Literature DB >> 30499410

In Silico Assessment of ADME Properties: Advances in Caco-2 Cell Monolayer Permeability Modeling.

Hai Pham-The1, Miguel Á Cabrera-Pérez2,3, Nguyen-Hai Nam1, Juan A Castillo-Garit4, Bakhtiyor Rasulev5, Huong Le-Thi-Thu6, Gerardo M Casañola-Martin5.   

Abstract

One of the main goals of in silico Caco-2 cell permeability models is to identify those drug substances with high intestinal absorption in human (HIA). For more than a decade, several in silico Caco-2 models have been made, applying a wide range of modeling techniques; nevertheless, their capacity for intestinal absorption extrapolation is still doubtful. There are three main problems related to the modest capacity of obtained models, including the existence of inter- and/or intra-laboratory variability of recollected data, the influence of the metabolism mechanism, and the inconsistent in vitro-in vivo correlation (IVIVC) of Caco-2 cell permeability. This review paper intends to sum up the recent advances and limitations of current modeling approaches, and revealed some possible solutions to improve the applicability of in silico Caco-2 permeability models for absorption property profiling, taking into account the above-mentioned issues. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.

Entities:  

Keywords:  ADME; Biopharmaceutics classification system (BCS); Caco-2 cell permeability; Human intestinalzzm321990absorption; In Vitro-In Vivo correlation (IVIVC); QSAR/QSPR.

Mesh:

Year:  2018        PMID: 30499410     DOI: 10.2174/1568026619666181130140350

Source DB:  PubMed          Journal:  Curr Top Med Chem        ISSN: 1568-0266            Impact factor:   3.295


  6 in total

1.  PerMM: A Web Tool and Database for Analysis of Passive Membrane Permeability and Translocation Pathways of Bioactive Molecules.

Authors:  Andrei L Lomize; Jacob M Hage; Kevin Schnitzer; Konstantin Golobokov; Mitchell B LaFaive; Alexander C Forsyth; Irina D Pogozheva
Journal:  J Chem Inf Model       Date:  2019-07-01       Impact factor: 4.956

2.  Development of a Hierarchical Support Vector Regression-Based In Silico Model for Caco-2 Permeability.

Authors:  Giang Huong Ta; Cin-Syong Jhang; Ching-Feng Weng; Max K Leong
Journal:  Pharmaceutics       Date:  2021-01-28       Impact factor: 6.321

Review 3.  Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries.

Authors:  Chandrabose Selvaraj; Ishwar Chandra; Sanjeev Kumar Singh
Journal:  Mol Divers       Date:  2021-10-23       Impact factor: 2.943

4.  Promising Hybrids Derived from S-Allylcysteine and NSAIDs Fragments against Colorectal Cancer: Synthesis, In-vitro Evaluation, Drug-Likeness and In-silico ADME/tox Studies.

Authors:  Angie Herrera-R; Wilson Castrillón; Manuel Pastrana; Andres F Yepes; Wilson Cardona-G
Journal:  Iran J Pharm Res       Date:  2021       Impact factor: 1.696

5.  Assessment of the Intestinal Absorption of Higher Olefins by the Everted Gut Sac Model in Combination with In Silico New Approach Methodologies.

Authors:  Quan Shi; Juan-Carlos Carrillo; Michael G Penman; Jason Manton; Elena Fioravanzo; Robert H Powrie; Clifford R Elcombe; Tilly Borsboom-Patel; Yuan Tian; Hua Shen; Peter J Boogaard
Journal:  Chem Res Toxicol       Date:  2022-07-13       Impact factor: 3.973

6.  Synthesis and biological activity, and molecular modelling studies of potent cytotoxic podophyllotoxin-naphthoquinone compounds.

Authors:  Ha Thanh Nguyen; Quynh Giang Nguyen Thi; Thu Ha Nguyen Thi; Phuong Hoang Thi; Giang Le-Nhat-Thuy; Tuyet Anh Dang Thi; Bao Le-Quang; Hai Pham-The; Tuyen Van Nguyen
Journal:  RSC Adv       Date:  2022-08-09       Impact factor: 4.036

  6 in total

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