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1 Department of Chemical and Biochemical Engineering, Technical University of Denmark 2 Computer Aided Process Engineering Center, Department of Chemical and Biochemical Engineering, Technical University of Denmark 3 University of Illinois at Chicago 4 Centre for oil and gas – DTU, Center, Technical University of Denmark 5 University of Illinois at Chicago
Unknown dose regimes are typically assessed on animals prior to clinical trials. Recent advances in the evaluation of new leads' efficacy have been achieved by pharmacokinetic modeling. Further improvements, including determination of the drug's mechanism of action and organism biodistribution, require an effective methodology for solving parameter estimation challenges. This article solves the problem of rigorously estimating unknown biochemical reaction and transport parameters from in vivo datasets and identifying whole-body physiologically based pharmacokinetic (PBPK) models.A rat blood circulation model was combined with biotransport, biochemical reactions and metabolism of the immunosuppressant Cyclosporin. We demonstrate the proposed methodology on a case study in Sprague-Dawley rats by bolus iv injections of 1.2, 6 and 30. mg/kg. Key pharmacokinetic parameters were determined, including renal and hepatic clearances, elimination half-life, and mass transfer coefficients, to establish drug biodistribution dynamics in all organs and tissues. This multi-scale model satisfies first principles and conservation of mass, species and momentum.Prediction of organ drug bioaccumulation as a function of cardiac output, physiology, pathology or administration route may be possible with the proposed PBPK framework. Successful application of our model-based drug development method may lead to more efficient preclinical trials, accelerated knowledge gain from animal experiments, and shortened time-to-market of new drugs. © 2013.
Computers and Chemical Engineering, 2013, Vol 54, p. 97-110
Animals; Biochemistry; Cardiovascular system; Conservation; Drug delivery; Parameter estimation; Pharmacokinetics; Tissue; Physiological models
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