MedElevator Войти в исследования
← Поиск публикаций

DOI 10.1007/s11095-023-03638-2

Медицинская библиотека · Pharmaceutical research · 2023

PBPK/PD Modeling of Nifedipine for Precision Medicine in Pregnant Women: Enhancing Clinical Decision-Making for Optimal Drug Therapy.

Liu Xinyang, Wang Wei, Chen Jingsi, Chen Dunjin, Tao Yong, Ouyang Defang

СтатьяПеревод в очереди

Аннотация

OBJECTIVE

This study aims to develop physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) predictive models for nifedipine in pregnant women, enhancing precision medicine and reducing adverse reactions for both mothers and infants.

METHODS

A PBPK/PD model was constructed using PK-Sim, MoBi, and MATLAB software, integrating literature and pregnancy-specific physiological information. The process involved: (1) establishing and validating a PBPK model for serum clearance after intravenous administration in non-pregnant individuals, (2) establishing and validating a PBPK model for serum clearance after oral administration in non-pregnant individuals, (3) constructing and validating a PBPK model for enzyme clearance after oral administration in non-pregnant individuals, and (4) adjusting the PBPK model structure and enzyme parameters according to pregnant women and validating it in oral administration. (5) PK/PD model was explored through MATLAB, and the PBPK and PK/PD models were integrated to form the PBPK/PD model.

RESULTS

The Nifedipine PBPK model's predictive accuracy was confirmed by non-pregnant and pregnant validation studies. The developed PBPK/PD model accurately predicted maximum antihypertensive effects for clinical doses of 5, 10, and 20 mg. The model suggested peak effect at 0.86 h post-administration, achieving blood pressure reductions of 5.4 mmHg, 14.3 mmHg, and 21.3 mmHg, respectively. This model provides guidance for tailored dosing in pregnancy-induced hypertension based on targeted blood pressure reduction.

CONCLUSION

Based on available literature data, the PBPK/PD model of Nifedipine in pregnancy demonstrated good predictive performance. It will help optimize individualized dosing of Nifedipine, improve treatment outcomes, and minimize the risk of adverse reactions in mothers and infants.

Для цитирования: Liu Xinyang, Wang Wei, Chen Jingsi, Chen Dunjin, Tao Yong, Ouyang Defang. PBPK/PD Modeling of Nifedipine for Precision Medicine in Pregnant Women: Enhancing Clinical Decision-Making for Optimal Drug Therapy.. Pharmaceutical research. 2023. DOI: 10.1007/s11095-023-03638-2.

Предметные рубрики MeSH

Подготовка и перевод публикации
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Тип публикации указан по данным источника. Уровень доказательности автоматически не присваивается.