Literature DB >> 30554411

From Endogenous Compounds as Biomarkers to Plasma-Derived Nanovesicles as Liquid Biopsy; Has the Golden Age of Translational Pharmacokinetics-Absorption, Distribution, Metabolism, Excretion-Drug-Drug Interaction Science Finally Arrived?

David Rodrigues1, Andrew Rowland2.   

Abstract

It is now established that a drug's pharmacokinetics (PK) absorption, distribution, metabolism, excretion (ADME) and drug-drug interaction (DDI) profile can be modulated by age, disease, and genotype. In order to facilitate subject phenotyping and clinical DDI assessment, therefore, various endogenous compounds (in plasma and urine) have been pursued as drug-metabolizing enzyme and transporter biomarkers. Compared with biomarkers, however, the topic of circulating extracellular vesicles as "liquid biopsy" has received little attention within the ADME community; most organs secrete nanovesicles (e.g., exosomes) into the blood that contain luminal "cargo" derived from the originating organ (proteins, messenger RNA, and microRNA). As such, ADME profiling of plasma exosomes could be leveraged to better define genotype-phenotype relationships and the study of ontogeny, disease, and complex DDIs. If methods to support the isolation of tissue-derived plasma exosomes are successfully developed and validated, it is envisioned that they will be used jointly with genotyping, biomarkers, and modeling tools to greatly progress translational PK-ADME-DDI science.
© 2019 The Authors Clinical Pharmacology & Therapeutics © 2019 American Society for Clinical Pharmacology and Therapeutics.

Entities:  

Year:  2019        PMID: 30554411     DOI: 10.1002/cpt.1328

Source DB:  PubMed          Journal:  Clin Pharmacol Ther        ISSN: 0009-9236            Impact factor:   6.875


  23 in total

Review 1.  Quantitative Proteomics in Translational Absorption, Distribution, Metabolism, and Excretion and Precision Medicine.

Authors:  Deepak Ahire; Laken Kruger; Sheena Sharma; Vijaya Saradhi Mettu; Abdul Basit; Bhagwat Prasad
Journal:  Pharmacol Rev       Date:  2022-07       Impact factor: 18.923

2.  Plasma Carboxylesterase 1 Predicts Methylphenidate Exposure: A Proof-of-Concept Study Using Plasma Protein Biomarker for Hepatic Drug Metabolism.

Authors:  Jian Shi; Jingcheng Xiao; Xinwen Wang; Sun Min Jung; Barry E Bleske; John S Markowitz; Kennerly S Patrick; Hao-Jie Zhu
Journal:  Clin Pharmacol Ther       Date:  2021-11-30       Impact factor: 6.903

Review 3.  Potential implications of DMET ontogeny on the disposition of commonly prescribed drugs in neonatal and pediatric intensive care units.

Authors:  Siavosh Naji-Talakar; Sheena Sharma; Leslie A Martin; Derek Barnhart; Bhagwat Prasad
Journal:  Expert Opin Drug Metab Toxicol       Date:  2021-01-20       Impact factor: 4.481

4.  Application of Machine Learning in Translational Medicine: Current Status and Future Opportunities.

Authors:  Nadia Terranova; Karthik Venkatakrishnan; Lisa J Benincosa
Journal:  AAPS J       Date:  2021-05-18       Impact factor: 4.009

5.  Ultrasensitive Quantification of Drug-metabolizing Enzymes and Transporters in Small Sample Volume by Microflow LC-MS/MS.

Authors:  Deepak Suresh Ahire; Abdul Basit; Matthew Karasu; Bhagwat Prasad
Journal:  J Pharm Sci       Date:  2021-03-28       Impact factor: 3.784

Review 6.  Current status and future directions of high-throughput ADME screening in drug discovery.

Authors:  Wilson Z Shou
Journal:  J Pharm Anal       Date:  2020-05-23

7.  Plasma exosomes exacerbate alcohol- and acetaminophen-induced toxicity via CYP2E1 pathway.

Authors:  Mohammad A Rahman; Sunitha Kodidela; Namita Sinha; Sanjana Haque; Pradeep K Shukla; Radhakrishna Rao; Santosh Kumar
Journal:  Sci Rep       Date:  2019-04-25       Impact factor: 4.379

8.  Pregnancy-Related Hormones Increase Nifedipine Metabolism in Human Hepatocytes by Inducing CYP3A4 Expression.

Authors:  Raju Khatri; Natasha Kulick; Rebecca J B Rementer; John K Fallon; Craig Sykes; Amanda P Schauer; Melina M Malinen; Merrie Mosedale; Paul B Watkins; Angela D M Kashuba; Kim A Boggess; Philip C Smith; Kim L R Brouwer; Craig R Lee
Journal:  J Pharm Sci       Date:  2020-09-12       Impact factor: 3.534

9.  Data-driven personalization of a physiologically based pharmacokinetic model for caffeine: A systematic assessment.

Authors:  Rebekka Fendt; Ute Hofmann; Annika R P Schneider; Elke Schaeffeler; Rolf Burghaus; Ali Yilmaz; Lars Mathias Blank; Reinhold Kerb; Jörg Lippert; Jan-Frederik Schlender; Matthias Schwab; Lars Kuepfer
Journal:  CPT Pharmacometrics Syst Pharmacol       Date:  2021-06-26

Review 10.  Liquid Chromatography-Tandem Mass Spectrometry (LC-MS/MS)-Based Proteomics of Drug-Metabolizing Enzymes and Transporters.

Authors:  Jiapeng Li; Hao-Jie Zhu
Journal:  Molecules       Date:  2020-06-11       Impact factor: 4.411

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