A physiologically-based toxicokinetic and toxicodynamic (PBTK/TD) model was developed, from the open literature, to predict the toxicokinetic disposition and toxicodynamic response (acetylcholinesterase inhibition) of a ternary organophosphorus (OP) insecticide mixture: chlorpyrifos (CP), methyl parathion (MP) and parathion (P). In vivo studies were conducted in adult male Sprague-Dawley rats, orally administered one of two CP/MP/P mixtures (2.5, 0.5, 0.5 mg/kg or 5, 1, 1 mg/kg) with selected tissues (blood, brain, diaphragm, liver, lung and skeletal muscle) collected at 30min, 4, 12 and 24hr postdosing. Low dosages were studied so the mixture did not result in significant disruption of cardiovascular function nor invalidate the model’s underlying general physiological assumptions. The data were used to validate the model. CP and its metabolites (CP-oxon, 3,5,6-trichloro-2-pyridinol (TCP)), as well as MP, P and 4-nitrophenol, were quantified in the tissues of interest. Peak concentrations of CP were attained by 4hr in all tissues with the exception of the liver, whose peak occurred at 30min; MP, 30min in all tissues; P, 12hr in all tissues with the exception of the liver, 30min. This was supported by the model simulations. MP, P, and their respective oxons were below limits of quantitation for the lower dosage. No toxicokinetic interactions were observed in the present study. Cholinesterase inhibition in the tissues ranged from 11- 37% for the lower dosage, and 29-93% for the higher dosage group; with few exceptions, inhibition was generally additive and was also supported by the model simulations. This study demonstrates the utility of using previously developed individual PBTK/TD models and in vitro/in vivo data from the open literature to construct reliable mixture PBTK/TD models.

No description available.

L’amélioration du développement du médicament est un véritable défi et ceci encore plus dans le domaine de l’oncologie dans lequel le besoin d’avoir de nouvelles alternatives thérapeutiques est primordial. De plus, on note que le taux d’approbation des nouveaux anticancéreux après leur entrée en phase 1 fait partie des plus bas taux de toutes les aires thérapeutiques. De ce fait, ce processus doit être amélioré et l’utilisation de nouvelles approches faisant le lien entre développement préclinique et clinique par anticipation des propriétés pharmacocinétiques et d’efficacité pourrait être une perspective intéressante.L’objectif de ce travail est l’élaboration de stratégies basées sur la modélisation mathématique de données précliniques in vivo et in vitro afin d’anticiper le comportement chez l’homme d’un nouvel inhibiteur de bcl-2 développé par les Laboratoires Servier pour soutenir le développement clinique. Ce projet a été mené suivant différentes étapes :Premièrement, un modèle semi-mécanistique décrivant le mode d’action de la molécule a été établi chez la souris.Une stratégie d’extrapolation inter-espèces des caractéristiques PK utilisant la modélisation PBPK a été effectuée afin d’anticiper les profils temps-concentration chez l’homme.Des stratégies d’extrapolation de la partie PD basées sur différentes hypothèses ont été proposées pour prédire une efficacité chez l’homme et des doses à tester lors de l’étude clinique.Les prédictions obtenues ont ainsi été comparées aux résultats cliniques issus de la première étude réalisée chez l’homme confirmant le caractère utile de telles approches et la supériorité des stratégies bâties à l’aide de concepts semi-mécanistiques par rapport aux approches plus empiriques.Ce projet souligne donc le grand intérêt d’élaborer des approches translationnelles inter-espèces durant le développement du médicament et pourrait favoriser leur utilisation afin d’accélérer le développement de nouvelles entités, diminuant ainsi les risques d’échecs ainsi que les coûts financiers / Improvement of drug development is a very challenging question and even more in the field of oncology wherein the need for new medicines is crucial. In addition, the rate of approval for anticancer drugs after entry in phase I clinical trial was reported as one of the lowest of all therapeutic areas. Thereby, this process has to be improved, and the use of new approaches fulfilling the gap between preclinical and clinical settings by anticipating human pharmacokinetics and efficacy could be an interesting solution.The work is focused on the building of strategies based on mathematical modeling of in vivo and in vitro preclinical data to anticipate the behavior of a new bcl-2 inhibitor developed by Servier laboratories in human to support clinical development. This project was elaborated following different steps:Firstly, a semi-mechanistic relationship was established in mice to describe the mechanism of action of the compound.PK extrapolation strategy using PBPK modeling was performed to anticipate human concentration-time profiles.PD extrapolation strategies based on different assumptions were proposed to predict human efficacy and doses to be tested in clinical trial.Predictions obtained were consequently compared to clinical results from a First in Human study confirming the usefulness of such approaches and the superiority of mechanism-based strategies compared to more empirical approaches.Therefore, this project highlights the large interest of elaborating interspecies translational approaches during drug development and could promote their use to accelerate new entities development, decreasing the risks of failure and financial costs.

Résumé: De nombreuses études ont établi que l’exposition aux moisissures intérieures peut être nuisible à la santé. Dans une récente étude, 21 composés organiques volatils microbiens (COVM) ont été sélectionnés comme biomarqueurs potentiels de l’exposition aux moisissures intérieures. L’objectif du projet était de déterminer les coefficients de partage (CP) sang:air, urine:air, plasma:air et eau:air pour ces composés, paramètres utilisés dans la prédiction de la toxicocinétique des xénobiotiques. Pour y parvenir, la méthode de flacons à l’équilibre a été utilisée. Les COVM (1.57-2.01 µg) injectés dans des flacons (20 ml) hermétiquement scellés contenant soit 0.5 ml de matrice (flacons test) ou simplement de l’air (flacons références) ont été incubés 60 min à 37⁰ C sous agitation continue. La quantification des COVM dans l’espace de tête des flacons (test et références) a été ensuite faite par chromatographie en phase gazeuse couplée à la spectrométrie de masse (GC-MS/MS). Les CP de 19 COVM variaient entre 78 et 4721 pour sang:air, 14 et 3586 pour urine:air, 64 et 5604 pour plasma:air et 16 et 2210 pour eau:air. Les CP eau:air étaient étroitement liés aux CP urine:air pour 17 COVM (R2 = 0,97, pente =1,001) suggérant que la valeur de CP eau:air (lorsqu’inférieur à103) peut être un substitut au CP urine:air. L’étude des ratios sang:urine indique que six COVM seraient nettement plus concentrés dans le sang, matrice de choix pour ces composés. Les données générées par cette étude faciliteront le développement de modèles pharmacocinétiques de COVM et le paramétrage de leurs prélèvements en tant que biomarqueurs de l’exposition aux moisissures intérieures. / Abstract: Numerous studies have established that exposure to indoor molds can be harmful to health. In a recent study, 21 microbial volatile organic compounds (mVOCs) were selected as potential biomarkers of indoor mold exposure. The objective of the project was to determine the blood:air, urine:air, plasma:air, and water:air partition coefficients (PCs) for these compounds, parameters used in predicting the toxicokinetics of xenobiotics. To achieve this, the vial-equilibration method was used. mVOCs (1.57-2.01 µg) were injected into hermetically sealed vials (20 ml) containing either 0.5 ml of matrix (test vials) or simply air (reference vials) and were incubated for 60 min at 37 ⁰C under continuous agitation. Quantification of mVOCs in the headspace of the vials (test and reference) was then performed by gas chromatography mass spectrometry (GC-MS/MS). The PCs of 19 mVOCs ranged from 78 and 4721 for blood:air, 14 and 3586 for urine:air, 64 and 5604 for plasma:air, and 16 and 2210 for water:air. Water:air PCs were closely related to urine:air PCs for 17 mVOCs (R2 = 0.97, slope =1.001) suggesting that the water:air PC value (when less than 103) may be a surrogate for the urine:air PC. The blood:urine ratio study indicates that six mVOCs would be significantly more concentrated in blood, the matrix of choice for these compounds. The data generated from this study will facilitate the development of pharmacokinetic models of mVOCs and the parameterization of their sampling as biomarkers of indoor mold exposure.

Die Phänotypisierung von Cytochrom P450 (CYP) und Leberfunktionstests sind wichtige Methoden in der Klinik. Die Methoden nutzen die Pharmakokinetik (PK) von Testsubstanzen und ihren Metaboliten, um Einblicke in die Stoffwechselkapazität der Leber und in die Aktivität von Enzymen und Transportern zu gewinnen. Die Leberfunktionstests werden nicht nur von zahlreichen Proband:innenmerkmalen, sondern auch von den Besonderheiten der Untersuchung beeinflusst. Eine zentrale Herausforderung besteht darin, die verschiedenen Faktoren, die das Ergebnis der Messungen beeinflussen, voneinander zu trennen, um ihren jeweiligen Einfluss auf das Messergebniss zu untersuchen. In dieser Arbeit wurde die Herausforderung durch Metaanalysen und physiologisch basierte Pharmakokinetik Modellierung (PBPK) angegangen. Es wurde eine offene Pharmakokinetik-Datenbank (PK-DB) entwickelt und PK-Daten für ein breites Spektrum von Testsubstanzen kuratiert. Meines Wissens enthält PK-DB derzeit den größten offenen PK-Datensatz zu Testsubstanzen. Der Datensatz ermöglichte die Identifizierung und Quantifizierung von demografischen und rassischen Bias (Geschlecht, ethnische Zugehörigkeit, Alter, Gesundheitszustand), Meldefehlern und Unstimmigkeiten in der Literatur. Auf der Grundlage der Daten wurde eine Metaanalyse der PK von Koffein im Hinblick auf verschiedene Faktoren bzgl. Leberfunktion und CYP1A2-Aktivität durchgeführt. Insbesondere wurde das vorhandene Wissen über die Auswirkungen des Rauchens, der Einnahme oraler Verhütungsmittel, verschiedener Krankheiten und Begleitmedikationen auf die PK von Koffein durch Metaanalysen und Datenintegration konsolidiert. Ebenso wurde die Messgenauigkeit der Koffeinkonzentration in Bezug auf den Messprotokol analysiert. Darüber hinaus wurde der Einfluss des CYP2D6-Polymorphismus untersucht. Hierzu wurde ein PBPK-Modell für Dextromethorphan und seine Metaboliten Dextrorphan und Dextrorphan O-Glucuronid entwickelt und mit den PK-Daten kalibriert und validiert. / Cytochrome P450 (CYP) phenotyping and dynamic liver function testing are essential methods in clinical practice. These methods utilize the pharmacokinetics (PK) of test substances and their metabolites to gain insight into the liver's metabolic capacity and the activity of enzymes and transporters. Liver function tests are not only influenced by numerous characteristics of a studied subject but also by the specifics of individual study procedures. A key challenge is to disentangle the various factors which influence the outcome of the measurements from each other to study their influence on the dynamic liver function and CYP phenotype. In this work, the challenge was addressed through meta-analysis and physiologically based pharmacokinetic modeling. As a foundation, an open pharmacokinetics database was developed and pharmacokinetics data were curated for a wide range of test substances. To my knowledge, PK-DB currently contains the largest open pharmacokinetic dataset on substances used for phenotyping and dynamical liver function testing. The dataset allowed for identifying and quantifying demographic and racial bias (sex, ethnicity, age, health), reporting errors, and inconsistencies in pharmacokinetic literature. Based on the data, a caffeine pharmacokinetics meta-analysis was conducted concerning various factors affecting liver function and CYP1A2 activity. In particular, meta-analysis and data integration solidified existing knowledge on the effects of smoking, oral contraceptives, multiple diseases, and co-medications on caffeine pharmacokinetics. Similarly, the measurement accuracy of caffeine concentration was investigated with respect to various aspects of the measurement protocol. In addition, the impact of CYP2D6 polymorphism was investigated. Therefore, a PBPK model of dextromethorphan (DXM) and its metabolites dextrorphan (DXO) and dextrorphan O-glucuronide (DXO-Glu) was developed, and calibrated, and validated with pharmacokinetics data.

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.

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Vancomycin is an antibiotic used for the treatment of systemic infections. It is given intravenously usually every twelve or twenty-four hours. This particular drug has a medium level of boundedness, with approximately fty percent of the drug being free and thus physiologically eective. A physiologically-based pharmacokinetic (PBPK) model was used to better understand the absorption, distribution, and elimination of the drug. Using optimal parameters, the model could be used in the future to test how various factors, such as BMI or excretion levels, might aect the concentration of the antibiotic.

Levofloxacin is in a class of antibiotics known as fluoroquinolones, which treat infections by killing the bacteria that cause them. A physiologically-based pharmacokinetic (PBPK) model was developed to investigate the uptake, distribution, and elimination of Levofloxacin after a single dose. PBPK modeling uses parameters such as body weight, blood flow rates, partition coefficients, organ volumes, and several other parameters in order to model the distribution of a particular drug throughout the body. Levofloxacin is only moderately bound in human blood plasma, and, thus, for the purposes of this paper, linear bonding is incorporated into the model because the free or unbound portion of the drug is the only portion that is considered to be medicinally effective. Parameter estimation is then used to estimate the two unknown parameters given clinical data from literature on the total concentration of Levofloxacin in the blood over time. Once an adequate model is generated, the effects of varying Body Mass Index are tested for the absorption and distribution of Levofloxacin throughout the body.

Background: Prenatal exposure to perfluoroalkyl substances (PFAS) has been associated with lower birth weight in epidemiologic studies. This association could be attributable to glomerular filtration rate (GFR), which is related to PFAS concentration and birth weight. Objectives: We used a physiologically based pharmacokinetic (PBPK) model of pregnancy to assess how much of the PFAS–birth weight association observed in epidemiologic studies might be attributable to GFR. Methods: We modified a PBPK model to reflect the association of GFR with birth weight (estimated from three studies of GFR and birth weight) and used it to simulate PFAS concentrations in maternal and cord plasma. The model was run 250,000 times, with variation in parameters, to simulate a population. Simulated data were analyzed to evaluate the association between PFAS levels and birth weight due to GFR. We compared simulated estimates with those from a meta-analysis of epidemiologic data. Results: The reduction in birth weight for each 1-ng/mL increase in simulated cord plasma for perfluorooctane sulfonate (PFOS) was 2.72 g (95% CI: –3.40, –2.04), and for perfluorooctanoic acid (PFOA) was 7.13 g (95% CI: –8.46, –5.80); results based on maternal plasma at term were similar. Results were sensitive to variations in PFAS level distributions and the strength of the GFR–birth weight association. In comparison, our meta-analysis of epidemiologic studies suggested that each 1-ng/mL increase in prenatal PFOS and PFOA levels was associated with 5.00 g (95% CI: –21.66, –7.78) and 14.72 g (95% CI: –8.92, –1.09) reductions in birth weight, respectively. Conclusion: Results of our simulations suggest that a substantial proportion of the association between prenatal PFAS and birth weight may be attributable to confounding by GFR and that confounding by GFR may be more important in studies with sample collection later in pregnancy.