Literature DB >> 24900502

Getting the MAX out of Computational Models: The Prediction of Unbound-Brain and Unbound-Plasma Maximum Concentrations.

Scot Mente1, Angela Doran1, Travis T Wager1.   

Abstract

The objective of this work was to establish that unbound maximum concentrations may be reasonably predicted from a combination of computed molecular properties assuming subcutaneous (SQ) dosing. Additionally, we show that the maximum unbound plasma and brain concentrations may be projected from a mixture of in vitro absorption, distribution, metabolism, excretion experimental parameters in combination with computed properties (volume of distribution, fraction unbound in microsomes). Finally, we demonstrate the utility of the underlying equations by showing that the maximum total plasma concentrations can be projected from the experimental parameters for a set of compounds with data collected from clinical research.

Keywords:  ADME; Cmax; blood–brain barrier; brain availability; fraction unbound; volume of distribution

Year:  2012        PMID: 24900502      PMCID: PMC4025848          DOI: 10.1021/ml300029a

Source DB:  PubMed          Journal:  ACS Med Chem Lett        ISSN: 1948-5875            Impact factor:   4.345


  18 in total

1.  Prediction of the brain-blood distribution of a large set of drugs from structurally derived descriptors using partial least-squares (PLS) modeling.

Authors:  J M Luco
Journal:  J Chem Inf Comput Sci       Date:  1999 Mar-Apr

2.  QSAR model for drug human oral bioavailability.

Authors:  F Yoshida; J G Topliss
Journal:  J Med Chem       Date:  2000-06-29       Impact factor: 7.446

3.  ElogD(oct): a tool for lipophilicity determination in drug discovery. 2. Basic and neutral compounds.

Authors:  F Lombardo; M Y Shalaeva; K A Tupper; F Gao
Journal:  J Med Chem       Date:  2001-07-19       Impact factor: 7.446

4.  Blood-brain barrier permeation models: discriminating between potential CNS and non-CNS drugs including P-glycoprotein substrates.

Authors:  Marc Adenot; Roger Lahana
Journal:  J Chem Inf Comput Sci       Date:  2004 Jan-Feb

Review 5.  The influence of drug-like concepts on decision-making in medicinal chemistry.

Authors:  Paul D Leeson; Brian Springthorpe
Journal:  Nat Rev Drug Discov       Date:  2007-11       Impact factor: 84.694

6.  Structural pairwise comparisons of HLM stability of phenyl derivatives: Introduction of the Pfizer metabolism index (PMI) and metabolism-lipophilicity efficiency (MLE).

Authors:  Mark L Lewis; Lourdes Cucurull-Sanchez
Journal:  J Comput Aided Mol Des       Date:  2008-09-18       Impact factor: 3.686

7.  In silico prediction of volume of distribution in human using linear and nonlinear models on a 669 compound data set.

Authors:  Giuliano Berellini; Clayton Springer; Nigel J Waters; Franco Lombardo
Journal:  J Med Chem       Date:  2009-07-23       Impact factor: 7.446

8.  In silico prediction of unbound brain-to-plasma concentration ratio using machine learning algorithms.

Authors:  Hongming Chen; Susanne Winiwarter; Markus Fridén; Madeleine Antonsson; Ola Engkvist
Journal:  J Mol Graph Model       Date:  2011-04-27       Impact factor: 2.518

9.  Computation of brain-blood partitioning of organic solutes via free energy calculations.

Authors:  F Lombardo; J F Blake; W J Curatolo
Journal:  J Med Chem       Date:  1996-11-22       Impact factor: 7.446

10.  Hydrogen bonding. 33. Factors that influence the distribution of solutes between blood and brain.

Authors:  M H Abraham; H S Chadha; R C Mitchell
Journal:  J Pharm Sci       Date:  1994-09       Impact factor: 3.534

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