Quantitative Assessment of the Impact of Crohn's Disease on Protein Abundance of Human Intestinal Drug-Metabolising Enzymes and Transporters

Alrubia, Sarah; Al‐Majdoub, Zubida M.; Achour, Brahim; Rostami‐Hodjegan, Amin; Barber, Jill

doi:10.1016/j.xphs.2022.07.012

Cited by 10 publications

(5 citation statements)

References 87 publications

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“…Several drug transporters, such as ABCC3 and SLC16A1, decreased in both inflamed and adjacent non-inflamed colon tissue in ulcerative colitis and Crohn's disease (Erdmann et al, 2019;Alrubia et al, 2022). A similar decrease was also reported in levels of several CYP enzymes in ileum in Crohn's disease (Alrubia et al, 2022). Although the studies included very few donors (n < 5), similar results were observed in both cohorts.…”

Section: Applications In Specific and Disease Populationssupporting

confidence: 77%

“…For example, inflammatory bowel disease has been shown to affect levels of intestinal drug transporter and drug metabolizing proteins. Several drug transporters, such as ABCC3 and SLC16A1, decreased in both inflamed and adjacent non-inflamed colon tissue in ulcerative colitis and Crohn's disease (Erdmann et al, 2019;Alrubia et al, 2022). A similar decrease was also reported in levels of several CYP enzymes in ileum in Crohn's disease (Alrubia et al, 2022).…”

Section: Applications In Specific and Disease Populationssupporting

confidence: 69%

“…In broader terms, many groups have utilized proteomics for characterization of interindividual variability to investigate the impact of age (Bhatt et al, 2018(Bhatt et al, , 2019van Groen et al, 2018;Goelen et al, 2023), genotype (Dalton et al, 2020;El-Boraie et al, 2022), and disease conditions (Al-Majdoub et al, 2020;Alrubia et al, 2022;. For example, quantitative proteomic analysis of 455 human liver samples revealed that variability in UGT2B17 is associated with age, sex, race, and genotype (Bhatt et al, 2018).…”

Section: What Is New In Quantitative Proteomics: Techniques and Appli...mentioning

confidence: 99%

“…For example, quantitative proteomic analysis of 455 human liver samples revealed that variability in UGT2B17 is associated with age, sex, race, and genotype (Bhatt et al, 2018). Similarly, recent studies have utilized proteomics for characterizing the effect of diseases or abnormal physiological conditions, such as Crohn's disease (Alrubia et al, 2022), colorectal cancer , liver diseases (Prasad et al, 2018;Al-Majdoub et al, 2020;, and obesity (Wegler et al, 2022). Not confined to proteomics of the host, the technique extends to quantifying gut microbial proteins like glucuronidases (GUS) and establishing correlations, such as those between GUS enzymes and the deconjugation rate of drug glucuronides (Parvez et al, 2021).…”

Section: What Is New In Quantitative Proteomics: Techniques and Appli...mentioning

confidence: 99%

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Quantitative Proteomics for Translational Pharmacology and Precision Medicine: State of The Art and Future Outlook

Prasad,

Al-Majdoub,

Wegler

et al. 2024

Drug Metab Dispos

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Over the past 20 years, quantitative proteomics has contributed a wealth of protein expression data, which are currently used for a variety of systems pharmacology applications, as a complement or a surrogate for activity of the corresponding proteins. A symposium at the 25th North American ISSX meeting, in Boston, in September 2023, was held to explore current and emerging applications of quantitative proteomics in translational pharmacology and strategies for improved integration into model-informed drug development based on practical experience of each of the presenters. A summary of the talks and discussions is presented in this perspective alongside future outlooks that were outlined for future meetings. Significance StatementThis perspective explores current and emerging applications of quantitative proteomics in translational pharmacology and precision medicine and outlines outlooks for improved integration into model-informed drug development.

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Section: Applications In Specific and Disease Populationssupporting

confidence: 77%

Section: Applications In Specific and Disease Populationssupporting

confidence: 69%

Section: What Is New In Quantitative Proteomics: Techniques and Appli...mentioning

confidence: 99%

Section: What Is New In Quantitative Proteomics: Techniques and Appli...mentioning

confidence: 99%

See 2 more Smart Citations

Quantitative Proteomics for Translational Pharmacology and Precision Medicine: State of The Art and Future Outlook

Prasad,

Al-Majdoub,

Wegler

et al. 2024

Drug Metab Dispos

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“…For example, decreased Pglycoprotein (P-gp) and Breast Cancer Resistance Protein (BCRP) expression were observed for the colon and the rectum in patients with active UC (Blokzijl et al, 2007;Effinger et al, 2019;Englund et al, 2007). Altered intestinal expression of P-gp and cytochrome P450 (CYP) 3A4 have been reported for CD patients (Alrubia, Al-Majdoub, et al, 2022;Blokzijl et al, 2007;Plewka et al, 2014;Wilson et al, 2017Wilson et al, , 2019. A reduction in CYP3A4 activity has also been observed in celiac disease patients in a clinical setting (Morón et al, 2013).…”

Section: Transport and Metabolismmentioning

confidence: 99%

Potential and Challenges in Application of Physiologically Based Pharmacokinetic Modeling in Predicting Diarrheal Disease Impact on Oral Drug Pharmacokinetics

Zhang,

Arnold

2023

Drug Metab Dispos

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Word count of the introduction: 751 Word count of the minireview body (excluding introduction and conclusion): 8222 Word count of the minireview conclusion: 83 List of Non-standard Abbreviations: A amount of drug A d dissolved mass of drug A u undissolved mass of drug ACAT Advanced Compartment Absorption and Transit ADAM Advanced Dissolution Absorption Metabolism ASF absorption scale factor AUC area under the concentration-time curve BAD bile acid diarrhea BCRP Breast Cancer Resistance Protein BCS biopharmaceutics drug classes C l luminal drug concentration in the gut C max maximum concentration C s solubility of drug

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A guide to developing population files for physiologically‐based pharmacokinetic modeling in the Simcyp Simulator

Curry,

Alrubia,

Bois

et al. 2024

CPT Pharmacom & Syst Pharma

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The Simcyp Simulator is a software platform widely used in the pharmaceutical industry to conduct stochastic physiologically‐based pharmacokinetic (PBPK) modeling. This approach has the advantage of combining routinely generated in vitro data on drugs and drug products with knowledge of biology and physiology parameters to predict a priori potential pharmacokinetic changes in absorption, distribution, metabolism, and excretion for populations of interest. Combining such information with pharmacodynamic knowledge of drugs enables planning for potential dosage adjustment when clinical studies are feasible. Although the conduct of dedicated clinical studies in some patient groups (e.g., with hepatic or renal diseases) is part of the regulatory path for drug development, clinical studies for all permutations of covariates potentially affecting pharmacokinetics are impossible to perform. The role of PBPK in filling the latter gap is becoming more appreciated. This tutorial describes the different input parameters required for the creation of a virtual population giving robust predictions of likely changes in pharmacokinetics. It also highlights the considerations needed to qualify the models for such contexts of use. Two case studies showing the step‐by‐step development and application of population files for obese or morbidly obese patients and individuals with Crohn's disease are provided as the backbone of our tutorial to give some hands‐on and real‐world examples.

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Quantitative Assessment of the Impact of Crohn's Disease on Protein Abundance of Human Intestinal Drug-Metabolising Enzymes and Transporters

Cited by 10 publications

References 87 publications

Quantitative Proteomics for Translational Pharmacology and Precision Medicine: State of The Art and Future Outlook

Quantitative Proteomics for Translational Pharmacology and Precision Medicine: State of The Art and Future Outlook

Potential and Challenges in Application of Physiologically Based Pharmacokinetic Modeling in Predicting Diarrheal Disease Impact on Oral Drug Pharmacokinetics

A guide to developing population files for physiologically‐based pharmacokinetic modeling in the Simcyp Simulator

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