PURPOSE: To investigate the effect of dose staggering on metabolic drug-drug interactions (MDDI). METHODS: Using Matlab, anatomical, physiological and biochemical data relating to human pharmacokinetics were integrated to create a representative virtual healthy subject relevant to in vivo studies. The effects of dose staggering on AUC and C(max) were investigated under various scenarios with respect to pharmacokinetic characteristics of the inhibitor and substrate drugs (e.g. hepatic extraction ratio). Specific cases were also simulated where MDDI had been studied experimentally for combinations of drugs (budesonide and ketoconazole; triazolam and itraconazole). RESULTS: The decrease in the magnitude of the inhibitory effect of the 'perpetrator' drug (inhibitor) on the 'victim' drug (substrate) as a result of 'dose staggering' was greater when the 'perpetrator' was given after the 'victim'. There was reasonable agreement between the predicted extent of the interactions and the observed in vivo data (mean prediction errors of 25 and -14% for AUC and C(max) values, respectively (n=7)). The impact of dose staggering was minimal during continuous dosage of inhibitors with long elimination half-lives (e.g. itraconazole, >20 h). CONCLUSIONS: Clinical trial simulations using physiological information may provide useful guidelines for optimal dose staggering when poly-pharmacy is inevitable.
PURPOSE: To investigate the effect of dose staggering on metabolic drug-drug interactions (MDDI). METHODS: Using Matlab, anatomical, physiological and biochemical data relating to human pharmacokinetics were integrated to create a representative virtual healthy subject relevant to in vivo studies. The effects of dose staggering on AUC and C(max) were investigated under various scenarios with respect to pharmacokinetic characteristics of the inhibitor and substrate drugs (e.g. hepatic extraction ratio). Specific cases were also simulated where MDDI had been studied experimentally for combinations of drugs (budesonide and ketoconazole; triazolam and itraconazole). RESULTS: The decrease in the magnitude of the inhibitory effect of the 'perpetrator' drug (inhibitor) on the 'victim' drug (substrate) as a result of 'dose staggering' was greater when the 'perpetrator' was given after the 'victim'. There was reasonable agreement between the predicted extent of the interactions and the observed in vivo data (mean prediction errors of 25 and -14% for AUC and C(max) values, respectively (n=7)). The impact of dose staggering was minimal during continuous dosage of inhibitors with long elimination half-lives (e.g. itraconazole, >20 h). CONCLUSIONS: Clinical trial simulations using physiological information may provide useful guidelines for optimal dose staggering when poly-pharmacy is inevitable.
Authors: Jihao Zhou; Zhaohui Qin; Sara K Quinney; Seongho Kim; Zhiping Wang; Menggang Yu; Jenny Y Chien; Aroonrut Lucksiri; Stephen D Hall; Lang Li Journal: J Pharmacokinet Pharmacodyn Date: 2009-01-21 Impact factor: 2.745
Authors: Janneke M Brussee; Huixin Yu; Elke H J Krekels; Semra Palić; Margreke J E Brill; Jeffrey S Barrett; Amin Rostami-Hodjegan; Saskia N de Wildt; Catherijne A J Knibbe Journal: Pharm Res Date: 2018-07-30 Impact factor: 4.200
Authors: M J E Brill; P A J Välitalo; A S Darwich; B van Ramshorst; H P A van Dongen; A Rostami-Hodjegan; M Danhof; C A J Knibbe Journal: CPT Pharmacometrics Syst Pharmacol Date: 2015-12-18
Authors: Janneke M Brussee; Huixin Yu; Elke H J Krekels; Berend de Roos; Margreke J E Brill; Johannes N van den Anker; Amin Rostami-Hodjegan; Saskia N de Wildt; Catherijne A J Knibbe Journal: CPT Pharmacometrics Syst Pharmacol Date: 2018-05-10