ArticleJournal of pharmaceutical sciences2017
The Promises of Quantitative Proteomics in Precision Medicine.
Article in Journal of pharmaceutical sciences, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
20 citing papers in PubMed, 42 citations in OpenAlex.
- Transitioning from Transcriptomics to Proteomics: Enhancing Mechanistic Accuracy in PBPK Modeling via Absolute Protein Abundances.CPT: pharmacometrics & systems pharmacology · 2026Article
- Applying molecular dynamics simulations to validate OCT1 substrates uncovers vitamin K1 as a high-affinity ligand.Frontiers in pharmacology · 2026Article
- Identification and applications of disease-associated differential human and bacterial proteins with metaproteomic evidence.Health information science and systems · 2025Article
- Utility of Protein Markers in COVID-19 Patients.International journal of molecular sciences · 2025Review
- The Impact of Serum/Plasma Proteomics on SARS-CoV-2 Diagnosis and Prognosis.International journal of molecular sciences · 2024Review
- Article
- Quantitative Proteomics in Translational Absorption, Distribution, Metabolism, and Excretion and Precision Medicine.Pharmacological reviews · 2022Review
- Proteomics of colorectal cancer liver metastasis: A quantitative focus on drug elimination and pharmacodynamics effects.British journal of clinical pharmacology · 2022Article
- Ultrasensitive Quantification of Drug-metabolizing Enzymes and Transporters in Small Sample Volume by Microflow LC-MS/MS.Journal of pharmaceutical sciences · 2021Article
- Signaling pathways in intestinal homeostasis and colorectal cancer: KRAS at centre stage.Cell communication and signaling : CCS · 2021Review
- Hepatic Cytochrome P450 Abundance and Activity in the Developing and Adult Göttingen Minipig: Pivotal Data for PBPK Modeling.Frontiers in pharmacology · 2021Article
- Towards Building a Quantitative Proteomics Toolbox in Precision Medicine: A Mini-Review.Frontiers in physiology · 2021Review
- Hepatic Transporter Alterations by Nuclear Receptor Agonist T0901317 in Sandwich-Cultured Human Hepatocytes: Proteomic Analysis and PBPK Modeling to Evaluate Drug-Drug Interaction Risk.The Journal of pharmacology and experimental therapeutics · 2020Article
- Analysis of Spatiotemporal Urine Protein Dynamics to Identify New Biomarkers for Sepsis-Induced Acute Kidney Injury.Frontiers in physiology · 2020Article
- Pharmacogenomic Testing to Guide Personalized Cancer Medicine Decisions in Private Oncology Practice: A Case Study.Frontiers in oncology · 2020Article
- Toward a Consensus on Applying Quantitative Liquid Chromatography-Tandem Mass Spectrometry Proteomics in Translational Pharmacology Research: A White Paper.Clinical pharmacology and therapeutics · 2019Article
- A repository of protein abundance data of drug metabolizing enzymes and transporters for applications in physiologically based pharmacokinetic (PBPK) modelling and simulation.Scientific reports · 2019Article
- Simultaneous absolute quantitation of ATP-binding cassette transporters in normal dog tissues by signature peptide analysis using a LC/MS/MS method.Research in veterinary science · 2019Article
- Age- and Genotype-Dependent Variability in the Protein Abundance and Activity of Six Major Uridine Diphosphate-Glucuronosyltransferases in Human Liver.Clinical pharmacology and therapeutics · 2019Article
- Critical Issues and Optimized Practices in Quantification of Protein Abundance Level to Determine Interindividual Variability in DMET Proteins by LC-MS/MS Proteomics.Clinical pharmacology and therapeutics · 2018Review
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
Precision medicine approach has a potential to ensure optimum efficacy and safety of drugs at individual patient level. Physiologically based pharmacokinetic and pharmacodynamic (PBPK/PD) models could play a significant role in precision medicine by predicting interindividual variability in drug disposition and response. In order to develop robust PBPK/PD models, it is imperative that the critical physiological parameters affecting drug disposition and response and their variability are precisely characterized. Currently used PBPK/PD modeling software, for example, Simcyp and Gastroplus, encompass information such as organ volumes, blood flows to organs, body fat composition, glomerular filtration rate, etc. However, the information on the interindividual variability of the majority of the proteins associated with PK and PD, for example, drug metabolizing enzymes, transporters, and receptors, are not fully incorporated into these PBPK modeling platforms. Such information is significant because the population factors such as age, genotype, disease, and gender can affect abundance or activity of these proteins. To fill this critical knowledge gap, mass spectrometry-based quantitative proteomics has emerged as an important technique to characterize interindividual variability in the protein abundance of drug metabolizing enzymes, transporters, and receptors. Integration of these quantitative proteomics data into in silico PBPK/PD modeling tools will be crucial toward precision medicine.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.