A mechanistic modelling approach for the determination of the mechanisms of inhibition by cyclosporine on the uptake and metabolism of atorvastatin in rat hepatocytes using a high throughput uptake method

Determine the inhibition mechanism through which cyclosporine inhibits the uptake and metabolism of atorvastatin in fresh rat hepatocytes using mechanistic models applied to data generated using a high throughput oil spin method. Atorvastatin was incubated in fresh rat hepatocytes (0.05–150 nmol/ml) with or without 20 min pre-incubation with 10 nmol/ml cyclosporine and sampled over 0.25–60 min using a high throughput oil spin method. Micro-rate constant and macro-rate constant mechanistic models were ranked based on goodness of fit values. The best fitting model to the data was a micro-rate constant mechanistic model including non-competitive inhibition of uptake and competitive inhibition of metabolism by cyclosporine (Model 2). The association rate constant for atorvastatin was 150-fold greater than the dissociation rate constant and 10-fold greater than the translocation into the cell. The association and dissociation rate constants for cyclosporine were 7-fold smaller and 10-fold greater, respectively, than atorvastatin. The simulated atorvastatin-transporter-cyclosporine complex derived using the micro-rate constant parameter estimates increased in line with the incubation concentration of atorvastatin. The increased amount of data generated with the high throughput oil spin method, combined with a micro-rate constant mechanistic model helps to explain the inhibition of uptake by cyclosporine following pre-incubation

Prediction of human renal clearance from preclinical species for a diverse set of drugs that exhibit both active secretion and net re- absorption

Number of words in abstract: 184 Number of words in introduction: 552 Number of words in discussion: 822 Abbreviations: ADME, absorption, distribution, metabolism and excretion; afe, average fold error; CLr, renal clearance; CLp, plasmatic clearance; fu, unbound plasma fraction; GFR, glomerular filtration rate; KBF, kidney blood flow; NSAID, non-steroidal anti-inflammatory drug; OAT, organic anion transporter; OATP, organic anion transport protein; PPB, plasma protein binding; rmse, root mean square error. DMD # 37267 Abstract Identifying any extra-hepatic excretion phenomenon in preclinical species is crucial for an accurate prediction of the pharmacokinetics in man. This is particularly the case for drugs with a small volume of distribution, as they require an especially low total clearance in order to be suitable for a once-a-day dosing regimen in man. In this study, three animal scaling techniques were applied for the prediction of the human renal clearance of 36 diverse drugs that show active secretion or net re-absorption

Use of mechanistic modeling to assess interindividual variability and interspecies differences in active uptake in human and rat hepatocytes

Interindividual variability in activity of uptake transporters is evident in vivo, yet limited data exist in vitro, confounding in vitro-in vivo extrapolation. The uptake kinetics of seven organic anion-transporting polypeptide substrates was investigated over a concentration range in plated cryopreserved human hepatocytes. Active uptake clearance (CL(active, u)), bidirectional passive diffusion (P(diff)), intracellular binding, and metabolism were estimated for bosentan, pitavastatin, pravastatin, repaglinide, rosuvastatin, telmisartan, and valsartan in HU4122 donor using a mechanistic two-compartment model in Matlab. Full uptake kinetics of rosuvastatin and repaglinide were also characterized in two additional donors, whereas for the remaining drugs CL(active, u) was estimated at a single concentration. The unbound affinity constant (K(m, u)) and P(diff) values were consistent across donors, whereas V(max) was on average up to 2.8-fold greater in donor HU4122. Consistency in K(m, u) values allowed extrapolation of single concentration uptake activity data and assessment of interindividual variability in CL(active) across donors. The maximal contribution of active transport to total uptake differed among donors, for example, 85 to 96% and 68 to 87% for rosuvastatin and repaglinide, respectively; however, in all cases the active process was the major contributor. In vitro-in vivo extrapolation indicated a general underprediction of hepatic intrinsic clearance, an average empirical scaling factor of 17.1 was estimated on the basis of seven drugs investigated in three hepatocyte donors, and donor-specific differences in empirical factors are discussed. Uptake K(m, u) and CL(active, u) were on average 4.3- and 7.1-fold lower in human hepatocytes compared with our previously published rat data. A strategy for the use of rat uptake data to facilitate the experimental design in human hepatocytes is discussed

Simultaneous assessment of uptake and metabolism in rat hepatocytes: A comprehensive mechanistic model

Kinetic parameters describing hepatic uptake in hepatocytes are frequently estimated without appropriate incorporation of bidirectional passive diffusion, intracellular binding, and metabolism. A mechanistic two-compartment model was developed to describe all of the processes occurring during the in vitro uptake experiments performed in freshly isolated rat hepatocytes plated for 2 h. Uptake of rosuvastatin, pravastatin, pitavastatin, valsartan, bosentan, telmisartan, and repaglinide was investigated over a 0.1 to 300 μM concentration range at 37°C for 2 or 45–90 min; nonspecific binding was taken into account. All concentration-time points were analyzed simultaneously by using a mechanistic two-compartment model describing uptake kinetics [unbound affinity constant (K(m,u)), maximum uptake rate (V(max)), unbound active uptake clearance (CL(active,u))], passive diffusion [unbound passive diffusion clearance (P(diff,u))], and intracellular binding [intracellular unbound fraction (fu(cell))]. When required (telmisartan and repaglinide), the model was extended to account for the metabolism [unbound metabolic clearance (CL(met,u))]. The CL(active,u) ranged 8-fold, reflecting a 11-fold range in uptake K(m,u), with telmisartan and valsartan showing the highest affinity for uptake transporters (K(m,u) <10 μM). Both P(diff,u) and fu(cell) span over two orders of magnitude and reflected the lipophilicity of the drugs in the dataset. An extended incubation time allowed steady state to be reached between media and intracellular compartment concentrations and reduced the error in certain parameter estimates observed with shorter incubation times. Active transport accounted for >70% of total uptake for all drugs investigated and was 4- and 112-fold greater than CL(met,u) for telmisartan and repaglinide, respectively. Modeling of uptake kinetics in conjunction with metabolism improved the precision of the uptake parameter estimates for repaglinide and telmisartan. Recommendations are made for uptake experimental design and modeling strategies