Mixed micellar liquid chromatography methods: modelling quantitative retention–activity relationships of angiotensin converting enzyme inhibitors

Wu, Liping; Cui, Yan; Xiong, Meijin; Wang, Shurong; Chen, Cong; Ye, Liming

doi:10.1002/bmc.1053

Cited by 11 publications

(5 citation statements)

References 30 publications

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“…Cilazaprilat is mainly eliminated via the kidneys [ 52 ]. Cilazapril and cilazaprilat are mainly bound to albumin, belonging to medium plasma-binding drugs, and their free fractions in plasma are 0.70 and 0.76 [ 50 ], respectively. Six clinical reports, including one report involving liver cirrhosis, were selected in the simulations.…”

Section: Resultsmentioning

confidence: 99%

Simultaneously Predicting the Pharmacokinetics of CES1-Metabolized Drugs and Their Metabolites Using Physiologically Based Pharmacokinetic Model in Cirrhosis Subjects

Luo,

Zhang,

et al. 2024

Pharmaceutics

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Hepatic carboxylesterase 1 (CES1) metabolizes numerous prodrugs into active ingredients or direct-acting drugs into inactive metabolites. We aimed to develop a semi-physiologically based pharmacokinetic (semi-PBPK) model to simultaneously predict the pharmacokinetics of CES1 substrates and their active metabolites in liver cirrhosis (LC) patients. Six prodrugs (enalapril, benazepril, cilazapril, temocapril, perindopril and oseltamivir) and three direct-acting drugs (flumazenil, pethidine and remimazolam) were selected. Parameters such as organ blood flows, plasma-binding protein concentrations, functional liver volume, hepatic enzymatic activity, glomerular filtration rate (GFR) and gastrointestinal transit rate were integrated into the simulation. The pharmacokinetic profiles of these drugs and their active metabolites were simulated for 1000 virtual individuals. The developed semi-PBPK model, after validation in healthy individuals, was extrapolated to LC patients. Most of the observations fell within the 5th and 95th percentiles of simulations from 1000 virtual patients. The estimated AUC and Cmax were within 0.5–2-fold of the observed values. The sensitivity analysis showed that the decreased plasma exposure of active metabolites due to the decreased CES1 was partly attenuated by the decreased GFR. Conclusion: The developed PBPK model successfully predicted the pharmacokinetics of CES1 substrates and their metabolites in healthy individuals and LC patients, facilitating tailored dosing of CES1 substrates in LC patients.

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Section: Resultsmentioning

confidence: 99%

Simultaneously Predicting the Pharmacokinetics of CES1-Metabolized Drugs and Their Metabolites Using Physiologically Based Pharmacokinetic Model in Cirrhosis Subjects

Luo,

Zhang,

et al. 2024

Pharmaceutics

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“…It has been testified to be useful to study human oral absorption prediction, chemical toxicity, skin permeability and penetration of drugs across the bloodbrain barrier (BBB) [11][12][13][14][15][16] . Moreover, biological activity of different oral drugs were studied by our research group [17][18][19][20][21][22] .…”

Section: Effect Of Acid-base Property In Conjunction With Molecular Dmentioning

confidence: 99%

Effect of Acid-Base Property in Conjunction with Molecular Descriptors for Chemical Drugs and Bioactive Ingredients of Traditional Chinese Medicine on Prediction of Oral Absorption by Biopartioning Micellar Chromatography

Chen¹,

Liang²,

Ren³

et al. 2013

Asian J. Chem.

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This research was aimed to predict per cent of human oral absorption (HOA %) for drugs by biopartitioning micellar chromatography (BMC). A data set of 102 chemical drugs containing acidic, basic, neutral and amphiprotic drugs from various structure classes with oral absorption rate data available was studied to construct prediction models of oral absorption for all chemical drugs, acidic chemical drugs, basic chemical drugs and neutral chemical drugs respectively and proved the effect of the acid-base property of drugs on oral absorption. Oral absorption was reciprocally correlated to the negative value of the capacity factor (-1/k). The correlation was improved with the addition of molecular descriptors. According to established prediction models for chemical drugs, biopartitioning micellar chromatography was applied to predict oral absorption of the organic acids and alkaloids of traditional Chinese medicines (TCM) for bioactive ingredients basing on constructed quantitative structure-activity relationship/quantitative retention-activity relationship models of chemical drugs. The results showed that application was predictable and practical in bioactive ingredients of traditional Chinese medicines.

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“…BMLC speeds up screening a large number of drug candidates in partitioning process into biological systems. In recent years, BMLC has been shown good correlations with oral drug absorption, [ 26 ] partition coefficients of drugs in blood to lung, blood to liver, blood to fat and blood to skin, [ 27 ] the bioactivities of alkaloids, [ 28 ] the bioactivities of angiotensin converting enzyme inhibitors, [ 29 ] blood–brain barrier penetration ability, [ 30 ] protein binding of acidic drugs, [ 31 ] the bioactivity of cephalosporins, [ 32 ] and therapeutic efficacy parameters, preclinical pharmacology, and pharmacokinetic of phenothiazines. [ 33 ]…”

Section: Introductionmentioning

confidence: 99%

The experimental and theoretical assessment of biopartitioning micellar liquid chromatography to mimic the drug‐protein binding of some pain‐relief drugs

Mohammadnia

Fatemi

Taghizadeh

2020

J Chinese Chemical Soc

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In this work, biopartitioning micellar liquid chromatography (BMLC) was used to the assessment of affinity binding of 13 pain‐relief drugs to human serum albumin (HSA) molecules. The values of BMLC retention factors were determined by aqueous CTAB solution as mobile phase. Then, these values were correlated to some molecular structural descriptors by using a quantitative structure retention relationship methodology. The statistical quality of the obtained models was evaluated by different validation tests. Also, selected descriptors were correlated with protein–drug binding values and resulted in correlation coefficients higher than 0.8. Results indicated that selected descriptors can address the most important structural features influencing the binding affinity of studied drugs to HSA.

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Mixed micellar liquid chromatography methods: modelling quantitative retention–activity relationships of angiotensin converting enzyme inhibitors

Cited by 11 publications

References 30 publications

Simultaneously Predicting the Pharmacokinetics of CES1-Metabolized Drugs and Their Metabolites Using Physiologically Based Pharmacokinetic Model in Cirrhosis Subjects

Simultaneously Predicting the Pharmacokinetics of CES1-Metabolized Drugs and Their Metabolites Using Physiologically Based Pharmacokinetic Model in Cirrhosis Subjects

Effect of Acid-Base Property in Conjunction with Molecular Descriptors for Chemical Drugs and Bioactive Ingredients of Traditional Chinese Medicine on Prediction of Oral Absorption by Biopartioning Micellar Chromatography

The experimental and theoretical assessment of biopartitioning micellar liquid chromatography to mimic the drug‐protein binding of some pain‐relief drugs

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