Performance of DPA compared to DPA+MFBM (DPA combined with MACCS, GpiDAPH3, TGD and TGT molecular fingerprints) in different TOP positions.

<p>Performance of DPA compared to DPA+MFBM (DPA combined with MACCS, GpiDAPH3, TGD and TGT molecular fingerprints) in different TOP positions.</p

Flowchart of the ADE detection process for <i>pancreatitis</i>.

<p>Flowchart of the ADE detection process for <i>pancreatitis</i>.</p

Examples of candidates selected through the combination of DPA and MFBM (MACCS fingerprints) and similar molecules in the <i>pancreatitis</i> reference standard, along with OR05 (lower 5^th percentile of the Odds Ratio measure of association in DPA analysis) and TC (Tanimoto coefficient) values.

<p>Different level of <i>pancreatitis</i>-causal information was found for the candidate drugs in the literature.</p

The model generates interactions through the multiplication of the matrix M₁ (Established DDI matrix) by the matrix M₂ (Interaction profile similarity matrix.

<p>Note that each cell shows the TC between drugs A, B and C but interactions with more drugs are considered to calculate the TC value). The values in the diagonal of the matrices are set 0 since drug interactions with themselves are not taken into account. In the final matrix M₃ only the maximum value in the multiplication-array in each cell is preserved and a symmetry-based transformation is carried out retaining the highest TC value. In the example, the initial interactions A–B and A–C (red color) have a TC score of 0.9 in the matrix M₃. The system generated a new predicted interaction between B and C with a TC score of 0.8 (green color).</p

Enrichment factor (a) and precision (b) achieved by the model regarding random results for top drugs sold in 2010 (test set D).

<p>The test set of drugs are sorted according to the enrichment factor.</p

Some examples of correct interactions predicted for the 50 most frequently sold drugs in 2010 in which the model generated interactions through the comparison of drugs belonging to different pharmacological classes.

<p>TC is the Tanimoto coefficient.</p>1<p>The similarity between drugs is based on the drug-drug interaction profile.</p

Receiver Operating Characteristic (ROC) (a) and Precision-Recall (b) curves evaluating the set of 278 EHR ADE candidates with OR05 and different MFBMs.

<p>It is worth noting that although OR05 algorithm is very useful to originate the first set of 278 candidate drugs related to <i>pancreatitis</i> (99 out of 278 drugs were already included in the <i>pancreatitis</i> reference standard set), the precision of the method is constant within this set. However, an improvement of the precision in top positions can be achieved using MFBM (in the graphic: black-OR05, red-MACCS, green-GpiDAPH3, yellow-TGT, blue-TGD).</p

Receiver Operating Characteristic (ROC) (a) and Precision-Recall (b) curves evaluating the test set of EHR <i>pancreatitis</i> candidates (in the graphic are not included the drugs already in the reference standard: 21 true positives versus 158 false positives, black-OR05, red-MACCS, green-GpiDAPH3, yellow-TGT, blue-TGD).

<p>Receiver Operating Characteristic (ROC) (a) and Precision-Recall (b) curves evaluating the test set of EHR <i>pancreatitis</i> candidates (in the graphic are not included the drugs already in the reference standard: 21 true positives versus 158 false positives, black-OR05, red-MACCS, green-GpiDAPH3, yellow-TGT, blue-TGD).</p

Comparison between the TC for all the pairs of drugs in a matrix of 928×928 using MACCS and IPF fingerprints.

<p>The correlation coefficient (r) calculated through linear regression is 0.167 and p<.0001.</p

ROC curves for test set D: a) ROC curve generated by the IPF model for test set D.

<p>Interactions for the top 50 drugs (41 generic names) confirmed in drugs.com/drugdex were considered as true positives within all the possible interactions in a matrix of 41×928 drugs. Interactions already in the initial DrugBank DDI database (matrix M₁) were not included in the analysis; b) ROC showed by a model applied to test D using MACCS fingerprints; c) ROC curve calculated by the IPF model for test set D but excluding CYP interactions; d) ROC showed by the MACCS fingerprints model applied to the test D without CYP interactions.</p