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You searched for +publisher:"IUPUI" +contributor:("Bies, Robert R."). Showing records 1 – 2 of 2 total matches.

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IUPUI

1. Li, Claire. Modeling and simulation applications with potential impact in drug development and patient care.

Degree: 2014, IUPUI

Indiana University-Purdue University Indianapolis (IUPUI)

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.

Advisors/Committee Members: Bies, Robert R., Foroud, Tatiana, Li, Lang, Renbarger, Jamie L..

Subjects/Keywords: modeling and simulation; pharmacokinetics; pharmacodynamics; genetics; Molecular pharmacology  – Research  – Evaluation  – Methodology; Drug development  – Pharmacokinetics; Drug development  – Molecular genetics; Drugs  – Physiological effect  – Mathematical models; Simulation methods  – Research  – Evaluation  – Methodology; Mathematical models  – Research  – Evaluation  – Methodology; Drugs  – Metabolism; Drugs  – Design; Clinical trials  – Research  – Evaluation; Drugs  – Testing; Drugs  – Toxicology; Patient-centered health care; Pharmacokinetics  – Research

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Li, C. (2014). Modeling and simulation applications with potential impact in drug development and patient care. (Thesis). IUPUI. Retrieved from http://hdl.handle.net/1805/5969

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Li, Claire. “Modeling and simulation applications with potential impact in drug development and patient care.” 2014. Thesis, IUPUI. Accessed October 15, 2019. http://hdl.handle.net/1805/5969.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Li, Claire. “Modeling and simulation applications with potential impact in drug development and patient care.” 2014. Web. 15 Oct 2019.

Vancouver:

Li C. Modeling and simulation applications with potential impact in drug development and patient care. [Internet] [Thesis]. IUPUI; 2014. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/1805/5969.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Li C. Modeling and simulation applications with potential impact in drug development and patient care. [Thesis]. IUPUI; 2014. Available from: http://hdl.handle.net/1805/5969

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

2. Han, Xu. Identification and mechanistic investigation of clinically important myopathic drug-drug interactions.

Degree: 2014, IUPUI

Indiana University-Purdue University Indianapolis (IUPUI)

Drug-drug interactions (DDIs) refer to situations where one drug affects the pharmacokinetics or pharmacodynamics of another. DDIs represent a major cause of morbidity and mortality. A common adverse drug reaction (ADR) that can result from, or be exacerbated by DDIs is drug-induced myopathy. Identifying DDIs and understanding their underlying mechanisms is key to the prevention of undesirable effects of DDIs and to efforts to optimize therapeutic outcomes. This dissertation is dedicated to identification of clinically important myopathic DDIs and to elucidation of their underlying mechanisms. Using data mined from the published cytochrome P450 (CYP) drug interaction literature, 13,197 drug pairs were predicted to potentially interact by pairing a substrate and an inhibitor of a major CYP isoform in humans. Prescribing data for these drug pairs and their associations with myopathy were then examined in a large electronic medical record database. The analyses identified fifteen drug pairs as DDIs significantly associated with an increased risk of myopathy. These significant myopathic DDIs involved clinically important drugs including alprazolam, chloroquine, duloxetine, hydroxychloroquine, loratadine, omeprazole, promethazine, quetiapine, risperidone, ropinirole, trazodone and simvastatin. Data from in vitro experiments indicated that the interaction between quetiapine and chloroquine (risk ratio, RR, 2.17, p-value 5.29E-05) may result from the inhibitory effects of quetiapine on chloroquine metabolism by cytochrome P450s (CYPs). The in vitro data also suggested that the interaction between simvastatin and loratadine (RR 1.6, p-value 4.75E-07) may result from synergistic toxicity of simvastatin and desloratadine, the major metabolite of loratadine, to muscle cells, and from the inhibitory effect of simvastatin acid, the active metabolite of simvastatin, on the hepatic uptake of desloratadine via OATP1B1/1B3. Our data not only identified unknown myopathic DDIs of clinical consequence, but also shed light on their underlying pharmacokinetic and pharmacodynamic mechanisms. More importantly, our approach exemplified a new strategy for identification and investigation of DDIs, one that combined literature mining using bioinformatic algorithms, ADR detection using a pharmacoepidemiologic design, and mechanistic studies employing in vitro experimental models.

Advisors/Committee Members: Flockhart, David A., Bies, Robert R., Desta, Zeruesenay, Li, Lang, Queener, Sherry F., Quinney, Sara K., Zhang, Jian-Ting.

Subjects/Keywords: drug-drug interaction, myopathy, cytochrome P450, OATP1B1/1B3, simvastatin, loratadine, metabolism, transporter; Drug interactions  – Research  – Analysis  – Evaluation; Drugs  – Metabolism  – Evaluation; Pharmacokinetics  – Research; Cytochrome P-450  – Research  – Analysis  – Evaluation; Muscles  – Physiology; Drugs  – Physiological effect; Pharmacoepidemiology; Bioinformatics  – Research; Computer algorithms  – Research; Histamine  – Physiological effect  – Research; Anticholesteremic agents  – Physiological effect  – Research; Drugs  – Side effects; Drugs  – Physiological transport  – Research  – Analysis; Drug carriers (Pharmacy)  – Research  – Analysis

Record DetailsSimilar RecordsGoogle PlusoneFacebookTwitterCiteULikeMendeleyreddit

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Han, X. (2014). Identification and mechanistic investigation of clinically important myopathic drug-drug interactions. (Thesis). IUPUI. Retrieved from http://hdl.handle.net/1805/5275

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Han, Xu. “Identification and mechanistic investigation of clinically important myopathic drug-drug interactions.” 2014. Thesis, IUPUI. Accessed October 15, 2019. http://hdl.handle.net/1805/5275.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Han, Xu. “Identification and mechanistic investigation of clinically important myopathic drug-drug interactions.” 2014. Web. 15 Oct 2019.

Vancouver:

Han X. Identification and mechanistic investigation of clinically important myopathic drug-drug interactions. [Internet] [Thesis]. IUPUI; 2014. [cited 2019 Oct 15]. Available from: http://hdl.handle.net/1805/5275.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Han X. Identification and mechanistic investigation of clinically important myopathic drug-drug interactions. [Thesis]. IUPUI; 2014. Available from: http://hdl.handle.net/1805/5275

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

.