Profile monitoring is a well-known approach used in statistical process control where the quality of the product or process is characterized by a profile or a relationship between a response variable and one or more explanatory variables. Profile monitoring is conducted over two phases, labeled as Phase I and Phase II. In Phase I profile monitoring, regression methods are used to model each profile and to detect the possible presence of out-of-control profiles in the historical data set (HDS). The out-of-control profiles can be detected by using the statis-tic. However, previous methods of calculating the statistic are based on using all the data in the HDS including the data from the out-of-control process. Consequently, the ability of using this method can be distorted if the HDS contains data from the out-of-control process. This work provides a new profile monitoring methodology for Phase I analysis. The proposed method, referred to as the cluster-based profile monitoring method, incorporates a cluster analysis phase before calculating the statistic. Before introducing our proposed cluster-based method in profile monitoring, this cluster-based method is demonstrated to work efficiently in robust regression, referred to as cluster-based bounded influence regression or CBI. It will be demonstrated that the CBI method provides a robust, efficient and high breakdown regression parameter estimator. The CBI method first represents the data space via a special set of points, referred to as anchor points. Then a collection of single-point-added ordinary least squares regression estimators forms the basis of a metric used in defining the similarity between any two observations. Cluster analysis then yields a main cluster containing at least half the observations, with the remaining observations comprising one or more minor clusters. An initial regression estimator arises from the main cluster, with a group-additive DFFITS argument used to carefully activate the minor clusters through a bounded influence regression frame work. CBI achieves a 50% breakdown point, is regression equivariant, scale and affine equivariant and distributionally is asymptotically normal. Case studies and Monte Carlo results demonstrate the performance advantage of CBI over other popular robust regression procedures regarding coefficient stabil-ity, scale estimation and standard errors. The cluster-based method in Phase I profile monitoring first replaces the data from each sampled unit with an estimated profile, using some appropriate regression method. The estimated parameters for the parametric profiles are obtained from parametric models while the estimated parameters for the nonparametric profiles are obtained from the p-spline model. The cluster phase clusters the profiles based on their estimated parameters and this yields an initial main cluster which contains at least half the profiles. The initial estimated parameters for the population average (PA) profile are obtained by fitting a mixed model (parametric or nonparametric) to those profiles in the main cluster. Profiles that are not contained in the initial main cluster are iteratively added to the main cluster provided their statistics are "small" and the mixed model (parametric or nonparametric) is used to update the estimated parameters for the PA profile. Those profiles contained in the final main cluster are considered as resulting from the in-control process while those not included are considered as resulting from an out-of-control process. This cluster-based method has been applied to monitor both parametric and nonparametric profiles. A simulated example, a Monte Carlo study and an application to a real data set demonstrates the detail of the algorithm and the performance advantage of this proposed method over a non-cluster-based method is demonstrated with respect to more accurate estimates of the PA parameters and improved classification performance criteria. When the profiles can be represented by vectors, the profile monitoring process is equivalent to the detection of multivariate outliers. For this reason, we also compared our proposed method to a popular method used to identify outliers when dealing with a multivariate response. Our study demonstrated that when the out-of-control process corresponds to a sustained shift, the cluster-based method using the successive difference estimator is clearly the superior method, among those methods we considered, based on all performance criteria. In addition, the influence of accurate Phase I estimates on the performance of Phase II control charts is presented to show the further advantage of the proposed method. A simple example and Monte Carlo results show that more accurate estimates from Phase I would provide more efficient Phase II control charts. / Ph. D.

La grande fréquence des nodules thyroïdiens et la relative agressivité des traitements conventionnels ont motivé l'étude d'une méthode non invasive utilisant des Ultrasons Focalisés (HIFU). Matériel et méthodes : Les HIFU ont été testés initialement sur un modèle de brebis afin de réaliser une lésion thyroïdienne. Ces études animales ont été suivies de trois études cliniques sur des patients porteurs de nodules thyroïdiens. L'appareil utilisé associe un système d'imagerie échographique et un système de tir. Résultats : Le réglage des paramètres de tir et la mise au point de plusieurs prototypes chez l'animal a permis d'obtenir l'autorisation du comité d'éthique pour les expérimentations humaines. Ces essais ont démontré la capacité des HIFU à détruire des nodules thyroïdiens. Le dernier appareil mis au point a obtenu le marquage CE. Conclusion : Cette technique permet de réaliser une nécrose localisée dans un lobe thyroïdien et de détruire des nodules. Ces résultats doivent être confirmés par des études plus larges, mais ont été assez encourageants pour justifier la création d'une entreprise dédiée à la mise au point d'un appareil spécifique en collaboration avec l'INSERM / -

Introduction: La stomatite prothétique est une condition inflammatoire chronique de la muqueuse buccale recouverte par une prothèse. Cette maladie est considérée comme la lésion buccale la plus fréquente chez les porteurs de prothèses amovibles. Des études récentes sur l'étiologie de la stomatite prothétique suggèrent que des traitements basés sur la réduction de l'inflammation seraient efficaces dans le traitement de cette maladie. Objectifs: Évaluer l'efficacité du brossage du palais dans le traitement de la stomatite prothétique. Méthodes: Quarante-huit participants (âge moyen : 66,0 ± 11,2 ans) avec un diagnostic de stomatite prothétique, ont été sélectionnés à partir d’un examen préalable de 143 individus, afin de participer à cet essai clinique de phase I à deux centres, réalisé selon un devis de type pré-test/post-test à un seul groupe. L'intervention a consisté en un brossage du palais avec une brosse manuelle après chaque repas et avant le coucher. Des examens cliniques et microbiologiques ont été effectués avant le traitement, et à 1 mois et 3 mois de suivi. Des données supplémentaires ont été obtenues par l'utilisation d'un questionnaire validé. Les résultats primaires et secondaires étaient, respectivement, la rémission de stomatite prothétique et la diminution du nombre de colonies de Candida. Des tests statistiques descriptifs et non paramétriques ont été menés pour analyser les données. Résultats: À 3 mois de suivi, 10,4 % des participants ont été guéris et 70,8 % ont eu une amélioration clinique de la stomatite prothétique grâce au brossage du palais. Une réduction statistiquement significative de la surface et de l’intensité de l’inflammation après 3 mois de brossage du palais a été démontrée (p < 0,0001). L’ampleur de l’effet a varié d’un effet modéré à important (0,34 à 0,54) selon la classification utilisée pour le diagnostique de la stomatite prothétique. De plus, le nombre de colonies de Candida, recueillies par sonication des prothèses et par échantillonnage du palais, a diminué de manière statistiquement significative après 3 mois de brossage (p ≤ 0,05). Conclusion: Les résultats de cette étude suggèrent que le brossage du palais est efficace comme traitement de la stomatite prothétique. / Introduction: Denture-related erythematous stomatitis (denture stomatitis) is a chronic inflammation of the oral mucosa covered by a removable prosthesis. This disease is considered the most prevalent mucosal lesion associated with prosthesis use. Recent research on the etiology of denture stomatitis suggests that treatments based on the reduction of the inflammation are effective in the management of this disease. Objectives: To assess the efficacy of palatal brushing in the treatment of denture stomatitis. Methods: After screening 143 individuals with a potential diagnosis of denture stomatitis, 48 (mean age: 66.0 ± 11.2 years) were enrolled in a phase-I two-center clinical trial with one-group pre-test/post-test design. The intervention of interest was manual palatal brushing after each meal and before bedtime. Clinical and microbiological examinations were performed at baseline, 1 month and 3 months post-intervention. Additional data were obtained by the use of a validated questionnaire. The primary and secondary outcomes were the remission of denture stomatitis and the diminution of Candida Colony-Forming Units (CFUs), respectively. Descriptive and non-parametric statistical tests were conducted to analyze the data. Results: At 3-month follow-up, denture stomatitis was completely cured in 10.4 % of the study participants, and 70.8 % of denture wearers showed improvement in the clinical signs of denture stomatitis. There was a significant reduction in the area and severity of the palatal inflammation at 3-month follow-up (p < 0.0001). The effect size ranged from medium to large (0.34 to 0.54), depending on the classification used for the diagnosis of denture stomatitis. Furthermore, a significant reduction in the number of Candida CFUs isolated from the palatal mucosa and dentures was observed (p ≤ 0.05). Conclusion: The results of this study suggest that palatal brushing is effective in the treatment of denture stomatitis.

Le but principal d'un essai de phase I en oncologie est d'identifier, parmi un nombre fini de doses, la dose à recommander d'un nouveau traitement pour les évaluations ultérieures, sur un petit nombre de patients.Le critère de jugement principal est classiquement la toxicité. Bien que la toxicité soit mesurée pour différents organes sur une échelle gradée, elle est généralement réduite à un indicateur binaire appelé "toxicité dose-limitante" (DLT). Cette simplification très réductrice est problématiqu, en particulier pour les thérapies, dites "thérapies ciblées", associées à peu de DLTs.Dans ce travail, nous proposons un score de toxicité qui résume l'ensemble des toxicités observées chez un patient. Ce score, appelé TTP pour Total Toxicity Profile, est défini par la norme euclidienne des poids associés aux différents types et grades de toxicités possibles. Les poids reflètent l'importance clinique des différentes toxicités.\\ Ensuite, nous proposons la méthode de recherche de dose, QLCRM pour Quasi-Likelihood Continual Reassessment Method, modélisant la relation entre la dose et le score de toxicité TTP à l'aide d'une régression logistique dans un cadre fréquentiste.A l'aide d'une étude de simulation, nous comparons la performance de cette méthode à celle de trois autres approches utilisant un score de toxicité : i) la méthode de Yuan et al. (QCRM) basée sur un modèle empirique pour estimer, dans un cadre bayésien, la relation entre la dose et le score, ii) la méthode d'Ivanova et Kim (UA) dérivée des méthodes algorithmiques et utilisant une régression isotonique pour estimer la dose à recommander en fin d'essai, iii) la méthode de Chen et al. (EID) basée sur une régression isotonique pour l'escalade de dose et l'identification de la dose à recommander. Nous comparons ensuite ces quatre méthodes utilisant le score de toxicité aux méthodes CRM basées sur le critère binaire DLT. Nous étudions également l'impact de l'erreur de classement des grades pour les différentes méthodes, guidées par le score de toxicité ou par la DLT.Enfin, nous illustrons le processus de construction du score de toxicité ainsi que l'application de la méthode QLCRM dans un essai réel de phase I. Dans cette application, nous avons utilisé une approche Delphi pour déterminer avec les cliniciens la matrice des poids et le score de toxicité jugé acceptable.Les méthodes QLCRM, QCRM, UA et EID présentent une bonne performance en termes de capacité à identifier correctement la dose à recommander et de contrôle du surdosage. Dans un essai incluant 36 patients, le pourcentage de sélection correcte de la dose à recommander obtenu avec les méthodes QLCRM et QCRM varie de 80 à 90% en fonction des situations. Les méthodes basées sur le score TTP sont plus performantes et plus robustes aux erreurs de classement des grades que les méthodes CRM basées sur le critère binaire DLT.Dans l'application rétrospective, le processus de construction du score apparaît faisable facilement. Cette étude nous a conduits à proposer des recommandations pour guider les investigateurs et faciliter l'utilisation de cette approche dans la pratique.En conclusion, la méthode QLCRM prenant en compte l'ensemble des toxicités s'avère séduisante pour les essais de phase I évaluant des médicaments associés à peu de DLTs a priori, mais avec des toxicités multiples modérées probables. / The aim of a phase I oncology trial is to identify a dose with an acceptable safety level. Most phase I designs use the Dose-Limiting Toxicity (DLT), a binary endpoint, to assess the level of toxicity. DLT might be an incomplete endpoint for investigating molecularly targeted therapies as a lot of useful toxicity information is discarded.In this work, we propose a quasi-continuous toxicity score, the Total Toxicity Profile (TTP), to measure quantitatively and comprehensively the overall burden of multiple toxicities. The TTP is defined as the Euclidean norm of the weights of toxicities experienced by a patient, where the weights reflect the relative clinical importance of each type and grade of toxicity.We propose then a dose-finding design, the Quasi-Likelihood Continual Reassessment Method (QLCRM), incorporating the TTP-score into the CRM, with a logistic model for the dose-toxicity relationship in a frequentist framework. Using simulations, we compare our design to three existing designs for quasi-continuous toxicity scores: i) the QCRM design, proposed by Yuan et al., with an empiric model for the dose-toxicity relationship in a Bayesian framework, ii) the UA design of Ivanova and Kim derived from the "up-and-down" methods for the dose-escalation process and using an isotonic regression to estimate the recommended dose at the end of the trial, and iii) the EID design of Chen et al. using the isotonic regression for the dose-escalation process and for the identification of the recommended dose.We also perform a simulation study to evaluate the TTP-driven methods in comparison to the classical DLT-driven CRM. We then evaluate the robustness of these designs in a setting where grades can be misclassified.In the last part of this work, we illustrate the process of building the TTP-score and the application of the QLCRM method through the example of a paediatric trial. In this study, we have used the Delphi method to elicit the weights and the target toxicity-score considered as an acceptable toxicity measure.All designs using the TTP-score to identify the recommended dose had good performance characteristics for most scenarios, with good overdosing control. For a sample size of 36, the percentage of correct selection for the QLCRM ranged from 80 to 90%, with similar results for the QCRM design. Simulation study demonstrates also that score-driven designs present an improved performance and robustness compared to conventional DLT-driven designs. In the retrospective application of erlotinib trial, the consensus weights as well as the target-TTP were easily obtained, confirming the feasibility of the process. Some guidelines to facilitate the process in a real clinical trial for a better practice of this approach are suggested.The QLCRM method based on the TTP-endpoint combining multiple graded toxicities is an appealing alternative to the conventional dose-finding designs, especially in the context of molecularly targeted agents.

Introduction: La stomatite prothétique est une condition inflammatoire chronique de la muqueuse buccale recouverte par une prothèse. Cette maladie est considérée comme la lésion buccale la plus fréquente chez les porteurs de prothèses amovibles. Des études récentes sur l'étiologie de la stomatite prothétique suggèrent que des traitements basés sur la réduction de l'inflammation seraient efficaces dans le traitement de cette maladie. Objectifs: Évaluer l'efficacité du brossage du palais dans le traitement de la stomatite prothétique. Méthodes: Quarante-huit participants (âge moyen : 66,0 ± 11,2 ans) avec un diagnostic de stomatite prothétique, ont été sélectionnés à partir d’un examen préalable de 143 individus, afin de participer à cet essai clinique de phase I à deux centres, réalisé selon un devis de type pré-test/post-test à un seul groupe. L'intervention a consisté en un brossage du palais avec une brosse manuelle après chaque repas et avant le coucher. Des examens cliniques et microbiologiques ont été effectués avant le traitement, et à 1 mois et 3 mois de suivi. Des données supplémentaires ont été obtenues par l'utilisation d'un questionnaire validé. Les résultats primaires et secondaires étaient, respectivement, la rémission de stomatite prothétique et la diminution du nombre de colonies de Candida. Des tests statistiques descriptifs et non paramétriques ont été menés pour analyser les données. Résultats: À 3 mois de suivi, 10,4 % des participants ont été guéris et 70,8 % ont eu une amélioration clinique de la stomatite prothétique grâce au brossage du palais. Une réduction statistiquement significative de la surface et de l’intensité de l’inflammation après 3 mois de brossage du palais a été démontrée (p < 0,0001). L’ampleur de l’effet a varié d’un effet modéré à important (0,34 à 0,54) selon la classification utilisée pour le diagnostique de la stomatite prothétique. De plus, le nombre de colonies de Candida, recueillies par sonication des prothèses et par échantillonnage du palais, a diminué de manière statistiquement significative après 3 mois de brossage (p ≤ 0,05). Conclusion: Les résultats de cette étude suggèrent que le brossage du palais est efficace comme traitement de la stomatite prothétique. / Introduction: Denture-related erythematous stomatitis (denture stomatitis) is a chronic inflammation of the oral mucosa covered by a removable prosthesis. This disease is considered the most prevalent mucosal lesion associated with prosthesis use. Recent research on the etiology of denture stomatitis suggests that treatments based on the reduction of the inflammation are effective in the management of this disease. Objectives: To assess the efficacy of palatal brushing in the treatment of denture stomatitis. Methods: After screening 143 individuals with a potential diagnosis of denture stomatitis, 48 (mean age: 66.0 ± 11.2 years) were enrolled in a phase-I two-center clinical trial with one-group pre-test/post-test design. The intervention of interest was manual palatal brushing after each meal and before bedtime. Clinical and microbiological examinations were performed at baseline, 1 month and 3 months post-intervention. Additional data were obtained by the use of a validated questionnaire. The primary and secondary outcomes were the remission of denture stomatitis and the diminution of Candida Colony-Forming Units (CFUs), respectively. Descriptive and non-parametric statistical tests were conducted to analyze the data. Results: At 3-month follow-up, denture stomatitis was completely cured in 10.4 % of the study participants, and 70.8 % of denture wearers showed improvement in the clinical signs of denture stomatitis. There was a significant reduction in the area and severity of the palatal inflammation at 3-month follow-up (p < 0.0001). The effect size ranged from medium to large (0.34 to 0.54), depending on the classification used for the diagnosis of denture stomatitis. Furthermore, a significant reduction in the number of Candida CFUs isolated from the palatal mucosa and dentures was observed (p ≤ 0.05). Conclusion: The results of this study suggest that palatal brushing is effective in the treatment of denture stomatitis.

No description available.

Les Phases I sont un domaine des essais cliniques dans lequel les statisticiens ont encore beaucoup à apporter. Depuis trente ans, ce secteur bénéficie d'un intérêt croissant et de nombreuses méthodes ont été proposées pour gérer l'allocation séquentielle des doses aux patients intégrés à l'étude. Durant cette Phase, il s'agit d'évaluer la toxicité, et s'adressant à des patients gravement atteints, il s'agit de maximiser les effets curatifs du traitement dont les retours toxiques sont une conséquence. Parmi une gamme de doses, on cherche à déterminer celle dont la probabilité de toxicité est la plus proche d'un seuil souhaité et fixé par les praticiens cliniques. Cette dose est appelée la MTD (maximum tolerated dose). La situation canonique dans laquelle sont introduites la plupart des méthodes consiste en une gamme de doses finie et ordonnée par probabilité de toxicité croissante. Dans cette thèse, on introduit une modélisation très générale du problème, la SPM (semi-parametric methods), qui recouvre une large classe de méthodes. Cela permet d'aborder des questions transversales aux Phases I. Quels sont les différents comportements asymptotiques souhaitables? La MTD peut-elle être localisée? Comment et dans quelles circonstances? Différentes paramétrisations de la SPM sont proposées et testées par simulations. Les performances obtenues sont comparables, voir supérieures à celles des méthodes les plus éprouvées. Les résultats théoriques sont étendus au cas spécifique de l'ordre partiel. La modélisation de la SPM repose sur un traitement hiérarchique inférentiel de modèles satisfaisant des contraintes linéaires de paramètres inconnus. Les aspects théoriques de cette structure sont décrits dans le cas de lois à supports discrets. Dans cette circonstance, de vastes ensembles de lois peuvent aisément être considérés, cela permettant d'éviter les cas de mauvaises spécifications. / Phase I clinical trials is an area in which statisticians have much to contribute. For over 30 years, this field has benefited from increasing interest on the part of statisticians and clinicians alike and several methods have been proposed to manage the sequential inclusion of patients to a study. The main purpose is to evaluate the occurrence of dose limiting toxicities for a selected group of patients with, typically, life threatening disease. The goal is to maximize the potential for therapeutic success in a situation where toxic side effects are inevitable and increase with increasing dose. From a range of given doses, we aim to determine the dose with a rate of toxicity as close as possible to some threshold chosen by the investigators. This dose is called the MTD (maximum tolerated dose). The standard situation is where we have a finite range of doses ordered with respect to the probability of toxicity at each dose. In this thesis we introduce a very general approach to modeling the problem - SPM (semi-parametric methods) - and these include a large class of methods. The viewpoint of SPM allows us to see things in, arguably, more relevant terms and to provide answers to questions such as asymptotic behavior. What kind of behavior should we be aiming for? For instance, can we consistently estimate the MTD? How, and under which conditions? Different parametrizations of SPM are considered and studied theoretically and via simulations. The obtained performances are comparable, and often better, to those of currently established methods. We extend the findings to the case of partial ordering in which more than one drug is under study and we do not necessarily know how all drug pairs are ordered. The SPM model structure leans on a hierarchical set-up whereby certain parameters are linearly constrained. The theoretical aspects of this structure are outlined for the case of distributions with discrete support. In this setting the great majority of laws can be easily considered and this enables us to avoid over restrictive specifications than can results in poor behavior.

My MSc thesis is focused on parametric designs of Phase I clinical trials, using the continual reassessment method. A parametric model with unknown parameters is assumed. The observations are either toxic or nontoxic. Observations of toxicities are used to update the posterior distribution. Dose selection for the next patient is based on the estimated toxicity probability. The objective is to identify the maximum tolerated dose to be used in Phase II clinical trials. We introduce a new class of parametric functions for the continual reassessment method. This class is formed with the cumulative distribution function of the normal distribution. The major advantage is that we can choose different normal distributions to model different toxicity probability functions. We conduct simulation studies and compare our new design with the existing parametric designs, and have found that our design performs better by choosing the appropriate values of the mean and variance. / October 2016

Phase I clinical trials in oncology aim to evaluate the toxicity risk of new therapies and identify a safe but also effective dose for future studies. Traditional Phase I trials of chemotherapies focus on estimating the maximum tolerated dose (MTD). The rationale for finding the MTD is that better therapeutic effects are expected at higher dose levels as long as the risk of severe toxicity is acceptable. With the advent of a new generation of cancer treatments such as the molecularly targeted agents (MTAs) and immunotherapies, higher dose levels no longer guarantee increased therapeutic effects, and the focus has shifted to estimating the optimal biological dose (OBD). The OBD is a dose level with the highest biologic activity with acceptable toxicity. The search for OBD requires joint evaluation of toxicity and efficacy. Although several seamleass phase I/II designs have been published in recent years, there is not a consensus regarding an optimal design and further improvement is needed for some designs to be widely used in practice. In this dissertation, we propose a modification to an existing seamless phase I/II design by Wages and Tait (2015) for locating the OBD based on binary outcomes, and extend it to time to event (TITE) endpoints. While the original design showed promising results, we hypothesized that performance could be improved by replacing the original adaptive randomization stage with a different randomization strategy. We proposed to calculate dose assigning probabilities by averaging all candidate models that fit the observed data reasonably well, as opposed to the original design that based all calculations on one best-fit model. We proposed three different strategies to select and average among candidate models, and simulations are used to compare the proposed strategies to the original design. Under most scenarios, one of the proposed strategies allocates more patients to the optimal dose while improving accuracy in selecting the final optimal dose without increasing the overall risk of toxicity. We further extend this design to TITE endpoints to address a potential issue of delayed outcomes. The original design is most appropriate when both toxicity and efficacy outcomes can be observed shortly after the treatment, but delayed outcomes are common, especially for efficacy endpoints. The motivating example for this TITE extension is a Phase I/II study evaluating optimal dosing of all-trans retinoic acid (ATRA) in combination with a fixed dose of daratumumab in the treatment of relapsed or refractory multiple myeloma. The toxicity endpoint is observed in one cycle of therapy (i.e., 4 weeks) while the efficacy endpoint is assessed after 8 weeks of treatment. The difference in endpoint observation windows causes logistical challenges in conducting the trial, since it is not acceptable in practice to wait until both outcomes for each participant have been observed before sequentially assigning the dose of a newly eligible participant. The result would be a delay in treatment for patients and undesirably long trial duration. To address this issue, we generalize the time-to-event continual reassessment method (TITE-CRM) to bivariate outcomes with potentially non-monotonic dose-efficacy relationship. Simulation studies show that the proposed TITE design maintains similar probability in selecting the correct OBD comparing to the binary original design, but the number of patients treated at the OBD decreases as the rate of enrollment increases. We also develop an R package for the proposed methods and document the R functions used in this research. The functions in this R package assist implementation of the proposed randomization strategy and design. The input and output format of these functions follow similar formatting of existing R packages such as "dfcrm" or "pocrm" to allow direct comparison of results. Input parameters include efficacy skeletons, prior distribution of any model parameters, escalation restrictions, design method, and observed data. Output includes recommended dose level for the next patient, MTD, estimated model parameters, and estimated probabilities of each set of skeletons. Simulation functions are included in this R package so that the proposed methods can be used to design a trial based on certain parameters and assess performance. Parameters of these scenarios include total sample size, true dose-toxicity relationship, true dose-efficacy relationship, patient recruit rate, delay in toxicity and efficacy responses.

Acrylamide is an industrially produced chemical with known neurotoxic, reproductive toxin and carcinogenic effects. The carcinogenicity associated with acrylamide is mostly attributed to its metabolism by liver CYP2E1. However, studies investigating the effects of acrylamide on CYP2E1 enzyme are limited. In this study, it was aimed to investigate in vivo interaction of carcinogenic acrylamide on microsomal cytochrome P450 enzyme activities, and protein levels, and on cytosolic NQO1 and GST enzyme activities of rabbit liver, kidney and lung of acrylamide-treated rabbits. The in vivo protective effect of resveratrol, a phenolic compound, was also investigated on acrylamide toxicity. New Zealand male rabbits were treated with acrylamide and resveratrol, separately in different doses and conditions. Their combined effects were also investigated. CYP2E1-dependent p-Nitrophenol hydroxylase, NDMA N-demethylase and aniline 4-hydroxylase activities were found to be significantly increased in acrylamide-treated rabbit liver (1.80-3.0 fold) and kidney (1.6-fold). Rabbit liver and kidney CYP2E1 protein levels (determined by western blot analyisis) also increased approximately 2-fold due to acrylamide treatment. In rabbit liver, resveratrol was found significantly effective in decreasing both acrylamide-induced CYP2E1-dependent enzyme activities (approximately 1.5-1.80 fold) and CYP2E1 protein levels (approximately 1.5-1.70 fold). Additionally, resveratrol significantly decreased acrylamide-induced CYP2E1 protein level (2-2.5 fold) in rabbit kidney. However, no significant change was observed in rabbit lung CYP2E1-dependent enzyme activities and CYP2E1 protein levels due to acrylamide, resveratrol or their combined treatments. Furthermore, it was found that acrylamide treatment significantly increased CYP3A6-dependent erythromycin N-demethylase enzyme activity (1.85-fold) and CYP3A6 protein levels in rabbit liver (1.69-fold). No change was observed in CYP2B4-dependent benzphetamine N-demethylase enzyme activities of rabbit liver, kidney and lung by in vivo acrylamide, resveratrol or their combined treatments. Moreover, total GST and GST-Mu activities of rabbit kidney (1.5-fold, respectively) and total GST activity of rabbit lung (1.6-fold) were increased significantly only in resveratrol treated group. NQO1 enzyme activity of rabbit kidney was significantly increased by acrylamide treatment (1.6-fold). The results of the present study have demonstrated for the first time that acrylamide induces rabbit liver and kidney CYP2E1-dependent enzyme activities and CYP2E1 protein levels. The induction of CYP2E1 enzyme activity and protein level by acrylamide treatment can stimulate formation of other toxic compounds and procarcinogens metabolized by CYP2E1 which in turn further potentiates the risk of hepatotoxicity, mutagenicity and carcinogenicity. In the present study, it was also demonstrated for the first time that acrylamide treatment also increases CYP3A6 enzyme activity in rabbit liver which may lead to alterations in drug metabolism. The results of this study have also suggested that resveratrol may have protective effects on acrylamide induced toxicity / however, further in vivo studies are required to clarify the effect of resveratrol on both acrylamide-induced toxicity and anti-oxidant enzymes.