Paclitaxel (Taxol®) is now widely used against breast, ovarian and non-small-cell lung cancer. Anticancer agents generally have narrow therapeutic indices, often with myelosuppression (mainly neutropenia) as dose-limiting side effect. A further complicating factor is that paclitaxel when given as Taxol® has a nonlinear pharmacokinetic (PK) behaviour in plasma. Identifying risk groups more sensitive to chemotherapy due to either a PK or pharmacodynamic (PD) interindividual variability is of importance. The aim of the thesis was to develop predictive mechanism-based PK and PD models applicable for paclitaxel. PK and PK/PD models were developed for patient data from studies with relatively frequent sampling or sparse sampling schedules. Population analyses were performed using the software NONMEM. A pharmacokinetic model describing unbound, total plasma and blood concentrations of paclitaxel from known binding mechanisms was developed and validated. The nonlinear PK in plasma could to a large extent be explained by the micelle forming vehicle Cremophor EL (CrEL) and the unbound drug showed linear PK. Besides a binding component directly proportional to concentrations of CrEL, the model included both linear and nonlinear binding components in plasma and blood. Further, relations between the PK parameters and different demographic factors, including polymorphisms in the cytochrome P450s involved in paclitaxel metabolism, were investigated. A semi-physiological PD model for chemotherapy-induced myelosuppression was developed and applied to different anticancer drugs. The model included a self-renewal for proliferating cells, transit compartments describing the delay in observed myelosuppression and a feedback parameter reflecting the effect on the bone marrow from growth factors that can result in an overshoot in white blood cells. The system-related parameters estimated showed consistency across drugs and the difference in the drug-related parameter reflected the relative bone marrow toxicity of the drugs. Relations between demographic factors and the PD parameters were identified. The developed mechanism-based models promote a better understanding of paclitaxel PK and PD and may be used as tools in dosing individualisation and in development of dosing strategies for new administration forms and new drugs in the same area.

The blood-brain barrier (BBB) controls the movement of substances into and out of the brain. The tight junctions between endothelial cells and energy dependent transporters in the BBB influence rate and extent of drug distribution to the brain. The aim of this thesis was to study different methodological and pharmacokinetic aspects of drug transport at the BBB by characterizing possible active uptake and drug-drug interactions. Therefore, advanced tools for data acquisition and analysis were applied. The role of BBB transport in early drug development, with particular emphasis on in vitro-in vivo comparisons and species differences, was also investigated. Microdialysis in rats was used to study the BBB pharmacokinetics of oxymorphone, diphenhydramine (DPHM), oxycodone and morphine. Oxymorphone, DPHM and verapamil were all found to be actively taken up at the BBB, with brain to blood unbound drug ratios of 2, 5 and 2, respectively. The effect profile for oxycodone was successfully described using the modified M3 method for censored observations. In vitro experiments indicated a competitive interaction between DPHM and oxycodone on active uptake transport to the brain. No such interaction was observed in vivo due to much lower unbound concentrations achieved, compared with the in vitro Ki values. Active uptake of morphine at the BBB was not demonstrated even at very low concentrations as it was not possible to separate the active uptake transport process from active efflux by decreasing the morphine concentration. Mice carrying the human P-gp gene (hMDR1) were used to evaluate possible species differences in P-gp function. Differences were evident between the hMDR1 and normal mice in BBB penetration of various P-gp substrates and in the effect of blockers on P-gp function. Quantitative measurements of P-gp expression levels at the BBB and a comparison with human data are crucial for the future use of the hMDR1 model. In conclusion, this thesis reports active uptake of oxymorphone, DPHM and verapamil at the BBB. In vivo interaction of DPHM and oxycodone at the BBB was found not to be significant at therapeutic drug concentrations. Furthermore species differences were found between human and mouse P-gp function at the BBB.

<p>A central aim in drug development is to ensure that the new drug is efficacious and safe in the intended patient population.</p><p>Mathematical models describing the pharmacokinetic-pharmacodynamic (PK-PD) properties of a drug are valuable to increase the knowledge about drug effects and disease and can be used to inform decisions. The aim of this thesis was to develop mechanism-based PK-PD-disease models for important safety and efficacy biomarkers used in anti-diabetic drug development. </p><p>Population PK, PK-PD and disease models were developed, based on data from clinical studies in subjects with varying degrees of renal function, non-diabetic subjects with insulin resistance and patients with type 2 diabetes mellitus (T2DM), receiving a peroxisome proliferator-activated receptor (PPAR) α/γ agonist, tesaglitazar.</p><p>The PK model showed that a decreased renal elimination of the metabolite in renally impaired subjects leads to increased levels of metabolite undergoing interconversion and subsequent accumulation of tesaglitazar. Tesaglitazar negatively affects the glomerular filtration rate (GFR), and since renal function affects tesaglitazar exposure, a PK-PD model was developed to simultaneously describe this interrelationship. The model and data showed that all patients had decreases in GFR, which were reversible when discontinuing treatment. </p><p>The PK-PD model described the interplay between fasting plasma glucose (FPG), glycosylated haemoglobin (HbA1c) and haemoglobin in T2DM patients. It provided a mechanistically plausible description of the release and aging of red blood cells (RBC), and the glucose dependent glycosylation of RBC to HbA1c. The PK-PD model for FPG and fasting insulin, incorporating components for β-cell mass, insulin sensitivity and impact of disease and drug treatment, realistically described the complex glucose homeostasis in the heterogeneous patient population. </p><p>The mechanism-based PK, PK-PD and disease models increase the understanding about T2DM and important biomarkers, and can be used to improve decision making in the development of future anti-diabetic drugs. </p>

<p>In drug development clinical trials are designed to investigate whether a new treatment is safe and has the desired effect on the disease in the target patient population. Categorical endpoints, for example different ranking scales or grading of adverse events, are commonly used to measure effects in the trials. </p><p>Pharmacokinetic/Pharmacodynamic (PK/PD) models are used to describe the plasma concentration of a drug over time and its relationship to the effect studied. The models are utilized both in drug development and in discussions with drug regulating authorities. Methods for incorporation of ordered categorical data in PK/PD models were studied using a non-linear mixed effects modelling approach as implemented in the software NONMEM. The traditionally used proportional odds model was used for analysis of a 6-grade sedation scale in acute stroke patients and for analysis of a T-cell receptor expression in patients with Multiple Sclerosis, where the results also were compared with an analysis of the data on a continuous scale. Modifications of the proportional odds model were developed to enable analysis of a spontaneously reported side-effect and to analyze situations where the scale used is heterogeneous or where the drug affects the different scores in the scale in a non-proportional way. The new models were compared with the proportional odds model and were shown to give better predictive performances in the analyzed situations. </p><p>The results in this thesis show that categorical data obtained in clinical trials with different design and different categorical endpoints successfully can be incorporated in PK/PD models. The models developed can also be applied to analyses of other ordered categorical scales than those presented.</p>

<p>For prevention and treatment of thrombotic diseases with an anticoagulant drug it is important that an adequate dose is given to avoid occurrence or recurrence of thrombosis, without increasing the risk of bleeding and other adverse events to unacceptable levels. The aim of this thesis was to develop mathematical models that describe the dose-concentration (pharmacokinetic) and concentration-response (pharmacodynamic) relationships of direct thrombin inhibitors, in order to estimate optimal dosages for treatment and long-term secondary prevention of venous thromboembolism (VTE).</p><p>Population pharmacokinetic-pharmacodynamic models were developed, based on data from clinical investigations in healthy volunteers and patients receiving intravenous inogatran, subcutaneous melagatran and/or its oral prodrug ximelagatran. The benefit-risk profiles of different ximelagatran dosages were estimated using clinical utility functions. These functions were based on the probabilities and fatal consequences of thrombosis, bleeding and elevation of the hepatic enzyme alanine aminotransferase (ALAT).</p><p>The studies demonstrate that the pharmacokinetics of melagatran and ximelagatran were predictable and well correlated to renal function. The coagulation marker, activated partial thromboplastin time (APTT), increased non-linearly with increasing thrombin inhibitor plasma concentration. Overall, the systemic melagatran exposure (AUC) and APTT were similarly predictive of thrombosis and bleedings. The identified relationship between the risk of ALAT-elevation and melagatran AUC suggests that the incidence approaches a maximum at high exposures. The estimated clinical utility was favourable compared to placebo in the overall study population and in special subgroups of patients following fixed dosing of ximelagatran for long-term secondary prevention of VTE. Individualized dosing was predicted to add limited clinical benefit in this indication.</p><p>The models developed can be used to support the studied dosage and for selection of alternative dosing strategies that may improve the clinical outcome of ximelagatran treatment. In addition, the models may be extrapolated to aid the dose selection in clinical trials with other direct thrombin inhibitors.</p>

<p> Malaria, Human Immunodeficiency Virus (HIV) and tuberculosis (TB) are global health problems having their worst situation in sub-Saharan Africa. Consequently, concomitant use of antimalarial, antiretroviral and antitubercular drugs may be needed, resulting in a potential risk of drug-drug interactions.</p><p>Cytochrome P-450 (CYP) enzyme induction/inhibition may lead to drug-drug interactions and can be detected by probe drugs. An analytical method was developed for the quantitation of mephenytoin, CYP2B6 and CYP2C19 probe, and its metabolites. </p><p>Induction/inhibition of principal CYP enzymes by the antimalarials; artemisinin, dihydroartemisinin, arteether, artemether and artesunate, was evaluated using the 4-hour plasma concentration ratios of probe drugs and their metabolites along with modelling the population pharmacokinetics of S-mephenytoin and its metabolites. The extent of change in enzymatic activities was different among the antimalarials, with artemisinin having strongest capacity for induction and inhibition, consequently, the strongest potential risk for drug-drug interactions. </p><p>Drug-drug interactions between the antitubercular rifampicin and the antiretrovirals nevirapine and lopinavir were assessed, in TB/HIV patients, by developing population pharmacokinetic models. Rifampicin increased nevirapine oral clearance. Simulations suggested that increasing the nevirapine dose to 300 mg twice daily when co-administered with rifampicin, would result in nevirapine concentrations above subtherapeutic levels, with minimum exposure above the recommended maximum concentration. Lopinavir is co-formulated with ritonavir in the ratio of 4:1. In children, increasing ritonavir dose four times did not completely compensate the enhancement of lopinavir oral clearance caused by rifampicin. However, the predicted lopinavir trough concentration was above the recommended minimum therapeutic concentration.</p><p>The work presented in this thesis followed an investigation line though not done for a particular drug. First the CYP enzymes involved in the interaction are identified. Afterwards, the expected drug-drug interaction is investigated where the potentially interacting drugs are concomitantly administered and an adjustment in the dose regimen is proposed that is subsequently evaluated.</p>

Effects of drugs are in clinical trials often measured on categorical scales. These measurements are increasingly being analyzed using mixed-effects logistic regression. However, the experience with such analyzes is limited and only a few models are used. The aim of this thesis was to investigate the performance and improve the use of models and methods for mixed-effects categorical data analysis. The Laplacian method was shown to produce biased parameter estimates if (i) the data variability is large or (ii) the distribution of the responses is skewed. Two solutions are suggested; the Gaussian quadrature method and the back-step method. Two assumptions made with the proportional odds model have also been investigated. The assumption with proportional odds for all categories was shown to be unsuitable for analysis of data arising from a ranking scale of effects with several underlying causes. An alternative model, the differential odds model, was developed and shown to be an improvement, in regard to statistical significance as well as predictive performance, over the proportional odds model for such data. The appropriateness of the likelihood ratio test was investigated for an analysis where dependence between observations is ignored, i.e. performing the analysis using the proportional odds model. The type I error was found to be affected; thus assessing the actual critical value is prudent in order to verify the statistical significance level. An alternative approach is to use a Markov model, in which dependence between observations is incorporated. In the case of polychotomous data such model may involve considerable complexity and thus, a strategy for the reduction of the time-consuming model building with the Markov model and sleep data is presented. This thesis will hopefully contribute to a more confident use of models for categorical data analysis within the area of pharmacokinetic and pharmacodynamic modelling in the future.

For prevention and treatment of thrombotic diseases with an anticoagulant drug it is important that an adequate dose is given to avoid occurrence or recurrence of thrombosis, without increasing the risk of bleeding and other adverse events to unacceptable levels. The aim of this thesis was to develop mathematical models that describe the dose-concentration (pharmacokinetic) and concentration-response (pharmacodynamic) relationships of direct thrombin inhibitors, in order to estimate optimal dosages for treatment and long-term secondary prevention of venous thromboembolism (VTE). Population pharmacokinetic-pharmacodynamic models were developed, based on data from clinical investigations in healthy volunteers and patients receiving intravenous inogatran, subcutaneous melagatran and/or its oral prodrug ximelagatran. The benefit-risk profiles of different ximelagatran dosages were estimated using clinical utility functions. These functions were based on the probabilities and fatal consequences of thrombosis, bleeding and elevation of the hepatic enzyme alanine aminotransferase (ALAT). The studies demonstrate that the pharmacokinetics of melagatran and ximelagatran were predictable and well correlated to renal function. The coagulation marker, activated partial thromboplastin time (APTT), increased non-linearly with increasing thrombin inhibitor plasma concentration. Overall, the systemic melagatran exposure (AUC) and APTT were similarly predictive of thrombosis and bleedings. The identified relationship between the risk of ALAT-elevation and melagatran AUC suggests that the incidence approaches a maximum at high exposures. The estimated clinical utility was favourable compared to placebo in the overall study population and in special subgroups of patients following fixed dosing of ximelagatran for long-term secondary prevention of VTE. Individualized dosing was predicted to add limited clinical benefit in this indication. The models developed can be used to support the studied dosage and for selection of alternative dosing strategies that may improve the clinical outcome of ximelagatran treatment. In addition, the models may be extrapolated to aid the dose selection in clinical trials with other direct thrombin inhibitors.

Malaria, Human Immunodeficiency Virus (HIV) and tuberculosis (TB) are global health problems having their worst situation in sub-Saharan Africa. Consequently, concomitant use of antimalarial, antiretroviral and antitubercular drugs may be needed, resulting in a potential risk of drug-drug interactions. Cytochrome P-450 (CYP) enzyme induction/inhibition may lead to drug-drug interactions and can be detected by probe drugs. An analytical method was developed for the quantitation of mephenytoin, CYP2B6 and CYP2C19 probe, and its metabolites. Induction/inhibition of principal CYP enzymes by the antimalarials; artemisinin, dihydroartemisinin, arteether, artemether and artesunate, was evaluated using the 4-hour plasma concentration ratios of probe drugs and their metabolites along with modelling the population pharmacokinetics of S-mephenytoin and its metabolites. The extent of change in enzymatic activities was different among the antimalarials, with artemisinin having strongest capacity for induction and inhibition, consequently, the strongest potential risk for drug-drug interactions. Drug-drug interactions between the antitubercular rifampicin and the antiretrovirals nevirapine and lopinavir were assessed, in TB/HIV patients, by developing population pharmacokinetic models. Rifampicin increased nevirapine oral clearance. Simulations suggested that increasing the nevirapine dose to 300 mg twice daily when co-administered with rifampicin, would result in nevirapine concentrations above subtherapeutic levels, with minimum exposure above the recommended maximum concentration. Lopinavir is co-formulated with ritonavir in the ratio of 4:1. In children, increasing ritonavir dose four times did not completely compensate the enhancement of lopinavir oral clearance caused by rifampicin. However, the predicted lopinavir trough concentration was above the recommended minimum therapeutic concentration. The work presented in this thesis followed an investigation line though not done for a particular drug. First the CYP enzymes involved in the interaction are identified. Afterwards, the expected drug-drug interaction is investigated where the potentially interacting drugs are concomitantly administered and an adjustment in the dose regimen is proposed that is subsequently evaluated.

A central aim in drug development is to ensure that the new drug is efficacious and safe in the intended patient population. Mathematical models describing the pharmacokinetic-pharmacodynamic (PK-PD) properties of a drug are valuable to increase the knowledge about drug effects and disease and can be used to inform decisions. The aim of this thesis was to develop mechanism-based PK-PD-disease models for important safety and efficacy biomarkers used in anti-diabetic drug development. Population PK, PK-PD and disease models were developed, based on data from clinical studies in subjects with varying degrees of renal function, non-diabetic subjects with insulin resistance and patients with type 2 diabetes mellitus (T2DM), receiving a peroxisome proliferator-activated receptor (PPAR) α/γ agonist, tesaglitazar. The PK model showed that a decreased renal elimination of the metabolite in renally impaired subjects leads to increased levels of metabolite undergoing interconversion and subsequent accumulation of tesaglitazar. Tesaglitazar negatively affects the glomerular filtration rate (GFR), and since renal function affects tesaglitazar exposure, a PK-PD model was developed to simultaneously describe this interrelationship. The model and data showed that all patients had decreases in GFR, which were reversible when discontinuing treatment. The PK-PD model described the interplay between fasting plasma glucose (FPG), glycosylated haemoglobin (HbA1c) and haemoglobin in T2DM patients. It provided a mechanistically plausible description of the release and aging of red blood cells (RBC), and the glucose dependent glycosylation of RBC to HbA1c. The PK-PD model for FPG and fasting insulin, incorporating components for β-cell mass, insulin sensitivity and impact of disease and drug treatment, realistically described the complex glucose homeostasis in the heterogeneous patient population. The mechanism-based PK, PK-PD and disease models increase the understanding about T2DM and important biomarkers, and can be used to improve decision making in the development of future anti-diabetic drugs.