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  5. The Application of Physiological-Based Pharmacokinetic Modeling to Quantitatively Assess the Impaction of Gut Bacterial Tyrosine Decarboxylases on the Pharmacokinetics of Oral Levodopa
 
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The Application of Physiological-Based Pharmacokinetic Modeling to Quantitatively Assess the Impaction of Gut Bacterial Tyrosine Decarboxylases on the Pharmacokinetics of Oral Levodopa

Other Title
The Application of Physiological-Based Pharmacokinetic Modeling to Quantitatively Assess the Impaction of Gut Bacterial Tyrosine Decarboxylases on the Pharmacokinetics of Oral Levodopa
Type
thesis
Date Issued
2023-07-12
Author(s)
MERCADER, XAVIER JOSEPH
Advisor
謝堅銘
Subjects
系所名稱:臨床基因體學暨蛋白質體學碩士學位學程
Description
學位別:碩士
語文別:英文
口試委員:卓爾婕 CHO, ER-CHIEH;韓嘉莉 HAN, CHIA-LI;謝堅銘 HSIEH, CHIEN-MING
授權範圍:網際網路,開放日期為2023-07-27
Abstract
Parkinson’s Disease (PD) is a neurodegenerative illness affecting the geriatric population. The dopamine loss associated with this disorder results in various motor and non-motor dysfunctions, generating unintended movements that greatly distress the patient’s quality of life. It has long been established that levodopa is peripherally metabolized to dopamine in the gut which arises in a restriction of available dopamine in the brain. Recently, a novel microbial pathway for the metabolism of levodopa through bacterial tyrosine decarboxylase (tyrDC) was discovered. This study aims to quantitatively examine the influence of tyrDC on oral levodopa metabolism through a Physiologically Based Pharmacokinetic (PBPK) modeling. The in vitro metabolism displayed drastic reduction of levodopa and a concentration-dependent formation of dopamine in the presence of tyrDC over the course of 2 hours. The advantage of PBPK modeling is the ability to predict plasma concentrations without the need to undergo ethical considerations and clinical trials. Developed PBPK model went through validation and the prediction errors from the observed data compared to the simulated peak plasma concentration (Cmax) (mg/L) and Area Under the Curve (AUC) (mg*h/L) after single and multiple-dose simulations were all within two-fold. Correspondingly, our model is fit to predict the PK data of levodopa. After the validation, a series of simulations were employed by our PBPK model integrated with enzyme kinetics parameters. The model predicted reduced levels of levodopa which indicates levodopa metabolism by tyrDC in the gut. The values of the PK profiles of levodopa from the predicted were greatly lowered to as much as 50% in comparison with the clinical data. In conclusion, the devised PBPK model for levodopa successfully predicted the influence of the tyrDC in oral levodopa metabolism. However, a verification should be done in the future by comparing these results with in vivo studies on levodopa treated with tyrDC.
URI
https://handle.ncl.edu.tw/11296/2abe45
https://203.71.86.71/handle/123456789/10421

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