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Zhang X, Sui Y, Yu L, Zhou M, Zhang C, Liu D, Chen X, Yang L, Sui Y. Population Pharmacokinetic Analysis of Follicle-Stimulating Hormone During Ovarian Stimulation: Relation with Weight, Prolactin and Gene Polymorphism in THADA and ADIPOQ. Clin Pharmacokinet 2023; 62:1493-1507. [PMID: 37632631 DOI: 10.1007/s40262-023-01299-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/10/2023] [Indexed: 08/28/2023]
Abstract
BACKGROUND Personalisation strategies of ovarian stimulation for in vitro fertilisation (IVF)/ intracytoplasmic sperm injection (ICSI) treatments using exogenous follicle-stimulating hormone (FSH) have been extensively studied over the past 20 years. This research aimed to develop a FSH population pharmacokinetic (PPK) model taking into account the contribution of gene polymorphisms in Chinese reproductive-age women. METHODS Data from 173 patients undergoing GnRH agonist down-regulation long protocols of IVF/ICSI treatment were collected. PPK analysis was subsequently conducted using the nonlinear mixed-effect model (NONMEM) software. Several covariates, including 18 single nucleotide polymorphisms, demographic factors and biological characteristics, were evaluated. The final PPK model was extensively validated using bootstrapping and normalised prediction error distribution, as well as external validation on an independent group of 35 patients. RESULTS FSH PPK was accurately described by a one-compartment model with first-order absorption. The typical population value of apparent clearance was estimated to be 0.81 L/h [relative standard errors (RSE) 5.3%] with an inter-individual variability (IIV) of 16.0%. The typical apparent distribution volume was 8.36 L (RSE 9.7%, 59.7% IIV), and the absorption rate constant was estimated to be 0.0444 h-1 (RSE 9.1%). Body weight, basal prolactin concentration and the gene ADIPOQ (rs1501299) showed a significant covariate effect on the FSH clearance rate and exposure concentration. Genotypes of THADA (rs12478601) significantly influenced the distribution volume. Simulation results indicated that patients with the TT genotype of THADA (rs12478601) required a longer time to reach steady state and had less fluctuation in FSH levels. Model evaluations showed that the final model accurately and precisely described the observed data and demonstrated effective prediction performance. CONCLUSION PPK models of FSH have been developed, which could potentially be used for FSH dosage individualisation in the clinical setting. CLINICAL TRIAL REGISTRATION This study has been registered with the Chinese Clinical Trials Registry (ChiCTR2100049142).
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Affiliation(s)
- Xiaowei Zhang
- NHC Key Laboratory of Reproductive Health and Medical Genetics, China Medical University, Shenyang, China.
- Reproductive Affiliated Hospital of China Medical University, PuHe Street 10, Huanggu District, Shenyang, 110031, China.
| | - Yu Sui
- NHC Key Laboratory of Reproductive Health and Medical Genetics, China Medical University, Shenyang, China
- Reproductive Affiliated Hospital of China Medical University, PuHe Street 10, Huanggu District, Shenyang, 110031, China
- Key Laboratory of Medical Cell Biology of Ministry of Education, Institute of Health Sciences, China Medical University, Shenyang, China
| | - Lei Yu
- NHC Key Laboratory of Reproductive Health and Medical Genetics, China Medical University, Shenyang, China
- Reproductive Affiliated Hospital of China Medical University, PuHe Street 10, Huanggu District, Shenyang, 110031, China
- Department of Obstetrics and Gynecology, Shengjing Hospital of China Medical University, Shenyang, China
| | - Min Zhou
- NHC Key Laboratory of Reproductive Health and Medical Genetics, China Medical University, Shenyang, China
- Reproductive Affiliated Hospital of China Medical University, PuHe Street 10, Huanggu District, Shenyang, 110031, China
| | - Chong Zhang
- NHC Key Laboratory of Reproductive Health and Medical Genetics, China Medical University, Shenyang, China
- Reproductive Affiliated Hospital of China Medical University, PuHe Street 10, Huanggu District, Shenyang, 110031, China
| | - Danhua Liu
- NHC Key Laboratory of Reproductive Health and Medical Genetics, China Medical University, Shenyang, China
- Reproductive Affiliated Hospital of China Medical University, PuHe Street 10, Huanggu District, Shenyang, 110031, China
| | - Xinren Chen
- NHC Key Laboratory of Reproductive Health and Medical Genetics, China Medical University, Shenyang, China
- Reproductive Affiliated Hospital of China Medical University, PuHe Street 10, Huanggu District, Shenyang, 110031, China
| | - Liqun Yang
- NHC Key Laboratory of Reproductive Health and Medical Genetics, China Medical University, Shenyang, China
- Reproductive Affiliated Hospital of China Medical University, PuHe Street 10, Huanggu District, Shenyang, 110031, China
| | - Yang Sui
- NHC Key Laboratory of Reproductive Health and Medical Genetics, China Medical University, Shenyang, China.
- Reproductive Affiliated Hospital of China Medical University, PuHe Street 10, Huanggu District, Shenyang, 110031, China.
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Linking categorical models for prediction of pleasantness score using individual predictions of sweetness and creaminess: An advancement of categorical modeling. J Pharmacokinet Pharmacodyn 2021; 48:815-823. [PMID: 34196848 PMCID: PMC8604822 DOI: 10.1007/s10928-021-09771-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2020] [Accepted: 06/14/2021] [Indexed: 11/25/2022]
Abstract
The aim of this work was to develop and evaluate approaches of linked categorical models using individual predictions of probability. A model was developed using data from a study which assessed the perception of sweetness, creaminess, and pleasantness in dairy solutions containing variable concentrations of sugar and fat. Ordered categorical models were used to predict the individual sweetness and creaminess scores and these individual predictions were used as covariates in the model of pleasantness response. The model using individual predictions was compared to a previously developed model using the amount of fat and sugar as covariates driving pleasantness score. The model using the individual prediction of odds of sweetness and creaminess had a lower variability of pleasantness than the model using the content of sugar and fat in the test solutions, which indicates that the individual odds explain part of the variability in pleasantness. Additionally, simultaneous and sequential modeling approaches were compared for the linked categorical model. Parameter estimation was similar, but precision was better with sequential modeling approaches compared to the simultaneous modeling approach. The previous model characterizing the pleasantness response was improved by using individual predictions of sweetness and creaminess rather than the amount of fat and sugar in the solution. The application of this approach provides an advancement within categorical modeling showing how categorical models can be linked to enable the utilization of individual prediction. This approach is aligned with biology of taste sensory which is reflective of the individual perception of sweetness and creaminess, rather than the amount of fat and sugar in the solution.
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