Individualization of nifedipine dosing for preterm labor

Project: Research project

Project Details


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.
Effective start/end date7/1/126/30/17


  • National Institutes of Health: $125,841.00
  • National Institutes of Health: $125,601.00
  • National Institutes of Health: $125,841.00
  • National Institutes of Health: $125,841.00
  • National Institutes of Health: $125,641.00


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