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Information : Modeling Challenge 2008

Contents:
  1. Why ‘Human Oral Bioavailability’?
  2. Who wins what?
  3. Data
  4. Software and Tool
  5. What to send back to us and when
  6. Rules
  7. Some tips
  8. References


What to send back to us and when

Participants are requested to send us the following information:

1)    Your name, title and organization/university you represent, if any

2)    A brief write-up on the methodology followed; including descriptors generated, the final set of descriptors used to build the model, steps carried out
       for model building, the algorithm used for model building, any metrics generated as part of model building and the tools /software used for these various steps.

3)    A text file containing the predictions for the test set compounds along with identifier; Optionally, you may also send an sdf of the test set compounds
       along with  the prediction.


Please send the required data and information to editor@qsarworld.com.

The last date for submission of entries is 31st January 2009. 


Rules

  • The judges’ decision is final in choosing the winners.

  • Entries from employees of Strand Life Sciences Pvt Ltd will not be considered for prizes.

  • The models submitted for the contest become the property of ‘QSARworld’.

Some tips

‘QSARworld’ features some write-ups and articles on building and validation of QSAR models. Following sections may be useful read
in this aspect :


http://www.qsarworld.com/qsar-guest-column1.php

http://www.qsarworld.com/files/bender_article_3.pdf

http://www.qsarworld.com/files/ACS_QSAR_Absorption-Rate-Constant.pdf

http://www.qsarworld.com/qsar-machine-learning.php?mm=2

If a simple regression model does not yield good results, a nested approach can be tried.  Read a primer on Nested Regression model here >> Read

To know about how Sarchitect Designer builds nested models, read the manual after downloading the tool.


References

1.  Lipinski, C. A.; Lombardo, F.; Dominy, B. W.; Feeney, P. J.Experimental and computational approaches to estimate solubility and permeability in drug discovery
     and development settings. Adv. Drug Del. Rev. 1997, 23, 3–25.

2.  Larsen, T.; Link, A. A timely reassessment of early prediction in the bioavailability of orally administered drugs. Angew. Chem. Int. Ed. Engl. 2005, 44, 4432-4.

3.  Yoshida, F.; Topliss, J. G. QSAR model for drug human oral bioavailability. J. Med. Chem. 2000, 43, 2575-85.
     Erratum in: J. Med. Chem. 2000, 43, 4723.

4.  Bains, W.; Gilbert, R.; Sviridenko, L.; Gascon, J. M.; Scoffin, R.; Birchall, K.; Harvey, I.; Caldwell, J. Evolutionary computational methods to predict
     oral bioavailability QSPRs. Curr. Opin. Drug  Disc. Dev. 2002, 5, 44–5.

5.  Pintore, M.; Van de Waterbeemd, H.; Piclin, N.;  Chrétien, J. R.Prediction of oral bioavailability by adaptive fuzzy partitioning.
     Eur. J. Med. Chem. 2003, 38, 427-431.

6.  Andrews,  C. W.; Bennett.,L.; Yu, L. X. Predicting human oral bioavailability of a compound: development of a novel quantitative structure-bioavailability      
     relationship. Pharm. Res. 2000, 17, 639-44.

7.  Hou, T. ADME databases, http://modem.ucsd.edu/adme/databases/databases_extend.htm

8.  Molecular Descriptors the free online resource, http://www.moleculardescriptors.eu


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