Dissertationen: „Dose-Response modeling“

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Leininger, Thomas J. „An Adaptive Bayesian Approach to Dose-Response Modeling“. Diss., CLICK HERE for online access, 2009. http://contentdm.lib.byu.edu/ETD/image/etd3325.pdf.

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Ås, Joel. „Active dose selection and dose-response modeling for quantitative high-throughput screening (qHTS)“. Thesis, Uppsala universitet, Cancerfarmakologi och beräkningsmedicin, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-300682.

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This master thesis studies the potential benefit of iterative selection of the concentrations evaluated when building mathematical dose-response curves (and response surfaces when there are two drugs) using experimental measurements. The reference alternative is to use a standard two-fold dilution series or ten-fold dilution series measured in replicates. The standard 4-parameter Hill dose-response model is used as a reference and for simulations. Models to screen for synergy between two different substances are also developed in this thesis.

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Adamus-Górka, Magdalena. „Improved dose response modeling for normal tissue damage and therapy optimization“. Doctoral thesis, Stockholm University, Medical Radiation Physics (together with KI), 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-7433.

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The present thesis is focused on the development and application of dose response models for radiation therapy. Radiobiological models of tissue response to radiation are an integral part of the radiotherapeutic process and a powerful tool to optimize tumor control and minimize damage to healthy tissues for use in clinical trials. Ideally, the models could work as a historical control arm of a clinical trial eliminating the need to randomize patents to suboptimal therapies. In the thesis overview part, some of the basic properties of the dose response relation are reviewed and the most common radiobiological dose-response models are compared with regard to their ability to describe experimental dose response data for rat spinal cord using the maximum likelihood method. For vascular damage the relative seriality model was clearly superior to the other models, whereas for white matter necrosis all models were quite good except possibly the inverse tumor and critical element models. The radiation sensitivity, seriality and steepness of the dose-response relation of the spinal cord is found to vary considerably along its length. The cervical region is more radiation sensitive, more parallel, expressing much steeper dose-response relation and more volume dependent probability of inducing radiation myelitis than the thoracic part. The higher number of functional subunits (FSUs) consistent with a higher amount of white matter close to the brain may be responsible for these phenomena. With strongly heterogeneous dose delivery and due to the random location of FSUs, the effective size of the FSU and the mean dose deposited in it are of key importance and the radiation sensitivity distribution of the FSU may be an even better descriptor for the response of the organ. An individual optimization of a radiation treatment has the potential to increase the therapeutic window and improve cure for a subgroup of patients.

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Adamus-Górka, Magdalena. „Improved dose response modeling for normal tissue damage and therapy optimization /“. Stockholm ; Solna : Medical Radiation Physics, Stockholm University and Karolinska institutet, 2008. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-7433.

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5

Eklund, Karin. „Modeling Silicon Diode Dose Response in Radiotherapy Fields using Fluence Pencil Kernels“. Doctoral thesis, Uppsala universitet, Avdelningen för sjukhusfysik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-120581.

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In radiotherapy, cancer is treated with ionizing radiation, most commonly bremsstrahlung photons from electrons of several MeV. Secondary electrons produced in photon-interactions results in dose deposition. The treatment response is low for low doses, raises sharply for normal treatment doses and saturates at higher doses. This response pattern applies to both eradication of tumors and to complications in healthy tissues. Well controlled treatments require accurate dosimetry since the uncertainty in delivered dose will be magnified 1 to 5 times in treatment response variations. Techniques that superpose many small radiation fields to concentrate the dose to a localized target are becoming increasingly used. A detector with high spatial resolution suitable for such fields is a silicon diode. To maintain the current accuracy of the dosimetric calibration of 1.5%, diode measurements relative to this calibration should preferably be possible at 0.5% accuracy level. The main limitation of silicon diodes is their over-response to low-energy photons. This problem has been adressed with the insertion of a high atomic number filter in diodes. For modeling diode detector response one must quantify the spectral variations in the irradiated medium resulting from variations of the beam parameters. This requires understanding of the particle transport and can be achieved by Monte Carlo simulations. However, the small dimensions of the detector geometry compared to surrounding medium makes a direct application of Monte Carlo impractical due to the large amount of CPU time necessary to reach statistically satisfactory results. In this work a fast method for spectra calculations is used, based on superposition of mono-energetic fluence pencil kernels. Building on this base a general model for silicon response functions in photon fields is developed. The incident photons are bipartitioned into a low and a high energy component. The high energy part is treated with the Spencer-Attic cavity theory while the low energy part and scattered photons are treated with large cavity theory. The deviations from electron equilibrium are investigated and handled with correction factors. The result is used to correct unshielded diode measurements, with an overall uncertainty less than 0.5%, except for very small fields where the precision is around 1-2%, thus eliminating the need for less predictable shielded diodes for measurements in photon fields.

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Sand, Salomon. „Dose-response modeling : evaluation, application, and development of procedures for benchmark dose analysis in health risk assessment of chemical substances /“. Stockholm, 2005. http://diss.kib.ki.se/2005/91-7140-420-1/.

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7

Wessel, Michael Raymond. „Dose time response modeling of neurobehavioral screening data application of physiologically relevant parameters to describe dose dependent time of peak effects /“. [Tampa, Fla.] : University of South Florida, 2005. http://purl.fcla.edu/fcla/etd/SFE0001273.

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8

Toyinbo, Peter A. „On Effective and Efficient Experimental Designs for Neurobehavioral Screening Tests: The Choice of a Testing Time for Estimating the Time of Peak Effects“. [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000393.

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Wessel, Michael Raymond. „Dose Time Response Modeling of Neurobehavioral Screening Data: Application of Physiologically Relevant Parameters to Allow for Dose Dependent Time of Peak Effects“. Scholar Commons, 2005. https://scholarcommons.usf.edu/etd/911.

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In collaboration with the United States Environmental Protection Agency (USEPA), the University of South Florida Health Risk Methodology Group has developed dose-time-response models to characterize neurobehavioral response to chemical exposure. The application of dose-time-response models to neurobehavioral screening tests on laboratory animals allows for benchmark dose estimation to establish exposure limits in environmental risk assessment. This thesis has advanced dose-time-response modeling by generalizing a published toxico diffusion model to allow for dose dependent time of peak effects. To accomplish this, a biphasic model was developed which adopted the effect compartment model paradigm used in pharmacokinetics/pharmacodynamics to estimate a distributional rate constant to account for dose related variation in the time of peak effect. The biphasic model was able to describe dose-dependent time of peak effects as observed in the data on acute exposure to parathion and adequately predicted the observed response. However, the experimental design appeared insufficient in statistical power to confirm statistical significance for each parameter of interest. Motivated by the question of what design requirement might be necessary to validate the biphasic model, Monte Carlo simulation was adopted. Simulations were performed to assess the efficacy and efficiency of various experimental designs for detecting and evaluating some critical characteristics of the biphasic model, including the TOPE. The results of simulation suggest that the location of measurement times around the TOPE have important implications for assessing the statistical significance of the parameter that describes dose-dependent TOPE and that the mean squared error of the parameter estimator was improved most when testing times were chosen to bracket the TOPE. While dose dependent time of peak effects has underlying physiological mechanisms such as synergistic or capacity limited kinetics, the biphasic model estimates these physiological properties through a mathematical function which may be physiologically relevant but does not necessarily define physiological mechanisms underlying the response. However, if verified through further testing, the biphasic model may contribute to the USEPA’s aim of developing physiologically relevant dose-response models for assessing risk of neurotoxicity with repeated measurements of response.

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Davidson, Sarah E. „Alternative Approach to Dose-Response Modeling of Toxicogenomic Data with an Application in Risk Assessment of Engineered Nanomaterials“. University of Cincinnati / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1627666554729205.

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11

Herr, Lisa [Verfasser], Marco [Akademischer Betreuer] Durante und Barbara [Akademischer Betreuer] Drossel. „Modeling of time-dose-LET effects in the cellular response to radiation / Lisa Herr. Betreuer: Marco Durante ; Barbara Drossel“. Darmstadt : Universitäts- und Landesbibliothek Darmstadt, 2015. http://d-nb.info/1111910936/34.

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12

Josefsson, Albin, und Tore Berggren. „Rate of change in psychotherapy: A matter of patients : A study contrasting the dose-effect model and the good-enough level model using the CORE-OM in primary care and psychiatric care“. Thesis, Linköpings universitet, Psykologi, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-108486.

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Studies on relations between number of sessions and effect of psychotherapy have usually assumed a constant rate of change across different lengths of therapy, explained by a model called the dose-effect model. This assumption has been challenged by the good-enough level (GEL) model, which makes the prediction that the rate of change will vary as a function of total number of sessions. This study aimed to compare these models. We also assessed the relationship between reliable and clinically significant change (RCSI) and total dose of therapy. Participants were drawn from two datasets in the Swedish primary care (n = 640) and adult psychiatric care (n = 249). The participants made session-wise ratings on the Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM). Multilevel analyses indicated a better fit using the GEL-model, with some reservations concerning RCSI and patterns of change. The results may indicate a general lawful relationship that may have implications for future research, as well as psychotherapy practice and policy making.

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MORASCHINI, LUCA. „Likelihood free and likelihood based approaches to modeling and analysis of functional antibody titers with applications to group B Streptococcus vaccine development“. Doctoral thesis, Università degli Studi di Milano-Bicocca, 2015. http://hdl.handle.net/10281/76794.

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Opsonophagocytic killing assays (OPKA) are routinely used for the quantification of bactericidal antibodies against Gram-positive bacteria in clinical trial samples. The OPKA readout, the titer, is traditionally estimated using non-linear dose-response regressions as the highest serum dilution yielding a predefined threshold level of bacterial killing. Therefore, these titers depend on a specific killing threshold value and on a specific dose-response model. This thesis describes a novel OPKA titer definition, the threshold free titer, which preserves biological interpretability whilst not depending on any killing threshold. First, a model-free version of this titer is presented and shown to be more precise than the traditional threshold-based titers when using simulated and experimental group B Streptococcus (GBS) OPKA experimental data. Second, a model-based threshold-free titer is introduced to automatically take into account the potential saturation of the OPKA killing curve. The posterior distributions of threshold-based and threshold-free titers is derived for each analysed sample using importance sampling embedded within a Markov chain Monte Carlo sampler of the coefficients of a 4PL logistic dose-response model. The posterior precision of threshold-free titers is again shown to be higher than that of threshold-based titers. The biological interpretability and operational characteristics demonstrated here indicate that threshold-free titers can substantially improve the routine analysis of OPKA experimental and clinical data.

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Mickelson, Bryan K. „Client Change in Multi-Model Treatment: A Comparison of Change Trajectories in Group, Individual, and Conjoint Formats in a Counseling Center“. Diss., CLICK HERE for online access, 2008. http://contentdm.lib.byu.edu/ETD/image/etd2758.pdf.

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Azemar, Nathan. „Μοdélisatiοn des tοxicités οptiques induites par radiοthérapie avec faisceaux de prοtοns“. Electronic Thesis or Diss., Normandie, 2024. https://theses.hal.science/tel-04947852.

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La protonthérapie, grâce à sa capacité à délivrer des doses élevées aux tumeurs tout en épargnant les tissus sains, est une option thérapeutique privilégiée pour traiter des localisations proches des structures optiques. Cependant, les rayonnements peuvent endommager les voies visuelles et causer des déficits visuels sévères. Cette thèse vise à modéliser les toxicités optiques induites par la protonthérapie chez les patients traités pour des tumeurs de la tête et du cou. Le travail repose sur l’analyse de données dosimétriques et paracliniques collectées auprès de 223 patients traités par protonthérapie au Centre François Baclesse et suivis au CHU de Caen. Une base de données multicentrique a été constituée, incluant les dosimétries, ainsi que les résultats des examens paracliniques (champ visuel, tomographie par cohérence optique et potentiels évoqués visuels). Un modèle relationnel a été développé pour établir un lien entre les résultats de champ visuel et la dose reçue par les organes visuels. Cette modélisation a mis en lumière les difficultés d'association des points du champ visuel avec les structures des voies optiques, en raison de la petite taille des structures, des incertitudes de segmentation et des mouvements des patients. Ce constat nous a conduit à mener une réduction de données et à évaluer les incertitudes de ces dernières. Ces analyses ont révélé les effets immédiats du traitement sur les examens paracliniques, ainsi que leurs évolutions dans le temps. Ces travaux ouvrent la voie à l’utilisation de modèles géométriques pour anticiper les complications visuelles et ainsi optimiser la prise en charge des patients
Proton therapy, with its ability to deliver high doses to tumors while sparing healthy tissues, is a preferred therapeutic option for treating tumors located near optical structures. However, radiation exposure can damage visual pathways, leading to severe visual deficits. This thesis aims to model the optical toxicities induced by proton therapy in patients treated for head and neck tumors. This work is based on the analysis of dosimetric and paraclinical data collected from 223 patients treated with proton therapy at the Centre François Baclesse and monitored at the University Hospital of Caen. A multicenter database was created, including dosimetry data as well as paraclinical examination results (visual field tests, optical coherence tomography, and visual evoked potentials). A relational model was developed to establish a link between visual field outcomes and the dose received by visual organs. This modeling highlighted challenges in associating visual field points with optical pathway structures, due to the small size of these structures, segmentation uncertainties, and patient movements. Consequently, a data reduction and uncertainty evaluation were performed. These analyses revealed the immediate effects of treatment on paraclinical examinations, as well as their progression over time. This work paves the way for the use of geometric and statistical models to predict visual complications, thus optimizing patient care

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Maloney, Alan. „Optimal (Adaptive) Design and Estimation Performance in Pharmacometric Modelling“. Doctoral thesis, Uppsala universitet, Institutionen för farmaceutisk biovetenskap, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-182284.

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The pharmaceutical industry now recognises the importance of the newly defined discipline of pharmacometrics. Pharmacometrics uses mathematical models to describe and then predict the performance of new drugs in clinical development. To ensure these models are useful, the clinical studies need to be designed such that the data generated allows the model predictions to be sufficiently accurate and precise. The capability of the available software to reliably estimate the model parameters must also be well understood. This thesis investigated two important areas in pharmacometrics: optimal design and software estimation performance. The three optimal design papers progressed significant areas of optimal design research, especially relevant to phase II dose response designs. The use of exposure, rather than dose, was investigated within an optimal design framework. In addition to using both optimal design and clinical trial simulation, this work employed a wide range of metrics for assessing design performance, and was illustrative of how optimal designs for exposure response models may yield dose selections quite different to those based on standard dose response models. The investigation of the optimal designs for Poisson dose response models demonstrated a novel mathematical approach to the necessary matrix calculations for non-linear mixed effects models. Finally, the enormous potential of using optimal adaptive designs over fixed optimal designs was demonstrated. The results showed how the adaptive designs were robust to initial parameter misspecification, with the capability to "learn" the true dose response using the accruing subject data. The two estimation performance papers investigated the relative performance of a number of different algorithms and software programs for two complex pharmacometric models. In conclusion these papers, in combination, cover a wide spectrum of study designs for non-linear dose/exposure response models, covering: normal/non-normal data, fixed/mixed effect models, single/multiple design criteria metrics, optimal design/clinical trial simulation, and adaptive/fixed designs.

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Leveque, Emilie. „Modélisation statistique de l'intensité des expositions prolongées en étiologie du cancer : application au tabac, à l'amiante, au cancer du poumon, et au mésothéliome pleural“. Thesis, Bordeaux, 2018. http://www.theses.fr/2018BORD0315/document.

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L'association entre le tabac et le cancer du poumon ou entre l'exposition professionnelle à l'amiante et le mésothéliome pleural ont largement été étudiées. Cependant, comme pour de nombreuses autres relations expositions prolongées-cancer, le rôle de l'intensité d'exposition tout au long de la vie a été peu étudié. La prise en compte de la variation de l'intensité au cours de la vie et de son effet dépendant du temps dans les analyses statistiques des données cas-témoins pose en effet quelques défis méthodologiques. Les objectifs de la thèse étaient 1) d'étudier l'effet dépendant du temps de l'intensité d'exposition au cours de la vie sur le risque de cancer et 2) d'identifier les profils de trajectoires d'intensité d'exposition sur la vie entière et comparer les risques de cancer associés. Pour répondre à ces deux objectifs, nous avons utilisé un indice cumulé d'exposition pondéré flexible déjà existant et nous avons développé un nouveau modèle conjoint à classes latentes, pour analyser les données de deux études cas-témoins françaises sur le mésothéliome pleural et le cancer du poumon. Les résultats montrent la contribution importante de l'intensité de la consommation de tabac récente pour le cancer du poumon et des expositions professionnelles anciennes à l'amiante pour les deux cancers. Ils confirment l'importance de considérer l'aspect temporel des expositions pour évaluer l'association avec le risque de cancer et illustrent l'intérêt des approches statistiques considérées
The association between smoking and lung cancer or between occupational exposure to asbestos and pleural mesothelioma have been extensively investigated. Nevertheless, as for many protracted exposures-cancer relationships, the role of exposure intensity over lifetime has been rarely addressed. Accounting for individual variation of intensity over lifetime and investigating time-dependent effect in the statistical analysis of case-control data indeed raise several methodological issues. The thesis objectives were 1) to study the time-dependent effect of exposure intensity over lifetime on the risk of cancer and 2) to identify lifetime profiles of exposure intensities and to compare their associated risks of cancer. To address these objectives, we used an existing flexible weighted cumulative index of exposure and we developed a new joint latent class mixed model, to analyze the data from two French case-control studies on lung cancer and pleural mesothelioma. The results show the important contribution of recent smoking intensity for lung cancer and distant intensity of exposure to asbestos for both cancers. They confirm the importance of the timing of exposure in the association with the risk of cancer and illustrate the relevance of the proposed statistical approaches

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Roche, Nicolas J.-H. „Caractérisation et modélisation de l'influence des effets cumulés de l'environnement spatial sur le niveau de vulnérabilité de systèmes spatiaux soumis aux effets transitoires naturels ou issus d'une explosion nucléaire“. Thesis, Montpellier 2, 2010. http://www.theses.fr/2010MON20108.

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L'environnement radiatif spatial est composé d'une grande diversité de particules dans un spectre en énergie très large. Parmi les effets affectant les composants électroniques, on distingue les effets cumulatifs et les effets singuliers transitoires analogiques (ASET). Les effets cumulatifs correspondent à une dégradation continue des paramètres électriques du composant induits par un dépôt d'énergie à faible débit de dose tout au long de la mission spatiale. Les ASETs sont eux causés par le passage d'une particule unique traversant une zone sensible du composant et engendrant une impulsion de tension transitoire qui se propage à la sortie de l'application. Au cours des tests au sol, les deux effets sont étudiés séparément, mais ils se produisent simultanément en vol. Il se produit donc un effet de synergie, induit par la combinaison de la dose et de l'apparition soudaine d'un ASET dans le dispositif préalablement irradié.Une étude de l'effet de synergie dose-ASET est proposée. Pour accélérer les irradiations, une technique connue sous le nom de « méthode de commutation de débit de dose » (DRS) prenant en compte la sensibilité accrue au faible débit de dose (ELDRS) est utilisée. Un modèle haut niveau est développé en utilisant l'analyse circuit permettant de prédire l'effet de synergie observé sur un amplificateur opérationnel à trois étages. Pour prédire l'effet de synergie, l'effet de dose est pris en compte en faisant varier les paramètres décrivant le modèle suivant une loi de variation déduite de la dégradation du courant d'alimentation qui est couramment enregistré au cours des essais industriels. Enfin, les effets transitoires des radiations sur l'électronique (TREEs) induits par un environnement de très fort débit de dose de rayons X pulsés ainsi que l'effet de synergie dose-TREE sont étudiés à l'aide d'un générateur de Flash-X. La méthode classique d'analyse des ASETs permet alors d'expliquer la forme des impulsions transitoires observées
The natural radiative space environment is composed by numerously particles in a very large energy spectrum. From an electronics component point of view, it is possible to distinguish cumulative effects and so-called Analog Single Event Transient effects (ASET). Cumulative effects correspond to continuous deterioration of the electrical parameters of the component, due to a low dose rate energy deposition (Total Ionizing Dose: TID) throughout the space mission. ASETs are caused by a single energetic particle crossing a sensitive area of the component inducing a transient voltage pulse that occurs at the output of the application. During ground testing, both effects are studied separately but happen simultaneously in flight. As a result a synergy effect, induced by the combination of the low dose rate energy deposition and the sudden occurrence of an ASET in the device previously irradiated, occurs. A study of dose-ASET synergistic effects is proposed using an accelerated irradiation test technique known as Dose Rate Switching method (DRS) tacking into account the concern of the Enhanced Low Dose Rate Sensitivity (ELDRS). A High Level Model is developed using circuit analysis to predict the synergy effect observed on a three stages operational amplifier. To predict synergy effect, the TID effect is taken into account by varying the model parameters following a variation law deduced from the degradation of the supply current which recorded during usual industrial TID testing. Finally, the Transient Radiation Effects on Electronics (TREE) phenomena induced by a Very High Dose Rate X-ray pulse environment and the dose-TREE synergy effect are then investigated using an X-ray flash facility. The classical ASETs methodology analysis can explain the shapes of transients observed

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Deveau, Michelle Leigh. „Exploration of Contextual Influences on the Incorporation of Chemical- and Scenario-Specific Data in the Derivation of Environmental Health and Occupational Exposure Limits for Chemicals“. Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42494.

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Outputs of dose–response assessments can be used as benchmarks that help to identify the need for risk management measures to reduce population health risks associated with exposure to chemicals. Various approaches can be used to facilitate the incorporation of chemical- or scenario-specific data into dose–response analyses, as a means of replacing or influencing default assumptions and extrapolations. The goal of the first part of this thesis was to examine the evolution of approaches to the incorporation of chemical- and scenario-specific data in dose–response assessments in regulatory settings, and identify contextual factors that serve as barriers and facilitators to the use of approaches. A main focus of the investigation was on physiological modelling, which is the most commonly-used category of approaches enabling extrapolations that depart from default assumptions. Evaluations of the dose–response applications of physiological modelling in the peer-reviewed scientific literature and in regulatory reports were conducted. Similarities between the scientific literature databases and regulatory reports were observed with respect to the evolution of physiological modelling in dose–response assessments, notably related to the timing, quantity, and annual frequency of publications. These similarities indicate that a factor in the low dose–response application of physiological modelling, relative to the overall production of physiological models, is an absence of data. However, variability in adoption of physiological modelling in regulatory dose–response assessments was observed among—and even within—organizations faced with the same data, indicating that other factors influence regulatory uptake of physiological modelling. Analysis of a survey indicated that factors acting as barriers or facilitators to regulatory risk assessors’ incorporation of increasingly data-informed approaches originated in both external and internal contexts. The external context was composed of the regulatory environment, domestic and international alignment, availability of external expertise, background of peer reviewers and stakeholders, availability and accessibility of software and tools, and chemical-dependent factors. The internal context was influenced by problem formulation, time and financial resources, organizational and management support, and training. A conceptual framework demonstrating how these factors impact a risk assessor’s ability to incorporate chemical- and scenario-specific data in dose–response analysis was developed, and subsequently used to provide recommendations on actions that could be taken to increase regulatory adoption of increasingly data-informed approaches. The second part of the thesis focused on the development of a knowledge translation tool designed to assist risk managers in the evaluation of dose–response analyses. The tool was focused on occupational exposure limits (OELs), and provides a guide to occupational hygienists in evaluating the relevance and reliability of individual OELs. When occupational hygienists are faced with multiple varying OELs for a chemical of interest, these evaluations can support the selection of the most appropriate OEL for a given situation. The usefulness of the tool was demonstrated for the selection of OELs for an OEL-rich compound (n-hexane), an OEL-poor compound (methamphetamine), and one additional compound (manganese). Such a tool can improve occupational hygienists’ understanding of the basis of OELs and the levels of protection afforded by each, which can contribute to more informed risk management decisions.

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Li, Li. „Computational modeling of dose response relationship for steroid hormone“. 2007. http://www.lib.ncsu.edu/ETD-db/ETD-catalog/view_etd?URN=etd-11052007-091224.

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Kappler, Martin [Verfasser]. „Dose response modeling using linear splines / vorgelegt von Martin Kappler“. 2007. http://d-nb.info/988756587/34.

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Herr, Lisa. „Modeling of time-dose-LET effects in the cellular response to radiation“. Phd thesis, 2015. http://tuprints.ulb.tu-darmstadt.de/4924/1/Thesis_Lisa_Herr_genehmigt_mit_Lebenslauf.pdf.

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This work is dedicated to the elucidation of time-dose- and if applicable linear energy transfer (LET) effects in the cellular response to ion or photon radiation. In particular, the common concept of the Local Effect Model (LEM) and the Giant Loop Binary Lesion (GLOBLE) model, which explains cell survival probabilities on the hand of clustering of double-strand breaks (DSB) in micrometer-sized sub-structural units of the DNA, was investigated with regard to temporal aspects. In previous studies with the LEM and GLOBLE model, it has been demonstrated that the definition of two lesion classes, characterized by single or multiple DSB in a DNA giant loop, with two repair fidelities is adequate to comprehensively describe the dose dependence of the cellular response to instantaneous photon irradiation or ion irradiation with varying LET. Furthermore, with the GLOBLE model for photon radiation, it has been shown that the assignment of two repair time scales to the two lesion classes allows to adequately reproduce time-dose effects after photon irradiation with an arbitrary constant dose-rate. In this work, the results of four projects that strengthen the mechanistic consistency and the practical applicability of the LEM and GLOBLE model will be presented. First, it was found that the GLOBLE model is applicable to describe time-dose effects in the cellular response to two split photon doses and in the occurrence of deterministic radiation effects. Second, in a comparison of ten models for the temporal course of DSB rejoining, it was revealed that a bi-exponential approach, as suggested by the LEM and GLOBLE model, finds a relatively large support by 61 experimental data sets. Third, in a comparison of four kinetic photon cell survival models that was based on fits to 13 dose-rate experiments, it was shown that the GLOBLE model performs well with respect to e.g. accuracy, parsimony, reliability and other factors that characterize a good approach. Last but not least, the dynamic concept of two time scales of cellular repair was introduced in the LEM. The consistency of predictions with this new kinetic model for ion radiation effects was verified and an agreement with experimental data was detected. In summary, the theoretical evidence that the time-dose-LET-dependence of the cellular response to radiation is explicable with radiation-characteristic damage distribution patterns on micrometer-scale was affirmed.

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Sarwat, Samiha. „Penalized spline modeling of the ex-vivo assays dose-response curves and the HIV-infected patients' bodyweight change“. 2015. http://hdl.handle.net/1805/8010.

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Indiana University-Purdue University Indianapolis (IUPUI)
A semi-parametric approach incorporates parametric and nonparametric functions in the model and is very useful in situations when a fully parametric model is inadequate. The objective of this dissertation is to extend statistical methodology employing the semi-parametric modeling approach to analyze data in health science research areas. This dissertation has three parts. The first part discusses the modeling of the dose-response relationship with correlated data by introducing overall drug effects in addition to the deviation of each subject-specific curve from the population average. Here, a penalized spline regression method that allows modeling of the smooth dose-response relationship is applied to data in studies monitoring malaria drug resistance through the ex-vivo assays.The second part of the dissertation extends the SiZer map, which is an exploratory and a powerful visualization tool, to detect underlying significant features (increase, decrease, or no change) of the curve at various smoothing levels. Here, Penalized Spline Significant Zero Crossings of Derivatives (PS-SiZer), using a penalized spline regression, is introduced to investigate significant features in correlated data arising from longitudinal settings. The third part of the dissertation applies the proposed PS-SiZer methodology to analyze HIV data. The durability of significant weight change over a period is explored from the PS-SiZer visualization. PS-SiZer is a graphical tool for exploring structures in curves by mapping areas where rate of change is significantly increasing, decreasing, or does not change. PS-SiZer maps provide information about the significant rate of weigh change that occurs in two ART regimens at various level of smoothing. A penalized spline regression model at an optimum smoothing level is applied to obtain an estimated first-time point where weight no longer increases for different treatment regimens.

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Campbell, Jerry L. „Physiologically-based pharmacokinetic modeling and dose-response for fetal skeletal malformations induced by ingestion of all-trans retinoic acid in CD-1 mice“. 2004. http://purl.galileo.usg.edu/uga%5Fetd/campbell%5Fjerry%5Fl%5F200412%5Fphd.

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Thesis (Ph. D.)--University of Georgia, 2004.
Directed by Mary Alice Smith. Includes an article published in Birth defects research, part B, developmental and reproductive toxicology, and an article submitted to Toxicological sciences. Includes bibliographical references.

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McLanahan, Eva Daneke. „Dose-response analysis of hypothalamic-pituitary-thyroid (HPT) axis perturbations in the adult rat using statistical methods for the binary mixture of PCB126 and perchlorate and computational modeling for iodide deficiency and perchlorate“. 2007. http://purl.galileo.usg.edu/uga%5Fetd/mclanahan%5Feva%5Fd%5F200712%5Fphd.

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Thesis (Ph. D.)--University of Georgia, 2007.
Directed by Jeffrey Fisher. Includes an article published in Toxicological sciences and articles submitted to Toxicological sciences and Environmental health perspectives. Includes bibliographical references.

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Κούση, Ευανθία. „Evaluation of dose-response models and determination of several radiobiological parameters“. Thesis, 2007. http://nemertes.lis.upatras.gr/jspui/handle/10889/596.

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Toxicity of the respiratory system is quite common after radiotherapy in thoracic tumours. The quantification of lung tissue response to irradiation is important in designing treatments associated with a minimum of complications and maximum tumor control. This work aims to estimate volumes V13, V20 and V30 as an index of radiation pneumonitis occurrence, to evaluate the predictive strength of the relative seriality, Lyman-Kutcher-Burman(LKB) and parallel normal tissue complication probability (NTCP) models regarding the incidence of radiation pneumonitis in a group of patients following lung cancer radiotherapy when lung perceived as paired and single organ respectively and also software development for the determination of the best estimates of the models’ parameters based on maximum likelihood method. The study was based on 46 patients and for each patient, lung dose-volume histograms (DVHs) and the clinical treatment outcome was available. From the 46 patients treated, 28 of them were scored as having radiation induced pneumonitis, with RTOG criteria grade ≥2. Firstly lungs were evaluated as a paired organ. Analyzing this material we failed to associate volume V13, V20 and V30 with radiation pneumonitis occurrence (χ2-test: probability of agreement between observed and predicted results using the 0.05 significance level). By applying ANOVA of the NTCP models examined in the overall group considering lungs as paired organs the LKB with Martel et al parameter set gave the best results, whereas when lungs perceived as individual organ (unhealthy lung volume-PTV) the best model was appeared to be LKB with Burman et al parameter set. However, in this relatively small group of lung cancer patients NTCP models didn’t show excessive correlation with the clinical outcome. Nevertheless, when total lung volume irradiated and total dose received were taken into account as factors of radiation pneumonitis prediction, correlation was almost duplicated for both perception of lungs. In order to achieve the best fitting of models to the clinical outcome for the specific patient group, maximum likelihood analysis was applied via software development using mle programming language, to find those parameters that maximize the likelihood function. When lungs perceived as single organ, the best fitting of models to the clinical outcome for relative seriality were D50 = 22Gy, γ= 2, s=0.031, LKB model D50 = 23Gy, m=0.18, n=1 and for parallel model, D50 = 20Gy, m=0.2, n=0.6. Maximum likelihood analysis was not applied for paired lung assumption as constraints did not allow us to properly fit the models.
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