Individualization of nifedipine dosing for preterm labor

早产硝苯地平剂量的个体化

基本信息

项目摘要

DESCRIPTION (provided by applicant): Project Summary/Abstract Preterm labor is a major cause of neonatal morbidity and mortality. Evidence for individualized therapy choice, a key tenant of personalized medicine, is lacking in many areas of obstetric medicine, including in the treatment choices for preterm labor. Incorporating principle components of clinical pharmacology, including pharmacogentics, pharmacokinetics, and quantitative models, into obstetrical research enriches the ability to individualize drug choice and dosing. The objective of this K23 proposal is to provide the advanced training and expertise necessary for the applicant to develop quantitative pharmacology models specific to the obstetric population. The candidate, Dr. Sara Quinney, Pharm.D., Ph.D., is a clinical pharmacologist and Assistant Research Professor in the Department of Obstetrics and Gynecology at the Indiana University School of Medicine (IUSM). Dr. Quinney's career goal is to combine laboratory and clinical data into quantitative pharmacometric models to optimize drug therapy in pregnant women. IUSM hosts a robust academic environment with a strong history of clinical research and a commitment to mentoring young faculty members. The mentors and advisors to this proposal will bring strengths in the areas pertinent to Dr. Quinney's career development. The primary mentor, Dr. David Flockhart, M.D., Ph.D., is an internationally recognized clinical pharmacologist who has shown a commitment to training translational investigators. The Department of Obstetrics and Gynecology at IUSM is home to an exceptional OB/GYN residency program and has excellent resources for translational research, including an established staff of clinical research assistants that are available to Dr. Quinney. The Center for Computational Biology and Bioinformatics (CCBB) provides access to computational resources needed for the completion of the proposal. The central hypothesis of the proposed research study is that nifedipine treatment can be optimized by a novel pharmacokinetic/ pharmacodynamic model that allows clinicians to select an optimum dosing regimen for nifedipine. A clinical trial will be conducted to test the hypothesis that women exposed to higher plasma concentrations of nifedipine are more likely to respond to nifedipine tocolysis and delay delivery at least 48 hours. Pharmacogenetic variations in nifedipine pathway genes, e.g. CYP3A4, CYP3A5, CACNA1C, and CACN1C, will be tested for association with tocolytic response to nifedipine. Secondly, using in vitro data on nifedipine metabolism and the results of the clinical study, a quantitative model that incorporates patient-specific covariates will be developed with the aim to of identifying optimal, individualized dosing regimens of nifedipine for preterm labor through more individualized treatment. This study is significant in that understanding of the factors associated with the variable response to nifedipine can improve the treatment of preterm labor. In addition, this study will lay the foundation for quantitative models of other drugs used in the treatment of preterm labor and other conditions of pregnancy, and for a successful career in obstetrical pharmacology for the candidate. PUBLIC HEALTH RELEVANCE: Project Narrative Preterm birth is a major cause of neonatal morbidity and mortality. Successful treatment of preterm labor, by individualizing therapy, can diminish the societal and economic consequences of preterm birth. Through the training gained and strategies developed in this proposal, Dr. Quinney will lay the groundwork for an independent career in clinical obstetric pharmacology, focused on improving maternal and neonatal health through individualization of therapies for preterm labor and other conditions of pregnancy.
描述(由申请人提供):项目摘要/摘要早产是新生儿发病率和死亡率的主要原因。个性化治疗选择是个性化药物的一个关键租户,在产科医学的许多领域缺乏个性化治疗选择的证据,包括早产的治疗选择。将临床药理学的主要组成部分,包括药源学、药代动力学和定量模型,纳入产科研究,丰富了个性化药物选择和剂量的能力。的目标是 这项K23提案旨在为申请者提供所需的高级培训和专业知识,以开发专门针对产科人群的定量药理学模型。候选人Sara Quinney博士是印第安纳大学医学院(IUSM)妇产科的临床药理学家和助理研究教授。昆尼博士的职业目标是将实验室和临床数据结合到定量药物计量模型中,以优化孕妇的药物治疗。IUSM拥有强大的学术环境,拥有强大的临床研究历史,并致力于指导年轻教职员工。这项提议的导师和顾问将在与昆尼博士的职业发展相关的领域带来优势。主要导师大卫·弗洛克哈特博士是一位国际公认的临床药理学家,他致力于培训翻译研究人员。IUSM的妇产科拥有特殊的产科/妇科住院医师计划,并拥有优秀的翻译研究资源,包括Quinney博士可以使用的临床研究助理人员。该中心为 计算生物学和生物信息学(CCBB)提供了完成提案所需的计算资源。这项拟议研究的中心假设是,硝苯地平的治疗可以通过一种新的药代动力学/药效学模型来优化,该模型允许临床医生选择硝苯地平的最佳剂量方案。将进行一项临床试验,以检验这一假设,即暴露于较高血浆浓度的硝苯地平的妇女更有可能对硝苯地平宫缩产生反应,并将分娩推迟至少48小时。硝苯地平途径基因的药物遗传变异,如细胞色素P3A4、细胞色素P3A5、CACNA1C和CACN1C,将被测试与硝苯地平的宫缩反应有关。其次,利用硝苯地平代谢的体外数据和临床研究的结果,将开发一个包含患者特定协变量的定量模型,旨在通过更个体化的治疗来确定早产的最佳、个性化的硝苯地平给药方案。这项研究的意义在于,了解与硝苯地平可变反应相关的因素可以改善早产的治疗。此外,本研究还将为定量模型的建立奠定基础 用于治疗早产和其他妊娠状况的其他药物,以及候选人在产科药理学领域的成功职业生涯。 公共卫生相关性:项目叙述早产是新生儿发病率和死亡率的主要原因。成功的早产治疗,通过个体化治疗,可以减少早产的社会和经济后果。通过在该计划中获得的培训和制定的策略,昆尼博士将为在临床产科药理学领域的独立职业生涯奠定基础,专注于通过针对早产和其他怀孕条件的个体化治疗来改善产妇和新生儿的健康。

项目成果

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Sara K Quinney其他文献

Sara K Quinney的其他文献

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{{ truncateString('Sara K Quinney', 18)}}的其他基金

Outreach, Dissemination, and Training Core
外展、传播和培训核心
  • 批准号:
    10309158
  • 财政年份:
    2021
  • 资助金额:
    $ 12.56万
  • 项目类别:
Logistics Core
物流核心
  • 批准号:
    10309159
  • 财政年份:
    2021
  • 资助金额:
    $ 12.56万
  • 项目类别:
Pharmacometrics and Clinical Trial Design Core
药理学和临床试验设计核心
  • 批准号:
    10487579
  • 财政年份:
    2021
  • 资助金额:
    $ 12.56万
  • 项目类别:
Pharmacometrics and Clinical Trial Design Core
药理学和临床试验设计核心
  • 批准号:
    10309157
  • 财政年份:
    2021
  • 资助金额:
    $ 12.56万
  • 项目类别:
Pharmacometrics and Clinical Trial Design Core
药理学和临床试验设计核心
  • 批准号:
    10676277
  • 财政年份:
    2021
  • 资助金额:
    $ 12.56万
  • 项目类别:
Outreach, Dissemination, and Training Core
外展、传播和培训核心
  • 批准号:
    10676279
  • 财政年份:
    2021
  • 资助金额:
    $ 12.56万
  • 项目类别:
Logistics Core
物流核心
  • 批准号:
    10487584
  • 财政年份:
    2021
  • 资助金额:
    $ 12.56万
  • 项目类别:
Outreach, Dissemination, and Training Core
外展、传播和培训核心
  • 批准号:
    10487582
  • 财政年份:
    2021
  • 资助金额:
    $ 12.56万
  • 项目类别:
Logistics Core
物流核心
  • 批准号:
    10676280
  • 财政年份:
    2021
  • 资助金额:
    $ 12.56万
  • 项目类别:
Integrated bioinformatic and pharmacokinetic models of high-dimensional drug interactions
高维药物相互作用的综合生物信息学和药代动力学模型
  • 批准号:
    9008147
  • 财政年份:
    2016
  • 资助金额:
    $ 12.56万
  • 项目类别:

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