Chaphekar, Nupur
(2023)
Application of Modeling and Simulation to Predict Drug Exposure and Response During Pregnancy.
Doctoral Dissertation, University of Pittsburgh.
(Unpublished)
Abstract
The primary objective of this work was to apply limited sampling strategy (LSS,) population pharmacokinetic (PopPK) and physiologically based pharmacokinetic (PBPK) modeling to predict drug exposure and response during pregnancy.
A clinical study conducted in our laboratory evaluated the pharmacokinetics of buprenorphine (BUP) during pregnancy and postpartum. A three-point limited sampling strategy was developed and validated to estimate exposure using multiple linear regression and Bayesian analysis. The limited sampling strategy simplifies the time intensive study designs making it more convenient to the patients while also reducing the time and cost burden on clinical research centers. A PopPK model was developed to evaluate the pharmacokinetics of buprenorphine and pregnancy was identified as a covariate impacting the clearance of buprenorphine. A two-compartment model with linear absorption, distribution, metabolism and excretion adequately described the time course of buprenorphine and its metabolites. This model was extrapolated to perform population pharmacokinetic-pharmacodynamic analysis to relate buprenorphine concentration and pupillary diameter. The relationship between pupillary diameter and BUP concentrations was described by a sigmoidal Emax model with a hypothetical effect compartment. The EC50 of BUP was not significantly different between pregnancy and postpartum. Linear mixed effects modeling analysis showed that the average area under the curve of COWS score was significantly higher during pregnancy as compared to postpartum however the craving scores were similar during pregnancy and postpartum.
PBPK modeling was used to predict cannabis mediated drug interactions during pregnancy. The effect of acute and chronic cannabinoid treatment on cytochrome P450 (CYP) activity and expression was first evaluated in primary cultures of human hepatocytes and the fold change in exposure of CYP substrates in-vitro was then incorporated into the PBPK model for caffeine and midazolam to predict the drug interactions due to cannabis smoking during pregnancy. The simulations suggested a modification in the dose for caffeine and midazolam in pregnant women smoking marijuana.
Overall, these approaches demonstrated the utility of LSS, PopPK and PBPK to predict drug exposure and response during pregnancy. The ultimate goal is to use these modeling approaches to optimize drug therapy during pregnancy when there is limited/no clinical data available.
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Details
| Item Type: |
University of Pittsburgh ETD
|
| Status: |
Unpublished |
| Creators/Authors: |
|
| ETD Committee: |
|
| Date: |
30 November 2023 |
| Date Type: |
Publication |
| Defense Date: |
27 July 2023 |
| Approval Date: |
30 November 2023 |
| Submission Date: |
21 November 2023 |
| Access Restriction: |
2 year -- Restrict access to University of Pittsburgh for a period of 2 years. |
| Number of Pages: |
264 |
| Institution: |
University of Pittsburgh |
| Schools and Programs: |
School of Pharmacy > Pharmaceutical Sciences |
| Degree: |
PhD - Doctor of Philosophy |
| Thesis Type: |
Doctoral Dissertation |
| Refereed: |
Yes |
| Uncontrolled Keywords: |
Pregnancy, modeling, simulation, exposure |
| Date Deposited: |
30 Nov 2023 13:57 |
| Last Modified: |
30 Nov 2023 13:57 |
| URI: |
http://d-scholarship.pitt.edu/id/eprint/45558 |
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