Mechanism-based pharmacokinetic-pharmacodynamic modeling: biophase distribution, receptor theory, and dynamical systems analysis.
ABSTRACT Mechanism-based PK-PD models differ from conventional PK-PD models in that they contain specific expressions to characterize, in a quantitative manner, processes on the causal path between drug administration and effect. This includes target site distribution, target binding and activation, pharmacodynamic interactions, transduction, and homeostatic feedback mechanisms. As the final step, the effects on disease processes and disease progression are considered. Particularly through the incorporation of concepts from receptor theory and dynamical systems analysis, important progress has been made in the field of mechanism-based PK-PD modeling. This has yielded models with much-improved properties for extrapolation and prediction. These models constitute a theoretical basis for rational drug discovery and development.
Article: Antitumor activity of targeted and cytotoxic agents in murine subcutaneous tumor models correlates with clinical response.[show abstract] [hide abstract]
ABSTRACT: Immunodeficient mice transplanted with subcutaneous tumors (xenograft or allograft) are widely used as a model of preclinical activity for the discovery and development of anticancer drug candidates. Despite their widespread use, there is a widely held view that these models provide minimal predictive value for discerning clinically active versus inactive agents. To improve the predictive nature of these models, we have carried out a retrospective population pharmacokinetic-pharmacodynamic (PK-PD) analysis of relevant xenograft/allograft efficacy data for eight agents (molecularly targeted and cytotoxic) with known clinical outcome. PK-PD modeling was carried out to first characterize the relationship between drug concentration and antitumor activity for each agent in dose-ranging xenograft or allograft experiments. Next, simulations of tumor growth inhibition (TGI) in xenografts/allografts at clinically relevant doses and schedules were carried out by replacing the murine pharmacokinetics, which were used to build the PK-PD model with human pharmacokinetics obtained from literature to account for species differences in pharmacokinetics. A significant correlation (r = 0.91, P = 0.0008) was observed between simulated xenograft/allograft TGI driven by human pharmacokinetics and clinical response but not when TGI observed at maximum tolerated doses in mice was correlated with clinical response (r = 0.36, P = 0.34). On the basis of these analyses, agents that led to greater than 60% TGI in preclinical models, at clinically relevant exposures, are more likely to lead to responses in the clinic. A proposed strategy for the use of murine subcutaneous models for compound selection in anticancer drug discovery is discussed.Clinical Cancer Research 05/2012; 18(14):3846-55. · 7.74 Impact Factor
Article: Basic PK/PD principles of drug effects in circular/proliferative systems for disease modelling.[show abstract] [hide abstract]
ABSTRACT: Disease progression modelling can provide information about the time course and outcome of pharmacological intervention on the disease. The basic PK/PD principles of proliferative and circular systems within the context of modelling disease progression and the effect of treatment thereupon are illustrated with the goal to better understand/predict eventual clinical outcome. Circular/proliferative systems can be very complex. To facilitate the understanding of how a dosing regimen can be defined in such systems we have shown the derivation of a system parameter named the Reproduction Minimum Inhibitory Concentration (RMIC) which represents the critical concentration at which the system switches from growth to extinction. The RMIC depends on two parameters (RMIC = (R(0) - 1) x IC(50)): the basic reproductive ratio (R(0)) a fundamental parameter of the circular/proliferative system that represents the number of offspring produced by one replicating species during its lifespan, and the IC(50), the potency of the drug to inhibit the proliferation of the system. The RMIC is constant for a given system and a given drug and represents the lowest concentration that needs to be achieved for eradication of the system. When exposure is higher than the RMIC, success can be expected in the long term. Time varying inhibition of replicating species proliferation is a natural consequence of the time varying inhibitor drug concentrations and when combined with the dynamics of the circular/proliferative system makes it difficult to predict the eventual outcome. Time varying inhibition of proliferative/circular systems can be handled by calculating the equivalent effective constant concentration (ECC), the constant plasma concentration that would give rise to the average inhibition at steady state. When ECC is higher than the RMIC, eradication of the system can be expected. In addition, it is shown that scenarios that have the same steady state ECC whatever the dose, dosage schedule or PK parameters have also the same average R (0) in the presence of the inhibitor (i.e. R (0-INH)) and therefore lead to the same outcome. This allows predicting equivalent active doses and dosing schedules in circular and proliferative systems when the IC(50) and pharmacokinetic characteristics of the drugs are known. The results from the simulations performed demonstrate that, for a given system (defined by its RMIC), treatment success depends mainly on the pharmacokinetic characteristics of the drug and the dosing schedule.Journal of Pharmacokinetics and Biopharmaceutics 03/2010; 37(2):157-77. · 2.06 Impact Factor
Article: Mechanism-based pharmacokinetic-pharmacodynamic modeling of the dopamine D2 receptor occupancy of olanzapine in rats.[show abstract] [hide abstract]
ABSTRACT: A mechanism-based PK-PD model was developed to predict the time course of dopamine D(2) receptor occupancy (D(2)RO) in rat striatum following administration of olanzapine, an atypical antipsychotic drug. A population approach was utilized to quantify both the pharmacokinetics and pharmacodynamics of olanzapine in rats using the exposure (plasma and brain concentration) and D(2)RO profile obtained experimentally at various doses (0.01-40 mg/kg) administered by different routes. A two-compartment pharmacokinetic model was used to describe the plasma pharmacokinetic profile. A hybrid physiology- and mechanism-based model was developed to characterize the D(2) receptor binding in the striatum and was fitted sequentially to the data. The parameters were estimated using nonlinear mixed-effects modeling . Plasma, brain concentration profiles and time course of D(2)RO were well described by the model; validity of the proposed model is supported by good agreement between estimated association and dissociation rate constants and in vitro values from literature. This model includes both receptor binding kinetics and pharmacokinetics as the basis for the prediction of the D(2)RO in rats. Moreover, this modeling framework can be applied to scale the in vitro and preclinical information to clinical receptor occupancy.Pharmaceutical Research 06/2011; 28(10):2490-504. · 4.09 Impact Factor