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Physiology-based IVIVE predictions of tramadol from in vitro metabolism data

(2015) PHARMACEUTICAL RESEARCH. 32(1). p.260-274
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Abstract
To predict the tramadol in vivo pharmacokinetics in adults by using in vitro metabolism data and an in vitro-in vivo extrapolation (IVIVE)-linked physiologically-based pharmacokinetic (PBPK) modeling and simulation approach (SimcypA (R)). Tramadol metabolism data was gathered using metabolite formation in human liver microsomes (HLM) and recombinant enzyme systems (rCYP). Hepatic intrinsic clearance (CLint(H)) was (i) estimated from HLM corrected for specific CYP450 contributions from a chemical inhibition assay (model 1); (ii) obtained in rCYP and corrected for specific CYP450 contributions by study-specific intersystem extrapolation factor (ISEF) values (model 2); and (iii) scaled back from in vivo observed clearance values (model 3). The model-predicted clearances of these three models were evaluated against observed clearance values in terms of relative difference of their geometric means, the fold difference of their coefficients of variation, and relative CYP2D6 contribution. Model 1 underpredicted, while model 2 overpredicted the total tramadol clearance by -27 and +22%, respectively. The CYP2D6 contribution was underestimated in both models 1 and 2. Also, the variability on the clearance of those models was slightly underpredicted. Additionally, blood-to-plasma ratio and hepatic uptake factor were identified as most influential factors in the prediction of the hepatic clearance using a sensitivity analysis. IVIVE-PBPK proved to be a useful tool in combining tramadol's low turnover in vitro metabolism data with system-specific physiological information to come up with reliable PK predictions in adults.
Keywords
ENZYME, COMMUNICATION, FORMULATIONS, BIOAVAILABILITY, CLEARANCE, PHARMACOKINETICS, DRUG DEVELOPMENT, ISOLATED HEPATOCYTES, VIVO EXTRAPOLATION, HUMAN LIVER-MICROSOMES, PBPK, IVIVE, clearance mechanisms, in vitro metabolism

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Citation

Please use this url to cite or link to this publication:

Chicago
T’jollyn, Huybrecht, Jan Snoeys, Pieter Colin, Jan Van Bocxlaer, Pieter Annaert, Filip Cuyckens, An Vermeulen, et al. 2015. “Physiology-based IVIVE Predictions of Tramadol from in Vitro Metabolism Data.” Pharmaceutical Research 32 (1): 260–274.
APA
T’jollyn, H., Snoeys, J., Colin, P., Van Bocxlaer, J., Annaert, P., Cuyckens, F., Vermeulen, A., et al. (2015). Physiology-based IVIVE predictions of tramadol from in vitro metabolism data. PHARMACEUTICAL RESEARCH, 32(1), 260–274.
Vancouver
1.
T’jollyn H, Snoeys J, Colin P, Van Bocxlaer J, Annaert P, Cuyckens F, et al. Physiology-based IVIVE predictions of tramadol from in vitro metabolism data. PHARMACEUTICAL RESEARCH. 2015;32(1):260–74.
MLA
T’jollyn, Huybrecht et al. “Physiology-based IVIVE Predictions of Tramadol from in Vitro Metabolism Data.” PHARMACEUTICAL RESEARCH 32.1 (2015): 260–274. Print.
@article{6940188,
  abstract     = {To predict the tramadol in vivo pharmacokinetics in adults by using in vitro metabolism data and an in vitro-in vivo extrapolation (IVIVE)-linked physiologically-based pharmacokinetic (PBPK) modeling and simulation approach (SimcypA (R)). 
Tramadol metabolism data was gathered using metabolite formation in human liver microsomes (HLM) and recombinant enzyme systems (rCYP). Hepatic intrinsic clearance (CLint(H)) was (i) estimated from HLM corrected for specific CYP450 contributions from a chemical inhibition assay (model 1); (ii) obtained in rCYP and corrected for specific CYP450 contributions by study-specific intersystem extrapolation factor (ISEF) values (model 2); and (iii) scaled back from in vivo observed clearance values (model 3). The model-predicted clearances of these three models were evaluated against observed clearance values in terms of relative difference of their geometric means, the fold difference of their coefficients of variation, and relative CYP2D6 contribution. 
Model 1 underpredicted, while model 2 overpredicted the total tramadol clearance by -27 and +22%, respectively. The CYP2D6 contribution was underestimated in both models 1 and 2. Also, the variability on the clearance of those models was slightly underpredicted. Additionally, blood-to-plasma ratio and hepatic uptake factor were identified as most influential factors in the prediction of the hepatic clearance using a sensitivity analysis. 
IVIVE-PBPK proved to be a useful tool in combining tramadol's low turnover in vitro metabolism data with system-specific physiological information to come up with reliable PK predictions in adults.},
  author       = {T'jollyn, Huybrecht and Snoeys, Jan and Colin, Pieter and Van Bocxlaer, Jan and Annaert, Pieter and Cuyckens, Filip and Vermeulen, An and Van Peer, Achiel and Allegaert, Karel and Mannens, Geert and Boussery, Koen},
  issn         = {0724-8741},
  journal      = {PHARMACEUTICAL RESEARCH},
  keywords     = {ENZYME,COMMUNICATION,FORMULATIONS,BIOAVAILABILITY,CLEARANCE,PHARMACOKINETICS,DRUG DEVELOPMENT,ISOLATED HEPATOCYTES,VIVO EXTRAPOLATION,HUMAN LIVER-MICROSOMES,PBPK,IVIVE,clearance mechanisms,in vitro metabolism},
  language     = {eng},
  number       = {1},
  pages        = {260--274},
  title        = {Physiology-based IVIVE predictions of tramadol from in vitro metabolism data},
  url          = {http://dx.doi.org/10.1007/s11095-014-1460-x},
  volume       = {32},
  year         = {2015},
}

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