L'évaluation des risques de l'exposition aux mélanges de produits chimiques par voies multiples peut être améliorée par une compréhension de la variation de la dose interne due à l’interaction entre les produits. Les modèles pharmacocinétiques à base physiologique (PBPK) sont des outils éprouvés pour prédire l'ampleur de ces variations dans différents scénarios. Dans cette étude, quatre composés organiques volatils (COV) (toluène, nhexane, cyclohexane et isooctane) ont été choisis pour représenter des produits pétroliers (essence) pouvant contaminer l'eau potable. Premièrement, les modèles PBPK ont simulé l'exposition à un seul COV par une voie (inhalation ou gavage). Ensuite, ces modèles ont été interconnectés pour simuler l'exposition à un mélange par voies multiples. Les modèles ont été validés avec des données in vivo chez des rats Sprague-Dawley (n=5) exposés par inhalation (50 ppm ; toluène, hexane, et 300 ppm ; cyclohexane, isooctane; 2-h) ou par gavage (8,3; 5,5; 27,9 et 41,27 mg/kg pour le toluène, l’hexane, le cyclohexane et l’isooctane, respectivement). Des doses similaires ont été utilisées pour l'exposition au mélange par voies multiples. Les AUC (mg/L x min) pour le toluène, l'hexane, le cyclohexane et l'isooctane étaient respectivement de 157,25; 18,77; 159,58 et 176,54 pour les données expérimentales, et 121,73; 21,91; 19,55 et 170,54 pour les modèles PBPK. Les résultats des modèles PBPK et les données in vivo (simple COV par voies multiples vs. mélange par voies multiples) ont montré des interactions entre les COVs dans le cas de l'exposition au mélange par voies multiples. Cette étude démontre l'efficacité des modèles PBPK pour simuler l'exposition aux mélanges de COV par voies multiples. / Risk assessment focusing on exposure to mixtures by multiple routes can be improved with an understanding of the changes in internal doses due to interaction among chemicals. Physiologically based pharmacokinetic (PBPK) models are proven tools to predict the magnitude of interaction in various scenarios. In this study, four volatile organic compounds (VOCs) (toluene, nhexane, cyclohexane and isooctane) were chosen to represent petroleum products that could contaminate the drinking water (e.g. gasoline). PBPK models were used first to simulate exposure to a single chemical by a single route (inhalation, gavage) and simulate exposure to a mixture by multiple routes. PBPK models were validated by comparing simulations with in vivo data. These data were collected from groups of male Sprague-Dawley rats (n=5) exposed by inhalation (50 ppm of toluene, hexane; 300 ppm of cyclohexane and isooctane; 2-hr) or gavage (8.3, 5.5, 27.9, and 41.27 mg/kg, respectively, for toluene, hexane, cyclohexane and isooctane). For exposure to the mixture by multiple routes, same doses were used. The AUCs (mg/L x min) based on experimental data were 157.25, 18.77, 159.58 and 176.54 and the AUCs of the PBPKs model were 121.73, 21.91, 19.55 and 170.54, respectively, for toluene, hexane, cyclohexane and isooctane. Results from both PBPK models and in vivo data (single VOC, multiple routes vs. mixture, multiple routes) showed interactions between VOCs in the case of exposure to the mixture by multiple routes. This study demonstrated that the PBPK model is an effective tool to simulate exposure to mixtures of VOCs by multiple routes.

Kyoto University (京都大学) / 0048 / 新制・課程博士 / 博士(工学) / 甲第16383号 / 工博第3464号 / 新制||工||1524(附属図書館) / 29014 / 京都大学大学院工学研究科都市環境工学専攻 / (主査)教授 米田 稔, 教授 伊藤 禎彦, 准教授 越後 信哉 / 学位規則第4条第1項該当

The majority of drugs available on the market are intended to be administered through the oral route. To achieve the desired therapeutic effect, an orally administered drug must first reach the systemic circulation and then its site of action. The fraction of the administered drug that reaches the systemic circulation is known as oral bioavailability and it is the product of the absorption and first-pass metabolism processes occurring in both the GI tract and the liver. The factors controlling bioavailability are manifold –both drug and physiologically related - and their complex interplay is key to defining a drug’s oral bioavailability. In drug discovery and development it is therefore pivotal to anticipate and understand the bioavailability of a drug candidate; a far from simple task, considering the multifactorial nature of the process. For that reason, the overall aim of this thesis was to provide different modelling and simulation (M&S) strategies that can be used for the prediction of oral bioavailability that can be of use in drug discovery and development. The first part of this thesis was focused on the evaluation of the use of bioavailability data obtained from pre-clinical species as a predictor of the human value, in a more traditional approach. In particular, the aim was to evaluate models that can quantitatively and qualitatively provide a relationship between animal and human bioavailability, by analysing trends in a large bioavailability dataset. This section demonstrated that although pre-clinical species cannot quantitatively predict bioavailability, the data obtained from them can be used for qualitative prediction of the human value. Nevertheless, such a modelling approach does not provide a mechanistic rationale of the factors affecting the bioavailability differences. Consequently, the second part of this thesis was focused on such mechanistic predictions. Particularly, we investigated the impact that drug release patterns can have on drug absorption and intestinal first pass metabolism, taking into account the physiological differences observed across the length of the human gastrointestinal (GI) tract. These release patterns are suspected to lead to bioavailability differences due to changes in the first-pass metabolism, especially for CYP3A substrates. Therefore we investigated this phenomenon applying a physiologically-based pharmacokinetic (PBPK) M&S approach: firstly, from the discovery point of view, using PBPK models in a prospective fashion to investigating the drug-related factors that might lead to such differences and secondly, from the development point of view, to predict the mechanistic differences in absorption and metabolism of oxybutynin, a drug known for its higher bioavailability when formulated as a modified release (MR) product. The latter was done by developing and applying a novel simplified PBPK model to predict such differences. The results of this work showed that the intestinal metabolism can be significantly reduced when having MR formulations of CYP3A substrates which, in some cases, can lead to higher relative bioavailability. Additionally, this thesis provided novel methods and models that have the potential to improve bioavailability predictions when using PBPK models, in particular for drugs formulated as MR.

There are currently two types of drug formulation in clinical use in the locoregional treatment of intermediate hepatocellular carcinoma (HCC). In the emulsion LIPDOX, the cytostatic agent doxorubicin (DOX) is dissolved in the aqueous phase, which is emulsified with the oily contrast agent Lipiodol® (LIP). In the microparticular system DEBDOX, DOX is loaded into the drug-eluting entity DC Bead™. The overall aim of the thesis was to improve pharmaceutical understanding of the LIPDOX and DEBDOX formulations, in order to facilitate the future development of novel drug delivery systems. In vivo release of DOX from the formulations and the disposition of DOX and its active metabolite doxorubicinol (DOXol) were assessed in an advanced multisampling-site acute healthy pig model and in patients with HCC. The release of DOX and disposition of DOX and DOXol where further analysed using physiologically based pharmacokinetic (PBPK) and biopharmaceutical (PBBP) modelling. The combination of in vivo investigations and in silico modelling could provide unique insight into the mechanisms behind drug release and disposition. The in vivo release of DOX from LIPDOX is not extended and controlled, as it is from DEBDOX. With both formulations, DOX is released as a burst during the early phase of administration. The in vivo release of DOX from LIPDOX was faster than from DEBDOX in both pigs and patients. The release from DEBDOX was slow and possibly incomplete. The in vivo release of DOX from LIPDOX and DEBDOX could be described by using the PBBP model in combination with in vitro release profiles. The disposition of DOX and DOXol was modelled using a semi-PBPK model containing intracellular binding sites. The contrast agent Lipiodol® did not affect the hepatobiliary disposition of DOX in the pig model. The control substance used in this study, cyclosporine A, inhibited the biliary excretion of DOX and DOXol but did not alter metabolism in healthy pigs. The disposition of DOX is similar in healthy pigs and humans, which was shown by the ease of translation of the semi-PBPK pig model to the human PBBP model.

PBPK modelling is used in drug development to predict how the drug isaffected by the body. These models are built on physiology and describeprocesses like absorption, distribution, metabolism and excretion.Simulations of these processes can take place in the software PK-Sim forinstance. In PK-Sim, datasets of clinical observations can be importedfor model validation. When building the models, correct data and correcttype of model has to used to prevent incorrect predictions. These errorscan be discovered by performing quality control, preferably beforeinitiating model development in order to save time. An automatic processof quality control is also a way to save time, as well as to setstandards and provide transparency. At Pharmetheus, where PBPK modellingin PK-Sim is performed, quality control is executed manually. In thisproject, an infrastructure for quality control of data in PBPK projectsin PK-Sim was developed in R. The intention was to use thisinfrastructure before initiating model development and as a complementto manual quality control. The quality control was focused on dataintegrity and data concordance. Controls that are performed includedcorrectness of values and units for the observed data as well asensuring that each data had been assigned to the corresponding model.The developed model achieved to capture all defined errors to a highdegree. However, in many scenarios rounding of values occurred which wasnot always handled as intended. More evaluation also has to be performedbefore this infrastructure can be used in production.

L’évaluation de l’exposition aux composés organiques volatils (COV) recourt couramment à l’analyse des métabolites urinaires en assumant qu’aucune interaction ne survient entre les composés. Or, des études antérieures ont démontré qu’une inhibition de type compétitive survient entre le toluène (TOL), l’éthylbenzène (EBZ) et le m-xylène (XYL). Le chloroforme, qui est également un solvant métabolisé par le CYP2E1, se retrouve souvent en présence des autres COV dans les échantillons de biosurveillance. La présente étude visait donc à évaluer si le chloroforme (CHL) peut lui aussi interagir avec ces COV et évaluer ces interactions au niveau de l’excrétion des biomarqueurs urinaires associés, soit l’o-crésol, l’acide mandélique et l’acide m-méthylhippurique pour TOL, EBZ et XYL respectivement. Afin d’obtenir des données humaines, cinq volontaires ont été exposés par inhalation à différentes combinaisons de COV (seuls et mélanges binaires ou quaternaires) où la concentration de chacun des composés était égale à 1/4 ou 1/8 de la valeur limite d’exposition (VLE) pour une durée de 6h. Des échantillons d’air exhalé, de sang et d’urine ont été récoltés. Ces données ont ensuite été comparées aux modèles pharmacocinétiques à base physiologique (PCBP) existants afin de les ajuster pour l’excrétion urinaire. Certaines différences ont été observées entre les expositions aux solvants seuls et les coexpositions, mais celles-ci semblent majoritairement attribuables aux remplacements de participants à travers les différentes expositions. Les valeurs de Vmax pour EBZ et CHL ont été optimisées afin de mieux prédire les niveaux sanguins de ces COV. À l’exception du modèle pour EBZ, tous les paramètres pour l’excrétion urinaire ont été obtenus à partir de la littérature. Les modèles adaptés dans cette étude ont permis de simuler adéquatement les données expérimentales. / Evaluation of volatile organic compounds (VOC) exposure commonly resorts to urinary metabolite analyses, assuming that no interaction occur between coexposed chemicals. However, previous studies have reported competitive inhibition between toluene (TOL), ethylbenzene (EBZ) and m-xylene (XYL). Chloroform, which is also metabolized by CYP2E1, is also often found in human biomonitoring samples along with the mentioned VOCs. The goal of the present study was to evaluate if chloroform (CHL) can interact with previous VOC and to evaluate those interactions at the urinary biomarker excretion level for corresponding metabolites, namely o-cresol, mandelic acid and m-methylhippuric acid for TOL, EBZ and XYL respectively. To obtain human data, five male volunteers were exposed by inhalation to different VOC combinations (single and binary or quaternary mixtures) where concentration of each chemical was equal to 1/4 or 1/8 of the threshold limit value (TLV) for 6h. Exhaled air blood and urine samples were collected. These data were then compared with existing physiologically based pharmacokinetic (PBPK) model predictions for adjustment for urinary excretion. Some differences were observed between single and mixed exposures but they may be mainly related to volunteer replacements throughout experiments. Vmax values for EBZ and CHL were optimized to better fit blood data. Except for EBZ model, all urinary excretion parameters were taken from the literature. Models adapted in the present study adequately simulated experimental data.

The medical use of marijuana is increasing, yet little is known about the exposure-response relationships resulting in its psychoactive effects. Δ9-tetrahydrocannabinol (THC) and its active metabolite (11-hydroxy-THC; THC-OH) are the principal psychoactive components in marijuana. It is well known that the plasma concentrations of the psychoactive components of marijuana do not directly relate to the observed psychoactive effects. The presence of a counter-clockwise hysteresis in the plasma concentrations-effect plot demonstrates a temporal delay between the plasma concentrations and observed effect following the intravenous administration of THC. The overarching objective of this research was to better understand the relationship between the plasma and brain concentrations of the psychoactive components (THC and THC-OH) and the observable psychoactive effects after intravenous administration of THC, utilizing model-based approaches. Specifically, the pharmacokinetics were explored using population pharmacokinetic (Pop PK) and physiologically-based pharmacokinetic (PBPK) modeling whereas the pharmacodynamics (PD) of the psychoactive effect (“highness”) were explored using effect-compartment modeling and linking the PD to the PBPK-derived concentrations predicted in the brain and an assumed effect-site. A “hypothetical” effect compartment model was developed to characterize the observed delay in peak “highness” ratings. A direct relationship was established between the reported psychoactive effects (“highness” or intoxication) and the predicted effect-site concentrations of both components (THC and THC-OH) using this effect-compartment modeling approach. The faster plasma to effect compartment equilibration for THC-OH indicated a more rapid equilibration of the active metabolite between plasma and the effect-site (biophase) than for the parent THC. In addition, a PBPK modeling approach was pursued to predict and relate the brain concentrations of THC and THC-OH to the psychoactive effect. The relationship between the effect and the predicted unbound brain concentration of THC indicated an indirect relationship, suggesting a temporal delay between brain concentrations of THC and observed effect. However, a direct relationship was observed between the observed effect and the unbound brain THC-OH concentrations. In addition, the unbound concentrations of THC-OH in the brain were predicted to be higher than the corresponding THC concentrations. These findings highlight the importance for the inclusion of THC-OH, in addition to THC, when relating the observed effect to the concentrations of the psychoactive components of marijuana. These models contribute to the understanding of the PK-PD relationships associated with marijuana use and are important steps in the prediction of the pharmacodynamic effects related to the psychoactive components in marijuana and establish an approach for investigating other THC-related effects.

Les modèles physiologiques toxicocinétiques (PBPK pour Physiologically-Based PharmacoKinetic) permettent de décrire la biodistribution d'une substance (c'est-à-dire, son administration, distribution, métabolisme, et excrétion) au sein d'un organisme. Cependant, l'ajustement d'un modèle PBPK à des données expérimentales peut se révéler difficile en raison de la complexité du modèle, du nombre important de paramètres à estimer, et de la nature des données toxicocinétiques (généralement peu nombreuses, éparses et entachées d'erreur de mesure). Pour pallier à ces difficultés, nous proposons de développer deux protocoles expérimentaux facilitant la paramétrisation des modèles PBPK, par l'apport d'informations complémentaires sur les paramètres des modèles : la collecte de données sur la distribution spatio-temporelle d'une substance dans l'organisme par des techniques d'imagerie, et l'utilisation de traceurs non-toxiques lors d'études toxicocinétiques. <br />Pour notre premier protocole, nous avons appliqué l'analyse d'image au développement d'un modèle PBPK décrivant la biodistribution d'un agent de contraste, Vistarem®. Grâce à la modélisation des données recueillies par imagerie par résonance magnétique, nous avons pu caractériser la vascularisation du corps entier et celle d'une tumeur greffée, ainsi qu'évaluer statistiquement les effets d'un traitement antiangiogénique. <br />Ensuite, nous avons introduit l'utilisation de traceurs explorateurs lors d'études toxicocinétiques. Nous avons développé des protocoles d'exposition à une substance toxique et à un traceur non-toxique pour les humains. Sur la base d'expositions simulées, nous avons montré qu'en administrant aux sujets deux substances, il est possible de réduire la dose d'exposition du toxique (par 4 dans notre exemple d'application) tout en maintenant la précision sur l'estimation des paramètres d'intérêt. L'inconvénient majeur de ce protocole d'exposition est la lourdeur des calculs induits (la calibration de deux modèles PBPK est nécessaire). Afin de réduire la complexité des calculs engendrés, nous avons proposé d'appliquer des techniques d'agrégation de systèmes d'équations différentielles. L'essentiel de ces techniques est de réduire un système tout en conservant sa dynamique. Sur des exemples simples, nous avons montré leur potentiel en toxico/pharmacocinétique. <br />Chacun des deux protocoles développés dans ce travail inclut, en plus de la substance d'intérêt, l'utilisation d'une substance "annexe". Notre travail montre que l'utilisation de cette substance annexe permet de renforcer la connaissance sur l'anatomie et la physiologie du sujet considéré. Ceci conduit donc à une meilleure détermination de l'action de la substance d'intérêt. Une suite logique de notre travail serait de coupler ces deux protocoles, c'est-à-dire de développer des protocoles d'exposition à une substance toxique et à une substance visualisable par une technique d'imagerie quantitative.

In risk assessment of risk chemicals, variability in susceptibility in the population is an important aspect. The health hazard of a pollutant is related to the internal exposure to the chemical, i.e. the target dose, rather than the external exposure. The target dose may be calculated by physiologically based pharmacokinetic (PBPK) modeling. Furthermore, variability in target dose may be estimated by introducing variability in the physiological, anatomical, and biochemical parameters of the model. Data on these toxicokinetic model parameters may be found in the scientific literature. Since the early seventies, a large number of experimental inhalation studies of the kinetics of several volatiles in human volunteers have been performed at the National Institute for Working Life in Solna. To this day, only very limited analyses of these extensive data have been performed. A Bayesian analysis makes it possible to merge a priori knowledge from the literature with the information in experimental data. If combined with population PBPK modeling, the Bayesian approach may yield posterior estimates of the toxicokinetic parameters for each subject, as well as for the population. One way of producing these estimates is by so-called Markov-chain Monte Carlo (MCMC) simulation. The aim of the thesis was to apply the MCMC technique on previously published experimental data. Another objective was to assess the reliability of PBPK models in general by the combination of the extensive data and Bayesian population techniques. The population kinetics of methyl chloride, dichloromethane, toluene and styrene were assessed. The calibrated model for dichloromethane was used to predict cancer risk in a simulated Swedish population. In some cases, the respiratory uptake of volatiles was found to be lower than predicted from reference values on alveolar ventilation. The perfusion of fat tissue was found to be a complex process that needs special attention in PBPK modeling. These results provide a significant contribution to the field of PBPK modeling of risk chemicals. Appropriate statistical treatment of uncertainty and variability may increase confidence in model results and ultimately contribute to an improved scientific basis for the estimation of occupational health risks.

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