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Best practices for chemical data curation and QSAR model ...

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Original<br />

Dataset<br />

Structure<br />

Curation/<br />

Harmonization<br />

Database<br />

Screening Using<br />

Applicability<br />

Domain<br />

Experimental<br />

Validation<br />

Predictive <strong>QSAR</strong> Modeling Workflow*<br />

Split into<br />

Training, Test<br />

<strong>and</strong> External<br />

Validation<br />

sets<br />

External validation<br />

Using Applicability<br />

Domain<br />

Multiple<br />

Training<br />

Sets<br />

Multiple<br />

Test<br />

Sets<br />

Y-r<strong>and</strong>omization<br />

Combi-<strong>QSAR</strong><br />

Modeling<br />

Activity<br />

Prediction<br />

Validated Predictive<br />

Models with High<br />

Internal & External<br />

Accuracy<br />

*Tropsha, A., Gramatica, P., Gombar, V. The importance of being earnest:…<br />

Quant. Struct. Act. Relat. Comb. Sci. 2003, 22, 69-77.<br />

Tropsha & Golbraikh, Curr. Pharm. Des., 2007, 13, 3494-3504<br />

Only accept<br />

<strong>model</strong>s that<br />

passed both<br />

internal <strong>and</strong><br />

external<br />

accuracy<br />

filters

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