Browsing by Subject "Pharmacometrics"

Now showing 1 - 10 of 10
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    Application of an active comparator-based benefit-risk Assessment in evaluating clinical trial design features of a new chemical entity using a Bayesian decision-theoretic framework.
    (2010-06) Goel, Varun
    During the drug development process, drug candidates are screened for their efficacy and toxicity. Dose selection is a crucial part of drug development and specifying the right dose imparts pharmacological activity while minimizing side effects. Evaluation of the benefit/risk ratio is typically done by examining the effect of a drug on efficacy and safety endpoints. However, this comparison can be difficult when there are multiple endpoints that are clinically and commercially relevant. A decision-based clinical utility is proposed and evaluated to aid in dose selection. A dose is viable if it has higher efficacy and lower toxicity than the values specified in multi-attribute decision criteria. PD 0200390 is a ligand of the α2δ subunit of the voltage-gated calcium channel being investigated for the treatment of primary insomnia and non-restorative sleep. Wake after sleep onset and number of awakenings are the measures of sleep consolidation while ease of awakening and morning behavior following wakefulness are the measures of residual effects. The objective of this research is to select a dose that maximizes the probability of a decision criterion characterized over safety and efficacy attributes. Data is obtained from two phase II double blind, randomized, placebo controlled crossover studies in subjects with primary insomnia. Dose response models are developed as hierarchical nonlinear model using NONMEM® and WinBUGS®. A Sensitivity analysis is performed to test the robustness of the selected dose with varying decision attributes.
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    Demonstration of pharmacometric applications to anti-infective chemotherapy.
    (2010-06) Salem, Ahmed Hamed Ahmed
    We developed a population pharmacokinetic model for efavirenz in pediatric HIV patients to guide dosing and decrease incidence of subtherapeutic levels. Data comprised of 3172 plasma concentrations collected over 4 years from 96 HIV-1 infected children who participated in the Pediatric AIDS Clinical Trials Group 382 (PACTG382) study. A one compartment model adequately described the data and the allometric size model accounted for the effect of body size on oral clearance and apparent volume of distribution. A sigmoid Emax maturation model demonstrated an increase in oral clearance by age to reach 90% of its mature level by the age of 9 months. The bioavailability of oral liquid formulations relative to the capsule formulation was also found to increase by age to reach 90% of its mature value of 0.79 by the age of 8 years. CYP2B6-G516T polymorphism was associated with a 51% decrease in oral clearance while MDR1-C3435T polymorphism has shown no effect. The final model showed good predictability performance and its application to improve dosing in pediatrics warrants further investigation. Appropriate initial treatment choices for methicillin resistant Staphylococcus aureus (MRSA) infections are very critical especially in the intensive care units (ICU) settings. We compared the ability of ceftobiprole, dalbavancin, daptomycin, tigecycline, linezolid and vancomycin to achieve their requisite PK/PD targets against MRSA isolates collected from ICU settings. Ceftobiprole and dalbavancin were found to have the highest probability of achieving favorable outcome against MRSA infections in the ICU. The susceptibility results suggested a further reduction of the vancomycin breakpoint to 1 μg/ml. We also employed a recently developed quantitative methodology to characterize the killing effect of vancomycin and rifampin combination against MRSA biofilm. The results suggest antagonism between vancomycin and rifampin against MRSA biofilm. The quantitative approach used provides a scientific rationale for further in vivo investigations which should allow a better understanding of the therapeutic potential of this combination in biofilm-associated MRSA infections. Finally, we compared the activities of moxifloxacin and vancomycin against MRSA and MRSE biofilms. Moxifloxacin exhibited a superior anti-biofilm activity suggesting potential benefit in treatment of MRSA and MRSE biofilm associated infections.
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    Methadone population pharmacokinetics: toward understanding the dose-response relationship in the treatment of opiate addiction
    (2013-01) Bart, Gavin Bryce-Samuel
    Methadone is a synthetic opiate agonist that is highly effective in the treatment of opiate addiction. When given as a long-term therapy, methadone maintenance reduces morbidity and mortality associated with opiate addiction. It is thus considered an “essential” medication by the World Health Organization. The benefits of methadone maintenance in the treatment of opiate addiction are well established. Predicting treatment response for a given individual, however, remains difficult. While methadone dose is generally associated with treatment outcome, large interstudy and interindividual variability in plasma concentrations of methadone have made it difficult to link dose response to pharmacokinetic parameters. This thesis explores characteristics of methadone maintained patients and develops a population pharmacokinetic model that identifies variables associated with methadone pharmacokinetic parameters. Chapter 1 provides a general review of the three Food and Drug Administration approved pharmacotherapeutic agents for the treatment of opiate dependence. Chapter 2 reviews the clinical pharmacology of methadone as used in the treatment of opiate dependence. Chapter 3 introduces us to the Hmong and their paradoxically exceptional treatment outcome in methadone maintenance on lower doses of methadone than their non-Hmong counterparts. This retrospective study helps form the hypothesis that their better treatment outcome is related to greater methadone exposure.The results of this population pharmacokinetic study and the psychosocial differences between Hmong and non-Hmong are presented in Chapters 4 and 5, respectively. We found that the lower methadone dose requirement is explained by higher apparent bioavailability of methadone in Hmong. Other influences on methadone pharmacokinetics, more specifically clearance, include age, body mass index, and single nucleotide polymorphisms in the ABCB1 and CYP2B6 genes. While the potential for culture to influence methadone treatment outcome is acknowledged, there remain sufficient grounds to hypothesize a significant biological (i.e., pharmacokinetic and/or pharmacodynamic) influence.
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    Pharmacokinetics, pharmacodynamics, and dose optimization of fludarabine in nonmyeloablative hematopoietic stem cell transplantation.
    (2010-10) Baron, Kyle Thomas
    The first goal of this research was to develop models describing pharmacokinetics and pharmacodynamics of fludarabine in a patient population undergoing nonmyeloablative hematopoietic stem cell transplantation. The second goal was to leverage model information to identify fludarabine doses that are most likely to achieve optimal outcomes after transplant. Datasets consisting of intensively sampled F-ara-A plasma concentrations after approximately 40 mg/m2 fludarabine as well as outcome data (treatment-related mortality, maximum acute graft-versus-host disease grade, and neutrophil engraftment) were available at the start of the modeling work. Population pharmacokinetic models were built using NONMEM. Covariate models for pharmacokinetic parameters were derived, including a model for the typical value of clearance in the population as a function of weight, creatinine clearance, and comorbidity score. Bayesian generalized linear models linking F-ara-A exposure to outcome probabilities were fit using OpenBUGS software. Both models were evaluated using predictive model checking methods. Fludarabine doses were optimized with respect to individual outcomes by finding the posterior probability that a certain dose would meet specific criteria defining treatment "success". Doses were optimized simultaneously across all three outcomes using a utility index defined as the product of the individual outcome success probabilities. In general, the results recommend a reduction of fludarabine doses to optimize outcomes after hematopoietic stem cell transplantation.
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    Pharmacometric analyses of lamotrigine in special populations: application to pregnant women, younger adult and elderly epilepsy patients
    (2012-12) Polepally, Akshanth R.
    The pharmacokinetics (PK) of lamotrigine (LTG) is understudied in pregnant women and elderly patients with epilepsy. Both pregnancy and advanced age are expected to result in changes in the LTG PK, which may cause potential loss of efficacy or safety. Optimal dosing of LTG in these special populations requires characterization of PK and its variability among the individuals. This dissertation work aimed at characterizing gestational age-associated changes in LTG PK and seizure control and age-related changes in LTG PK, and exploration of potential benefits of a newly developed LTG formulation over the conventional form in the elderly. The long-term goal of this research work is to create evidence-based guidelines for dosing LTG in both pregnant women and elderly patients with epilepsy. The change in apparent clearance of LTG (CL/F) was quantified with respect to gestational age and postpartum weeks in pregnant women who were maintained on LTG alone or with non-interacting drugs. During pregnancy, we identified two subpopulations of women that exhibited different rates of increase in LTG CL/F. The gestational age-associated increase in CL/F displayed a ten-fold higher rate in subpopulation I (0.120 L/h/week) compared to subpopulation II (0.0115 L/h/week). Such drastic changes in CL/F would require frequent dosage adjustments in subpopulation I. Further investigations revealed heterogeneity in the racial mix between the two subpopulations with a larger prevalence of whites (80%) in subpopulation I than in subpopulation II. We anticipate that race-associated genotypic variations in the activity or induction of UGT1A4 or polymorphisms in estrogen receptors could partly explain the varying degrees of enhanced CL/F between the two groups of pregnant women and may warrant further investigation. In the postpartum period, we calculated that an average duration of 3 weeks is required for LTG CL/F to reach preconception values, and that clinicians may need to taper the dose of LTG to the baseline prescribed dose within that time interval. When exploring seizure frequencies in pregnant women, the seizure rate was low most likely due to effective therapeutic drug monitoring. Future studies with a larger number of patients may provide information on exposure-response and time course changes of seizures in pregnant women. With the creation of a novel stable-labeled intravenous LTG formulation we were able to administer LTG by two routes (i.e., oral and intravenous) simultaneously in younger adults and elderly patients with epilepsy. We also demonstrated a comparable bioequivalence between extended-release and immediate release formulations in terms of steady-state area under the concentration-time curve, trough and average steady-state plasma concentration in elderly patients with epilepsy. We found a comparable absolute bioavailability (75%) of LTG tablets in both younger adult and elderly patients. However, the LTG clearance (CL) was 27% lower on average for elderly patients compared to younger adults. We hypothesize the observed reduction in CL may be caused by a reduced enzyme capacity (or UGT1A4 expression) and/or liver volume in the elderly group. Therefore, we recommend future studies to investigate age-selective differences in UGT1A4 expression. Overall, the studies presented in this thesis characterized the LTG PK in special populations that are underrepresented in clinical studies. We were unable to fully explain some of the PK findings in pregnant women or the elderly due to the lack of information on UGT1A4 genotypes. Therefore, future studies of LTG in these populations should investigate genotypic variations and expression of the main metabolic enzyme UGT1A4.
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    Pharmacometric modeling and simulation of ranitidine In human gastric acid secretion.
    (2012-01) Kim, Hyewon
    Stress-related gastric mucosal damage commonly occurs in critically ill patients. Prophylactic therapy has become the standard in patients admitted to intensive care unit to prevent the significant morbidity and mortality associated with acute gastric hemorrhage. Ranitidine has been used widely to prevent the gastric mucosal damage in critically ill patients. Data previously collected in two clinical trials included repeated measures of both plasma concentrations of ranitidine as well as multiple gastric acid measurements in critically ill patients and healthy volunteers. These studies were designed to answer a specific research question with a standard hypothesis-testing statistical approach, and those results have been reported. Over the past several years, new research methodologies have been developed or newly applied to analyze this type of data. The aim of this dissertation was to apply new methodologies to develop an appropriate model to simulate the human gastric acid system. A pharmacometric approach places strong statistical and mathematical interpretation to characterize pharmacokinetic and pharmacodynamic behavior and to identify the patient's prognostic factors that cause changes. The pharmacometric analysis showed that 2-compartment pharmacokinetic model, indirect Emax exposure-response response model in sequential approach was superior to all other tested models. Creatinine clearance and sex were identified as important covariates for ranitidine pharmacokinetics. Survival analysis provides unbiased estimates from the time-to-event data with differential follow-ups and censoring issues. A parametric survival approach can then be used to evaluate the model as well as predict observed or simulate future data. It was found that conditional hazard of event increased as time increased. Because it was impossible to discern the thorough exposure-response relationship of ranitidine effect with the range of explored exposure, we concluded that well designed, prospective time-to-event studies were necessary in the future. Simulation implements the physiologically-based mathematical model without invasive and costly experiments. The proposed mathematical model using STELLA® successfully demonstrated physiological gastric acid regulation, the effect of food, and histamine-2 receptor antagonist on gastric acid secretion. The information from this dissertation can be used to determine an optimal dosing regimen of ranitidine that effectively controls gastric pH and to guide future investigations of stress-related gastric mucosal damage.
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    Pharmacometric modeling of anti-cancer agents: application to gemcitabine, PQIP and irinotecan.
    (2010-07) Khatri, Amit
    We performed pharmacometric modeling of irinotecan, PQIP and gemcitabine. Irinotecan is a DNA topoisomerase-I inhibitor used in colorectal and brain tumors. One of our aims was to show that that cranial radiation, delivered during irinotecan administration, can enhance uptake in to cerebral-spinal fluid (CSF), and also to characterize the pharmacokinetics of irinotecan and its metabolites SN38 and APC in plasma and CSF in rats. The concentration-time data in plasma and CSF were analyzed by nonlinear mixed-effects modeling using FOCE-I method in NONMEM. The analysis showed that cranial radiation delivered during irinotecan administration enhances uptake in to CSF. The second aim of dissertation was to quantitatively evaluate the drug administration sequence effects of insulin-like growth factor type-1 receptor inhibitors (IGF-1R) with gemcitabine in vitro . Gemcitabine is a nucleoside analogue approved for a variety of solid tumors, while PQIP is an investigational IGF-1R inhibitor. In vitro experiments were conducted in 24-well tissue culture plates using MCF-7, MDA-MB-231 and Hs-578T human breast cancer cell lines. Viable cells were counted every day following the day of drug exposure. The effect of sequence on cell-kill was analyzed by bayesian techniques using WinBUGS. We found that exposure with gemcitabine first, followed by PQIP (GP sequence) was either superior or equivalent to the reverse sequence (PG sequence) with these drugs. The third aim of dissertation was to perform a population pharmacokinetic analysis of gemcitabine and its metabolites dFdU and dFdCTP in patients with solid tumors and to determine patient specific covariates associated with their disposition. Concentration data were obtained in 40 patients with solid tumors. The concentration-time data were analyzed by nonlinear mixed-effects modeling using first-order conditional estimation method with interaction (FOCE-I) in NONMEM. We found that Body surface area (BSA) and age were significant covariates for the disposition of gemcitabine, while creatinine clearance (CL CR ) and BSA were found to be significant covariates for the disposition of dFdU. We also found that patients who received gemcitabine at a rate less that 25 mg/m 2 /min had higher formation of dFdCTP than those who received gemcitabine at a rate greater than 25 mg/m 2 /min.
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    Pharmacometrics of antiepileptic drugs: modeling and simulation-based studies of lamotrigine and carbamazepine pharmacokinetics
    (2008-11) Prasittisopin, Baralee
    The population pharmacokinetic modeling plays a pivotal role in quantitative learning about drugs from sparse data collected in clinical studies. It provides crucial information needed for individualization of dosage regimens especially in special population in which the intensive pharmacokinetic studies are of ethical concern. Lamotrigine and carbamazepine are antiepileptic drugs commonly used in elderly patients; however, dosing these drugs is based largely on studies from adult patients. Pharmacokinetic information of these drugs in elderly patients is limited. The aims of the current dissertation were to determine the population pharmacokinetic parameters of lamotrigine and carbamazepine in the community-dwelling elderly patients, and to quantitatively identify factors that have significant effects on these parameters. The further aim was to characterize the time course of carbamazepine deinduction by an enzyme turnover model. Due to the presence of collinearity between covariates during the covariate model development of lamotrigine, the effect of collinearity on power, bias, and precision of the parameter estimates in the population covariate model was further investigated by means of simulations. The population pharmacokinetic models of lamotrigine and carbamazepine were successfully developed and the models adequately described the data sets. The important information of drugs' pharmacokinetics was obtained and it can be beneficial in developing dosing strategies for elderly patients receiving these drugs. The time course of carbamazepine deinduction was well described by an enzyme turnover model. This model allowed the estimation of the half-life of the induced enzymes involving carbamazepine metabolism which is the important parameter for characterizing the time course of carbamazepine deinduction process. The power of selecting the true covariates depends on sample size of the data set, the magnitude of covariate coefficient, and the degrees of correlation. The investigation of the effect of collinearity between two true covariates revealed that an increasing collinearity between two true covariates not only decreases the power of selecting the true covariate model, but also leads to the biased and imprecise parameter estimates. The results from this study improve the understanding of how and to what extent the collinearity affects the parameter estimates in the covariate model building.
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    Quantitative Pharmacological Approaches for Characterizing Lamotrigine Pharmacokinetics in Special Populations of Pregnancy, Postpartum and Breastfeeding Infants to Prospectively Optimize Dosing
    (2020-12) Karanam, Ashwin
    Lamotrigine (LTG) is one of the most prescribed antiseizure medications (ASMs) in women with epilepsy during pregnancy and postpartum. Pregnancy-related physiological changes are expected to alter LTG pharmacokinetics (PK) especially increases in apparent clearance (CL/F), leading to subtherapeutic concentrations and in-turn potential loss of efficacy and/or safety. This necessitates increases in LTG dose during pregnancy to maintain therapeutic LTG concentrations followed by a postpartum reduction in dose to prevent toxicity. In addition, infants born to mothers on LTG therapy are exposed to LTG via breastmilk, necessitating quantitative characterization of rate and extent of LTG exposure in infants and possible relationships with infant neurocognitive and developmental outcomes. Management of LTG therapy in pregnancy and postpartum is thus balancing seizures in mother while minimizing LTG exposure to fetus and infants. These special populations are understudied especially with respect to PK-pharmacodynamic (PK-PD) relationships. This dissertation work aims at characterizing changes to LTG PK in pregnancy, postpartum and in breastfeeding infants. In addition, this thesis explores feasibility of potential LTG dosing algorithms which maximizes exposure and safety during pregnancy. The long-term goal of this research work is to create robust evidence-based guidelines for dosing LTG in both pregnant women with epilepsy and their breastfeeding children.Investigations into CL/F changes in early pregnancy were performed in women with epilepsy maintained on LTG monotherapy who were planning to become pregnant. CL/F increased at the rate of 0.115 L/h for every gestational week with increases in CL/F observed as early as 5 weeks gestational age, often before women themselves know they are pregnant, and continue to increase through gestational week 13. The average increase in clearance by week 13 was approximately 1.6 times the preconception CL/F. Such rapid increases in LTG-CL would necessitate dose-adjustments relatively early in pregnancy. It was also identified that LTG-CL increased by 0.844 L/h for every 1 ng/ml of estradiol however gestational age was a more robust predictor of LTG-CL changes. This may potentially be due to gestational age reflecting additional factors, although neither was robust enough for clinical use owing to significant interpatient variability. We also identified a subpopulation of women who may not experience significance CL/F changes in early gestation however quantification of this group was limited by the small sample size. Our findings highlight the importance of planning and early detection of pregnancy and use of therapeutic drug monitoring (TDM) in this population. LTG CL/F changes in pregnancy and postpartum necessitate dose changes. However, there exists no consensus on dosing recommendations for these populations. Simulation based methods were used to understand the outcomes of LTG dosing changes and different regimens in pregnant women with epilepsy (PWWE) based on published data. We identified that without any dose changes women in the high CL/F change group could experience loss of efficacy as early as 8 weeks gestational age. At least two dose increases during pregnancy would be needed to prevent loss of efficacy. However, using the same two dose increase strategy in women with low CL/F change during gestation could possibly lead to toxic/unsafe LTG concentrations. These results show that a “one size fits all” philosophy does not work well for LTG dosing in PWWE based on current knowledge and reinforces the need for TDM. LTG CL/F was characterized in the largest cohort of PWWE and nonpregnant women with epilepsy (NPWWE) enrolled in the MONEAD study. During pregnancy, we identified two subpopulations of women that exhibited different rates of increase in LTG CL/F. The gestational age associated increase in CL/F displayed a 1.75-fold increase in pregnancy at the end gestation in a majority of the PWWE (91%) compared to no identifiable change in LTG CL/F in the remaining 9% closely reproducing a previous study performed in a smaller population. Clinical covariates available in the study failed to explain the difference in subpopulations. We anticipate genotypic variations in the activity or induction of UGT1A4 or polymorphisms in estrogen receptors could partly explain the varying degrees of enhanced CL/F between the two groups of pregnant women and may warrant further investigation. In the postpartum period, LTG CL/F reached baseline values by 3 weeks after birth necessitating dose tapering early in postpartum. After 3 weeks, the CL/F in postpartum PWWE was indistinguishable from NPWWE CL/F confirming that pregnancy related changes do not carry over to postpartum. Infant LTG exposure via breastmilk was quantified in breastfeeding infants exposed to LTG enrolled in the MONEAD study. Median infant LTG concentrations were approximately 28.9% of maternal concentrations with a range of 0.6-90.3% indicating significant infant exposure but also wide between infant variability pointing out the need to accurately characterize infant LTG PK. A physiology-based PK model (PBPK) methodology was utilized to incorporate mechanistic information of LTG disposition in both postpartum mother and infants to characterize LTG exposure with both models having predictions within 1.6-fold of observed levels. These models provide mechanistic understanding of LTG-CL changes in infants and predictions of infant exposures which can be used for exploring exposure-neurocognitive developmental relationships. This PBPK model serves as a framework for understanding PK and quantifying exposure of other commonly used drugs in these special populations and is not limited to the epilepsy therapeutic area. Overall, the studies presented in this thesis characterized the LTG PK in special underrepresented populations of women with epilepsy and their infants including pregnancy and postpartum and breastfed infants. The results of this thesis add robust evidence to inform clinical management of LTG therapy in PWWE.
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    Understanding the Impact of Pharmacogenetic Differences in Drug-Drug Interactions (DDIs): A Model-Based Approach to Predict Differences in Drug Exposure
    (2021-12) Cheng, Shen
    Genetic diversity between people can lead to differences in their capabilities to metabolize drugs. These pharmacogenomic differences induce variability in drug exposure (amount of drug in our bodies), which can cause both positive and negative effects. Another important contributor to differences in exposure occurs when one drug interacts with and alters how another drug is eliminated (drug-drug interactions, DDIs). Although the effects of pharmacogenetics or DDIs alone on drug exposure are well understood, a major gap in knowledge is how pharmacogenetic diversity might influence DDIs. Cytochrome P450s (CYP) are important superfamily of enzyme which includes many critical drug metabolism enzymes. CYP2C9 is an important drug metabolism enzyme in the CYP 2C subfamilies, which mediate 10-20% of the drugs that undergo CYP mediated metabolism. Several clinically important drugs including warfarin, phenytoin and flurbiprofen are metabolized through CYP2C9. Loss-of-function variants on gene encoding CYP2C9, such as *2 and *3, introduce considerable variabilities in the exposure and response of these drugs. Additionally, since CYP2C9 is inhibitable and inducible, the administration of these drugs together with CYP inhibitor and inducers will cause DDIs, which further complicate their dosing clinically. Two clinical trials sponsored by National Institute of Health (NIH) were conducted to investigate the extent of DDIs in the presence of CYP2C9 genotypes, using warfarin, flurbiprofen, ketoprofen and tolbutamide as probe drugs and fluconazole (a CYP inhibitor) and rifampin (a CYP inducer) as interacting drugs. Drug concentration data of probe drugs and their major metabolites in plasma and urine were collected for subsequent analysis. The aim of this thesis is to quantify the extent of DDIs in the presence of CYP2C9 genetic variants using the collected clinical PK data via mathematical modeling approach. Population PK models were first constructed for each probe drugs including pharmacogenomic differences and drug interactions as covariates. Model-based analysis were then performed based on parameter estimations. Physiology-based PK (PBPK) modeling was also performed to understand the genotype-dependent DDIs from a bottom-up prospective. The developed models will be valuable in quantifying genotype-dependent DDIs clinically, thus achieving another step toward precision medicine.