Literature DB >> 23427934

Predicting pharmacokinetic profiles using in silico derived parameters.

Natalie A Hosea1, Hannah M Jones.   

Abstract

Human pharmacokinetic (PK) predictions play a critical role in assessing the quality of potential clinical candidates where the accurate estimation of clearance, volume of distribution, bioavailability, and the plasma-concentration-time profiles are the desired end points. While many methods for conducting predictions utilize in vivo data, predictions can be conducted successfully from in vitro or in silico data, applying modeling and simulation techniques. This approach can be facilitated using commercially available prediction software such as GastroPlus which has been reported to accurately predict the oral PK profile of small drug-like molecules. Herein, case studies are described where GastroPlus modeling and simulation was employed using in silico or in vitro data to predict PK profiles in early discovery. The results obtained demonstrate the feasibility of adequately predicting plasma-concentration-time profiles with in silico derived as well as in vitro measured parameters and hence predicting PK profiles with minimal data. The applicability of this approach can provide key information enabling decisions on either dose selection, chemistry strategy to improve compounds, or clinical protocol design, thus demonstrating the value of modeling and simulation in both early discovery and exploratory development for predicting absorption and disposition profiles.

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Year:  2013        PMID: 23427934     DOI: 10.1021/mp300482w

Source DB:  PubMed          Journal:  Mol Pharm        ISSN: 1543-8384            Impact factor:   4.939


  11 in total

Review 1.  Human Ontogeny of Drug Transporters: Review and Recommendations of the Pediatric Transporter Working Group.

Authors:  K L R Brouwer; L M Aleksunes; B Brandys; G P Giacoia; G Knipp; V Lukacova; B Meibohm; S K Nigam; M Rieder; S N de Wildt
Journal:  Clin Pharmacol Ther       Date:  2015-09       Impact factor: 6.875

Review 2.  Physiologically Based Pharmacokinetic Modelling for First-In-Human Predictions: An Updated Model Building Strategy Illustrated with Challenging Industry Case Studies.

Authors:  Neil A Miller; Micaela B Reddy; Aki T Heikkinen; Viera Lukacova; Neil Parrott
Journal:  Clin Pharmacokinet       Date:  2019-06       Impact factor: 6.447

3.  Integrated virtual screening and molecular dynamics simulation revealed promising drug candidates of p53-MDM2 interaction.

Authors:  Abdul-Quddus Kehinde Oyedele; Temitope Isaac Adelusi; Abdeen Tunde Ogunlana; Rofiat Oluwabusola Adeyemi; Opeyemi Emmanuel Atanda; Musa Oladayo Babalola; Mojeed Ayoola Ashiru; Isong Josiah Ayoola; Ibrahim Damilare Boyenle
Journal:  J Mol Model       Date:  2022-05-10       Impact factor: 1.810

4.  Application of Pharmacokinetic Prediction Platforms in the Design of Optimized Anti-Cancer Drugs.

Authors:  Tyler C Beck; Kendra Springs; Jordan E Morningstar; Catherine Mills; Andrew Stoddard; Lilong Guo; Kelsey Moore; Cortney Gensemer; Rachel Biggs; Taylor Petrucci; Jennie Kwon; Kristina Stayer; Natalie Koren; Jaclyn Dunne; Diana Fulmer; Ayesha Vohra; Le Mai; Sarah Dooley; Julianna Weninger; Yuri Peterson; Patrick Woster; Thomas A Dix; Russell A Norris
Journal:  Molecules       Date:  2022-06-08       Impact factor: 4.927

5.  Novel in vitro dynamic metabolic system for predicting the human pharmacokinetics of tolbutamide.

Authors:  Cai-Fu Xue; Zhe Zhang; Yan Jin; Bin Zhu; Jun-Fen Xing; Guo Ma; Xiao-Qiang Xiang; Wei-Min Cai
Journal:  Acta Pharmacol Sin       Date:  2018-04-12       Impact factor: 6.150

6.  Prediction of pharmacokinetics and drug-drug interaction potential using physiologically based pharmacokinetic (PBPK) modeling approach: A case study of caffeine and ciprofloxacin.

Authors:  Min-Ho Park; Seok-Ho Shin; Jin-Ju Byeon; Gwan-Ho Lee; Byung-Yong Yu; Young G Shin
Journal:  Korean J Physiol Pharmacol       Date:  2016-12-21       Impact factor: 2.016

7.  Combination of Gemcitabine with Cell-Penetrating Peptides: A Pharmacokinetic Approach Using In Silico Tools.

Authors:  Abigail Ferreira; Rui Lapa; Nuno Vale
Journal:  Biomolecules       Date:  2019-11-04

8.  In silico modeling for tumor growth visualization.

Authors:  Fleur Jeanquartier; Claire Jean-Quartier; David Cemernek; Andreas Holzinger
Journal:  BMC Syst Biol       Date:  2016-08-08

9.  Pharmacokinetic parameters explain the therapeutic activity of antimicrobial agents in a silkworm infection model.

Authors:  Atmika Paudel; Suresh Panthee; Makoto Urai; Hiroshi Hamamoto; Tomohiko Ohwada; Kazuhisa Sekimizu
Journal:  Sci Rep       Date:  2018-01-25       Impact factor: 4.379

Review 10.  Predicting mammalian metabolism and toxicity of pesticides in silico.

Authors:  Robert D Clark
Journal:  Pest Manag Sci       Date:  2018-05-15       Impact factor: 4.845

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