Browsing by Subject "pharmacodynamics"

Now showing 1 - 4 of 4
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    Genetic Background and Sex: Impact on Generalizability of Research Findings in Pharmacology Studies
    (Springer, 2020) Sukoff Rizzo, Stacey J.; McTighe, Stephanie; McKinzie, David L.; Pharmacology and Toxicology, School of Medicine
    Animal models consisting of inbred laboratory rodent strains have been a powerful tool for decades, helping to unravel the underpinnings of biological problems and employed to evaluate potential therapeutic treatments in drug discovery. While inbred strains demonstrate relatively reliable and predictable responses, using a single inbred strain alone or as a background to a mutation is analogous to running a clinical trial in a single individual and their identical twins. Indeed, complex etiologies drive the most common human diseases, and a single inbred strain that is a surrogate of a single genome, or data generated from a single sex, is not representative of the genetically diverse patient populations. Further, pharmacological and toxicology data generated in otherwise healthy animals may not translate to disease states where physiology, metabolism, and general health are compromised. The purpose of this chapter is to provide guidance for improving generalizability of preclinical studies by providing insight into necessary considerations for introducing systematic variation within the study design, such as genetic diversity, the use of both sexes, and selection of appropriate age and disease model. The outcome of implementing these considerations should be that reproducibility and generalizability of significant results are significantly enhanced leading to improved clinical translation.
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    Implementing Extended-Infusion Cefepime as Standard of Care in a Children’s Hospital: A Prospective Descriptive Study
    (Sage, 2015-04) Nichols, Kristen R.; Karmire, Lauren C.; Cox, Elaine G.; Kays, Michael B.; Knoderer, Chad A.; Department of Pediatrics, Indiana University School of Medicine
    Background: Extended-infusion cefepime (EIC) has been associated with decreased mortality in adults, but to our knowledge, there are no studies in children. Objective: The objective of this study was to determine the feasibility of implementing EIC as the standard dosing strategy in a pediatric population. Methods: This was a descriptive study of children aged 1 month to 17 years, including patients in the intensive care unit, who received cefepime after admission to a freestanding, tertiary care children’s hospital. Patients were excluded if they were admitted to the neonatal intensive care unit or received cefepime in the outpatient, operating, or emergency department areas. Demographic and clinical data for patients who received cefepime from April through August 2013, the period following EIC implementation, were extracted from the medical records. Results: A total of 150 patients were included in the study, with a median age (interquartile range [IQR]) of 6 years (2-12.3 years) and median weight (IQR) of 20.7 kg (13.2-42.8 kg); 143 patients received cefepime via extended infusions, and 10 (7.0%) of those were changed to a 30-minute infusion during treatment. The most common reasons for infusion time change were intravenous (IV) incompatibility and IV access concerns, responsible for 50% of changes. Dosing errors and reported incidents during therapy were sparse (n = 12, 8.0%) and were most commonly related to renal dosing errors and/or initial dose error by prescriber. Conclusions: Because 93.0% of the patients who initially received EIC remained on EIC, implementation of EIC as the standard dosing strategy was feasible in this pediatric hospital.
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    Modeling and simulation applications with potential impact in drug development and patient care
    (2014) Li, Claire; Bies, Robert R.; Foroud, Tatiana; Li, Lang; Renbarger, Jamie L.
    Model-based drug development has become an essential element to potentially make drug development more productive by assessing the data using mathematical and statistical approaches to construct and utilize models to increase the understanding of the drug and disease. The modeling and simulation approach not only quantifies the exposure-response relationship, and the level of variability, but also identifies the potential contributors to the variability. I hypothesized that the modeling and simulation approach can: 1) leverage our understanding of pharmacokinetic-pharmacodynamic (PK-PD) relationship from pre-clinical system to human; 2) quantitatively capture the drug impact on patients; 3) evaluate clinical trial designs; and 4) identify potential contributors to drug toxicity and efficacy. The major findings for these studies included: 1) a translational PK modeling approach that predicted clozapine and norclozapine central nervous system exposures in humans relating these exposures to receptor binding kinetics at multiple receptors; 2) a population pharmacokinetic analysis of a study of sertraline in depressed elderly patients with Alzheimer’s disease that identified site specific differences in drug exposure contributing to the overall variability in sertraline exposure; 3) the utility of a longitudinal tumor dynamic model developed by the Food and Drug Administration for predicting survival in non-small cell lung cancer patients, including an exploration of the limitations of this approach; 4) a Monte Carlo clinical trial simulation approach that was used to evaluate a pre-defined oncology trial with a sparse drug concentration sampling schedule with the aim to quantify how well individual drug exposures, random variability, and the food effects of abiraterone and nilotinib were determined under these conditions; 5) a time to event analysis that facilitated the identification of candidate genes including polymorphisms associated with vincristine-induced neuropathy from several association analyses in childhood acute lymphoblastic leukemia (ALL) patients; and 6) a LASSO penalized regression model that predicted vincristine-induced neuropathy and relapse in ALL patients and provided the basis for a risk assessment of the population. Overall, results from this dissertation provide an improved understanding of treatment effect in patients with an assessment of PK/PD combined and with a risk evaluation of drug toxicity and efficacy.
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    A pharmacodynamic study of sirolimus and metformin in patients with advanced solid tumors
    (Springer, 2018-08) Sehdev, Amikar; Karrison, Theodore; Zha, Yuanyuan; Janisch, Linda; Turcich, Michelle; Cohen, Ezra E. W.; Maitland, Michael; Polite, Blase N.; Gajewski, Thomas F.; Salgia, Ravi; Pinto, Navin; Bissonnette, Marc B.; Fleming, Gini F.; Ratain, Mark J.; Sharma, Manish R.; Medicine, School of Medicine
    Background Sirolimus is a mammalian target of rapamycin (mTOR) inhibitor. Metformin may potentiate mTOR inhibition by sirolimus while mitigating its adverse effects. We conducted a pilot study to test this hypothesis. Methods Patients with advanced solid tumor were treated with sirolimus for 7 days followed by randomization to either sirolimus with metformin (Arm A) or sirolimus (Arm B) until day 21. From day 22 onwards, all patients received sirolimus and metformin. The primary aim was to compare the change in phospho-p70S6K (pp70S6K) in peripheral blood mononuclear cells (PBMC) from day 8 to day 22 using a two-sample t test. Secondary aims were objective response rate, toxicity, and other serum pharmacodynamic biomarkers (e.g., fasting glucose, triglycerides, insulin, C-peptide, IGF-1, IGF-1R, IGF-BP, and leptin). Results 24 patients were enrolled, with 18 evaluable for the primary endpoint. There was no significant difference in mean change in pp70S6K in arm A vs. arm B (− 0.12 vs. − 0.16; P = 0.64). Similarly, there were no significant differences in other serum pharmacodynamic biomarkers. There were no partial responses. There were no dose-limiting or unexpected toxicities. Conclusions Adding metformin to sirolimus, although well tolerated, was not associated with significant changes in pp70S6K in PBMC or other serum pharmacodynamic biomarkers. Impact: Combining metformin with sirolimus did not improve mTOR inhibition.