Object

Title: In silico modeling of proarrhythmic potential of drug candidates

Abstract:

The main objective of the work was to develop a tool supporting conventional methods of the proarrhythmic potential of the chemicals assessment with the use of in silico modelling techniques.The aim of the developed screening tool is discrimination the torsadogenic agents (with high hERG channel blocking potency) from potentially safe compounds at the early stage of the drug discovery process. The data set of the experimentally measured IC50 values with the relevant information regarding factors influencing the laboratory measurement results is the result of the first part of the work.The next objective of the work was to develop a standardization method for the IC¬50 values obtained with use of the different cell lines or temperature.The model development process included selection of the input vector components and a classification algorithm. Artificial neural networks, Bayesian algorithms and recursive partitioning methods were used for the predictive models development.Classification models were evaluated in modified 10-fold cross-validation procedure and with use of the independent external data set.The overall classification accuracy of the optimal model found during the numerical experimentation estimated on external test set was 87%. The predictive potential of the developed model stands out from models proposed so far in the literature despite the usage of rigorous tes ; ting methods.

Place of publishing:

Kraków

Level of degree:

2 - studia doktoranckie

Degree discipline:

farmacja

Degree grantor:

Wydział Farmaceutyczny

Promoter:

Brandys, Jerzy

Date issued:

2011

Identifier:

oai:dl.cm-uj.krakow.pl:3440

Call number:

ZB-116302

Language:

pol

Access rights:

nieograniczony

Object collections:

Last modified:

Jun 26, 2023

In our library since:

Mar 7, 2013

Number of object content hits:

1 093

Number of object content views in PDF format

79

All available object's versions:

http://dl.cm-uj.krakow.pl:8080/publication/3440

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ZB-116302 Jun 26, 2023
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