Mechanism-based modeling of functional adaptation upon chronic treatment with midazolam

Novel CNS drug discovery and development approach: model-based integration to predict neuro-pharmacokinetics and pharmacodynamics

INTRODUCTION

CNS drug development has been hampered by inadequate consideration of CNS pharmacokinetic (PK), pharmacodynamics (PD) and disease complexity (reductionist approach). Improvement is required via integrative model-based approaches. Areas covered: The authors summarize factors that have played a role in the high attrition rate of CNS compounds. Recent advances in CNS research and drug discovery are presented, especially with regard to assessment of relevant neuro-PK parameters. Suggestions for further improvements are also discussed. Expert opinion: Understanding time- and condition dependent interrelationships between neuro-PK and neuro-PD processes is key to predictions in different conditions. As a first screen, it is suggested to use in silico/in vitro derived molecular properties of candidate compounds and predict concentration-time profiles of compounds in multiple compartments of the human CNS, using time-course based physiology-based (PB) PK models. Then, for selected compounds, one can include in vitro drug-target binding kinetics to predict target occupancy (TO)-time profiles in humans. This will improve neuro-PD prediction. Furthermore, a pharmaco-omics approach is suggested, providing multilevel and paralleled data on systems processes from individuals in a systems-wide manner. Thus, clinical trials will be better informed, using fewer animals, while also, needing fewer individuals and samples per individual for proof of concept in humans.

Applications of linking PBPK and PD models to predict the impact of genotypic variability, formulation differences, differences in target binding capacity and target site drug concentrations on drug responses and variability

This study aimed to demonstrate the added value of integrating prior in vitro data and knowledge-rich physiologically based pharmacokinetic (PBPK) models with pharmacodynamics (PDs) models. Four distinct applications that were developed and tested are presented here. PBPK models were developed for metoprolol using different CYP2D6 genotypes based on in vitro data. Application of the models for prediction of phenotypic differences in the pharmacokinetics (PKs) and PD compared favorably with clinical data, demonstrating that these differences can be predicted prior to the availability of such data from clinical trials. In the second case, PK and PD data for an immediate release formulation of nifedipine together with in vitro dissolution data for a controlled release (CR) formulation were used to predict the PK and PD of the CR. This approach can be useful to pharmaceutical scientists during formulation development. The operational model of agonism was used in the third application to describe the hypnotic effects of triazolam, and this was successfully extrapolated to zolpidem by changing only the drug related parameters from in vitro experiments. This PBPK modeling approach can be useful to developmental scientists who which to compare several drug candidates in the same therapeutic class. Finally, differences in QTc prolongation due to quinidine in Caucasian and Korean females were successfully predicted by the model using free heart concentrations as an input to the PD models. This PBPK linked PD model was used to demonstrate a higher sensitivity to free heart concentrations of quinidine in Caucasian females, thereby providing a mechanistic understanding of a clinical observation. In general, permutations of certain conditions which potentially change PK and hence PD may not be amenable to the conduct of clinical studies but linking PBPK with PD provides an alternative method of investigating the potential impact of PK changes on PD.

The mastermind approach to CNS drug therapy: translational prediction of human brain distribution, target site kinetics, and therapeutic effects

Despite enormous advances in CNS research, CNS disorders remain the world's leading cause of disability. This accounts for more hospitalizations and prolonged care than almost all other diseases combined, and indicates a high unmet need for good CNS drugs and drug therapies.Following dosing, not only the chemical properties of the drug and blood-brain barrier (BBB) transport, but also many other processes will ultimately determine brain target site kinetics and consequently the CNS effects. The rate and extent of all these processes are regulated dynamically, and thus condition dependent. Therefore, heterogenious conditions such as species, gender, genetic background, tissue, age, diet, disease, drug treatment etc., result in considerable inter-individual and intra-individual variation, often encountered in CNS drug therapy.For effective therapy, drugs should access the CNS "at the right place, at the right time, and at the right concentration". To improve CNS therapies and drug development, details of inter-species and inter-condition variations are needed to enable target site pharmacokinetics and associated CNS effects to be translated between species and between disease states. Specifically, such studies need to include information about unbound drug concentrations which drive the effects. To date the only technique that can obtain unbound drug concentrations in brain is microdialysis. This (minimally) invasive technique cannot be readily applied to humans, and we need to rely on translational approaches to predict human brain distribution, target site kinetics, and therapeutic effects of CNS drugs.In this review the term "Mastermind approach" is introduced, for strategic and systematic CNS drug research using advanced preclinical experimental designs and mathematical modeling. In this way, knowledge can be obtained about the contributions and variability of individual processes on the causal path between drug dosing and CNS effect in animals that can be translated to the human situation. On the basis of a few advanced preclinical microdialysis based investigations it will be shown that the "Mastermind approach" has a high potential for the prediction of human CNS drug effects.

Decreased Efficacy of GABAA-receptor Modulation by Midazolam in the Kainate Model of Temporal Lobe Epilepsy

PURPOSE

The objective of this investigation was to characterize quantitatively the time-dependent changes in midazolam (MDL) efficacy in the silent period after induction of status epilepticus (SE) in rats. The changes in MDL efficacy were correlated to changes in ex vivo GABA(A)-receptor expression.

METHODS

MDL efficacy was quantified by pharmacokinetic-pharmacodynamic (PK-PD) modeling by using the beta-frequency of the EEG as PD end point. Two PK-PD experiments were performed in each animal: the first experiment before and the second experiment at either day 4 or day 14 after SE. SE was induced by repetitive intraperitoneal injections with kainate. GABA(A)-receptor expression was determined by ex vivo autoradiography with [(3)H]flumazenil.

RESULTS

The concentration versus EEG effect relation of midazolam was successfully described by the sigmoidal E(max) model. The maximal effect on the beta-frequency of the EEG (E(max)) was reduced to 51.6 +/- 35.6% and 25.8 +/- 33.7% of the original value at 4 and 14 days after induction of SE. The ex vivo study with [(3)H]flumazenil showed that the observed reductions in E(max) were paralleled by a reduction in GABA(A)-receptor density.

CONCLUSIONS

The efficacy of MDL is decreased in the silent period after SE, which can be partly accounted for by a reduction in GABA(A)-receptor density.

Effect of the administration of tiagabine and gabapentin on rabbit electroencephalogram activity

New generation antiepileptic drugs, including gabapentin and tiagabine, are used in monotherapy or in combination with other drugs for specific seizure types. The multidirectional mechanism of activity and varied pharmacological properties of these drugs suggest that they could also be used in the therapy of other diseases. A possible limitation of new generation antiepileptic drugs is the incidence of CNS-related adverse effects. Few studies have assessed the effect of new antiepileptic drugs on electroencephalogram (EEG) recordings in subjects using these drugs for diseases other than epilepsy. The aim of this study was to determine the effects of tiagabine and gabapentin on EEG recordings from the midbrain reticular formation, dorsal hippocampus and frontal cortex in rabbits. Tiagabine was administered orally at a single dose of 5 and 20 mg kg(-1), or repeatedly at a dose of 5 mg kg(-1) (twice a day) for 14 days. Gabapentin was administered orally at a single dose of 25 and 100 mg kg(-1), or repeatedly at a dose of 25 mg kg(-1) (twice a day) for 14 days. Both tiagabine and gabapentin caused changes indicative of CNS inhibitory properties, which may be associated with the adverse effects of the drugs. After repeated doses of the drugs, the changes in EEG recordings were less pronounced than after single doses, which may indicate adaptive changes. The hippocampus was found to be the least sensitive to the effect of gabapentin.

Estimating the parameters of the operational model of pharmacological agonism

The aim of this work is practical. We show that the parameters of the widely used operational model of pharmacological agonism are difficult to estimate from single dose-response curves. The parameters can be estimated using pairs of dose-response curves (usually treatment and control) sharing some parameters. Confidence bands for the estimators are developed. In the case of multiple dose-response curve pairs one can employ a non-linear mixed effects model to allow for inter-individual variation. The point estimates and the confidence intervals thus obtained are similar to the more naive construction based on mean and standard errors of parameter estimates. To test for difference of certain parameters between treatment and control we employ a permutation test and Wald's test.

Toward the prediction of CNS drug-effect profiles in physiological and pathological conditions using microdialysis and mechanism-based pharmacokinetic-pharmacodynamic modeling

Our ultimate goal is to develop mechanism-based pharmacokinetic (PK)-pharmacodynamic (PD) models to characterize and to predict CNS drug responses in both physiologic and pathologic conditions. To this end, it is essential to have information on the biophase pharmacokinetics, because these may significantly differ from plasma pharmacokinetics. It is anticipated that biophase kinetics of CNS drugs are strongly influenced by transport across the blood-brain barrier (BBB). The special role of microdialysis in PK/PD modeling of CNS drugs lies in the fact that it enables the determination of free-drug concentrations as a function of time in plasma and in extracellular fluid of the brain, thereby providing important data to determine BBB transport characteristics of drugs. Also, the concentrations of (potential) extracellular biomarkers of drug effects or disease can be monitored with this technique. Here we describe our studies including microdialysis on the following: (1) the evaluation of the free drug hypothesis; (2) the role of BBB transport on the central effects of opioids; (3) changes in BBB transport and biophase equilibration of anti-epileptic drugs; and (4) the relation among neurodegeneration, BBB transport, and drug effects in Parkinson's disease progression.

Pharmacodynamic analysis of the interaction between tiagabine and midazolam with an allosteric model that incorporates signal transduction

PURPOSE

The objective of this study was to characterize quantitatively the pharmacodynamic interaction between midazolam (MDL), an allosteric modulator of the gamma-aminobutyric acid subtype A (GABAA) receptor, and tiagabine (TGB), an inhibitor of synaptic GABA uptake.

METHODS

The in vivo concentration-response relation of TGB was determined through pharmacokinetic/pharmacodynamic (PK/PD) modeling. Rats received a single intravenous dose of 10 mg/kg TGB in the absence and the presence of a steady-state plasma concentration of MDL. The EEG response in the 11.5- to 30-Hz frequency band was used as the pharmacodynamic end point.

RESULTS

Infusion of MDL resulted in a mean steady-state plasma concentration of 66 +/- 3 ng/ml. A significant pharmacokinetic interaction with TGB was observed. MDL inhibited TGB clearance by 20 +/- 7 ml/min/kg from the original value of 89 +/- 6 ml/min/kg. However, no changes in plasma protein binding of both drugs were observed. The concentration-EEG relation of TGB was described by the sigmoid-Emax model. The pharmacodynamic parameter estimates of TGB were: Emax = 327 +/- 10 microV, EC50 = 392 +/- 20 ng/ml, and nH = 3.1 +/- 0.3. These values were not significantly different in the presence of MDL. Factors that may explain the lack of synergism were identified by a mechanism-based interaction model that separates the receptor activation from the signal-transduction process. High efficiency of signal transduction and the presence of a baseline response were shown to diminish the degree of synergism.

CONCLUSIONS

We conclude that the in vivo pharmacodynamic interaction between MDL and TGB is additive rather than synergistic. This strongly suggests that allosteric modulation of the antiseizure activity of a GAT-1 inhibitor by a benzodiazepine does not offer a therapeutic advantage.

Pharmacokinetic-pharmacodynamic modelling of tiagabine CNS effects upon chronic treatment in rats: lack of change in concentration-EEG effect relationship

The pharmacodynamics of the gamma-aminobutyric acid (GABA) uptake inhibitor (R)-N-(4,4-di-(methylthien-2-yl)but-3-enyl) nipecotic acid (tiagabine) was quantified in rats following chronic (14 days) administration by an integrated pharmacokinetic-pharmacodynamic (PK/PD) modelling approach. The increase in beta activity (11.5-30 Hz) of the EEG as derived by fast Fourier transformation analysis was used as pharmacodynamic endpoint. Two groups of male Wistar rats were treated for 14 days with either tiagabine at a steady-state concentration of 198+/-10 ng ml(-1) or placebo. Chronic treatment with tiagabine resulted in an increase of the EEG effect parameter by 38+/-2 microV. In the PK/PD experiment the time course of the EEG effect was determined in conjunction with the decline of drug concentrations after an i.v. bolus administration of 10 mg kg(-1). The pharmacokinetics of tiagabine was most adequately described by a bi-exponential function. No influence of chronic treatment on the pharmacokinetics was observed. Hysteresis between plasma concentration and EEG effect was accounted for by incorporation of an 'effect-compartment' in the model. The observed relationship between tiagabine concentrations and EEG effect was non-linear and described on the basis of the Hill equation. Between the treatment groups no differences in the pharmacodynamic parameters were observed. The population means for the different pharmacodynamic parameters were: maximum EEG effect 82 microV, EC(50) 486 ng ml(-1), Hill factor 2.0 and k(e0) 0.060 min(-1). In the in vitro [(3)H]GABA uptake assay no changes in affinity or functionality for the GABA uptake transporter were observed, consistent with the absence of adaptation. It is concluded that chronic treatment with tiagabine in an effective dose range for 14 days does not produce functional adaptation to tiagabine-induced GABA-ergic inhibition in vivo.