Literature DB >> 26478759

Structure Activity Relationships (SARs) Using a Structurally Diverse Drug Database: Validating Success of Predictor Tools.

Malcolm J D'Souza1, Fumie Koyoshi1, Lynn M Everett2.   

Abstract

ADME/Tox (absorption, distribution, metabolism, elimination and toxicity) technology is traditionally associated as a tool in the drug discovery process which is often used to predict the efficiency of drug adsorption, distribution, metabolic pathways, and elimination. For the past four years we have been involved in an effort to evaluate readily available Food and Drug Administration (FDA) consumer drug profiles and pharmacological data. Portable Document Format (PDF) data from drug profiles available on the FDA Drug Information website were used to create a searchable FDA Consumer Drug Database© using Bio-Rad's KnowItAll® platform which includes ADME/Tox in silico predictors. 14 pertinent pharmaceutical and pharmacological properties were collected for 75 structurally diverse consumer prescription drugs, and for several drugs, not all properties were completely populated. The major objective of this investigation was to validate the platforms prediction models for plasma protein binding (PPB) and bioavailability (BIO).

Entities:  

Keywords:  (quantitative) structure activity relationship (Q)SAR; ADME/Tox; FDA consumer drug database©; KnowItAll®; chemical informatics; predictor tools

Year:  2009        PMID: 26478759      PMCID: PMC4605434     

Source DB:  PubMed          Journal:  Pharm Rev        ISSN: 1918-5561


  7 in total

Review 1.  Reengineering the pharmaceutical industry by crash-testing molecules.

Authors:  Peter W Swaan; Sean Ekins
Journal:  Drug Discov Today       Date:  2005-09-01       Impact factor: 7.851

2.  A model validation and consensus building environment.

Authors:  T Abshear; G M Banik; M L D'Souza; K Nedwed; C Peng
Journal:  SAR QSAR Environ Res       Date:  2006-06       Impact factor: 3.000

Review 3.  A flexible approach for optimising in silico ADME/Tox characterisation of lead candidates.

Authors:  Yann Bidault
Journal:  Expert Opin Drug Metab Toxicol       Date:  2006-02       Impact factor: 4.481

Review 4.  In silico prediction of ADMET properties: how far have we come?

Authors:  John C Dearden
Journal:  Expert Opin Drug Metab Toxicol       Date:  2007-10       Impact factor: 4.481

5.  Extracting Relevant Information from FDA Drug Files to Create a Structurally Diverse Drug Database Using KnowItAll®

Authors:  Malcolm J D'Souza; Fumie Koyoshi
Journal:  Pharm Rev       Date:  2009-05-08

Review 6.  Computational toxicology: heading toward more relevance in drug discovery and development.

Authors:  Dale E Johnson; Amie D Rodgers
Journal:  Curr Opin Drug Discov Devel       Date:  2006-01

7.  DrugBank: a comprehensive resource for in silico drug discovery and exploration.

Authors:  David S Wishart; Craig Knox; An Chi Guo; Savita Shrivastava; Murtaza Hassanali; Paul Stothard; Zhan Chang; Jennifer Woolsey
Journal:  Nucleic Acids Res       Date:  2006-01-01       Impact factor: 16.971

  7 in total
  6 in total

1.  Evolution of a Structure-Searchable Database into a Prototype for a High-Fidelity SmartPhone App for 62 Common Pesticides Used in Delaware.

Authors:  Malcolm J D'Souza; Benjamin Barile; Aaron F Givens
Journal:  ... Int Conf Ind Instrum Control       Date:  2015-05

2.  Deficiencies in the reporting of VD and t(1/2) in the FDA approved chemotherapy drug inserts.

Authors:  Malcolm J D'Souza; Ghada J Alabed
Journal:  Pharm Rev       Date:  2010-02-03

3.  Integrative Biological Chemistry Program Includes The Use Of Informatics Tools, GIS And SAS Software Applications.

Authors:  Malcolm J D'Souza; Richard J Kashmar; Kent Hurst; Frank Fiedler; Catherine E Gross; Jasbir K Deol; Alora Wilson
Journal:  Contemp Issues Educ Res (Littleton)       Date:  2015 Third Quarter

4.  Data-intensive Undergraduate Research Project Informs to Advance Healthcare Analytics.

Authors:  M J D'Souza; D Wentzien; R Bautista; J Santana; M Skivers; S Stotts; F Fiedler
Journal:  IEEE Signal Process Med Biol Symp       Date:  2019-01-17

5.  Manipulating In-House Designed Drug Databases For The Prediction of pH-Dependent Aqueous Drug Solubility.

Authors:  Malcolm J D'Souza; Ghada J Alabed; Melissa Earley; Natalia Roberts; Fady J Gerges
Journal:  Am J Health Sci       Date:  2013

6.  A Database Developed with Information Extracted from Chemotherapy Drug Package Inserts to Enhance Future Prescriptions.

Authors:  Malcolm J D'Souza; Ghada J Alabed; Jordan M Wheatley; Natalia Roberts; Yogasudha Veturi; Xia Bi; Christopher Hart Continisio
Journal:  Conf Comput Vis Pattern Recognit Workshops       Date:  2011
  6 in total

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