Herceptin concentrations within each mouse by optical imaging after intravenous administration of Herceptin (monoclonal antibody widely used to treat patients with HER-2 receptor positive breast cancer) and construct PBPK models for Herceptin. By doing so, we tried to show the potential utility of nonlinear mixed effect modeling (NONMEM) and optical imaging in pre-clinical PK evaluation.
Furthermore, we also tried to predict the Herceptin concentration changes over time in interstitial fluid of major organs using the PBPK, which could be combined with the models for exposure-biochemical signal network change relationships and ligand-receptor interaction model of Herceptin.
Methods:
PK study was conducted in 24 male Balb/c-nude mice, where serial PK blood samples (0.5, 2, 4, 6, 24 h after intravenous injection of fluorescence-labeled Herceptin) in each mouse were drawn, and the blood concentration was measured by IVIS spectrum optical imaging system.
At 24 h, heart, lung, liver, spleen, and kidney were extracted from mice, and the concentrations of them were measured by IVIS spectrum optical imaging system.
A whole body PBPK (WBPBPK) modeling analysis was constructed based on the known physiological values of mouse including volumes of major organs, blood / lymphatic flows through the organs, and tissue partition coefficients (tissue versus blood) were estimated using NONMEM (version 7.3) subroutine ADVAN13 using first order conditional estimation with INTERACTION method.
Using the WBPBPK model, clinical trial simulation was performed with 1,000 replicates, referencing the human physiological values from literature and a previous clinical trial, in which healthy male subjects received intravenous herceptin at 6 mg/kg over 1.5 hours.
Then the simulated PK data in human was compared with real observed data in the previous study.
Results:
A whole body PBPK model describing the herceptin concentration over time in blood and other major organs in mouse was successfully developed and predicted the concentrations in blood, lung, liver, spleen, kidney and heart well.
A common tissue clearance with its unexplained inter-subject variability was included in the final model, which was estimated to be 0.0118 ml/h. Fraction of lymphatic drainage contributing venous blood concentration of herceptin (FRL) was estimated to be 0.319. Kp for lung, liver, spleen, kidney, and heart relative to blood were 3.67, 3.56, 1.06, 1.20, and 0.769, respectively.
The predicted mean area under the concentration time curve (AUC), and maximal concentration (Cmax) were similar to those of observed in a previous clinical trial[2]. The ratios of simulated versus observed AUC and Cmax were 1.02 and 0.72, respectively.
Using the whole body PBPK model, the mean herceptin concentration over time, and AUC with their 95% prediction interval in various organs in human could be predicted.
Conclusions: We successfully built the WBPBPK models with high human predictability based on mouse experiment with serial PK blood sampling in each mouse by successful implementation of optical imaging. The current study provided the potential synergistic applications of WBPBPK and optical imaging in the prediction of human PK based on the preclinical data in the early stage of drug development process.
References:
[1] Rowland M, Peck C, Tucker G. Physiologically-based pharmacokinetics in drug development and regulatory science. Annu Rev Pharmacol Toxicol. 2011;51:45-73.
[2] Yang Z, Leon J, Martin M, Harder JW, Zhang R, et al. (2009) Pharmacokinetics and biodistribution of near-infrared fluorescence polymeric nanoparticles. Nanotechnology 20: 165101.
Reference: PAGE 27 (2018) Abstr 8617 [www.page-meeting.org/?abstract=8617]
Poster: Drug/Disease Modelling - Absorption & PBPK