Assay-ADR associations

The ADR tools in BioPrint assist the user in accessing and implementing the ADR data included in BioPrint. One can quickly access the ADRs listed for a selected compound, the ADRs related to a selected body system, and the ADRs statistically associated with in vitro assay data (ADR associations). The ADR associations can be searched both by assay and by ADR. When searching by assay, ADRs associated with the selected assays and IC50 values are returned along with the risk assessment. The risk information includes the number of compounds that list the ADR, and the number of compounds... 

Figure 5. Heat map showing some of the identified assay-ADR associations. 87 pharmacological assays are clustered on the X-axis and 48 ADRs are clustered on the Y-axis. Red spots in the heat map indicate significant associations. The criteria for significant associations are those described in paragraph 7.2.

Hits on individual assays can be analyzed in a couple of different ways. First, drugs can be identified that have similar strength hits and then the ADR profiles of these drugs can be examined to identify ADRs that maybe associated with these hits. Also, contained in BioPrint are extensive collections of ADR associations [2], which have been identified by querying the database for statistically significant correlations between individual assays and individual ADRs. These ADRs are stored in the database and can be accessed by searching assay or the ADR. It is also useful to consult the pharmacokinetic data to confirm that the strength of the in vitro hit is consistent with in vivo exposure levels. 

On searching the database among ADR associations we can retrieve a large number of associations for the calcium channel diltiazem site binding assay. Two ADR associations are shown in Figures 2.19 and 2.20. The ADR tinnitus has a... 

A data-mining engine was used to associate the binary ADR variables with each assay. ADRs listed on less than 0.5% of the drug labels were excluded. 

The BioPrint collection of ADR associations can also be viewed using clustering. In Fig. 5, the heat map shows a subset of ADRs clustered on the vertical axis versus the assays on the horizontal axis. At the bottom right of this figure, the seemingly disparate ADRs of prolactin increase and torsades de pointes cluster closely together. Further research in literature shows that in fact both of these are well known ADRs of atypical antipsychotics. " ... 

At the level of individual hits, the database can be queried to retrieve either marketed BioPrint drugs that have that same activity, or the ADR associations discussed in the previous section can be queried to identify potential ADRs and their relative risks. At the profile level, compounds with similar profiles can be identified using standard statistical methods such as similarity metrics and hierarchical clustering. This similarity can be assessed using the whole panel of assays or by using selected subsets of those assays as determined by the user. Once compounds with similar profiles have been identified, in vivo data for the similar compoimds can be accessed and examined for information that may permit the user to anticipate in vivo effects. 

BioPrint consists of a large database and a set of tools with which both the data and the models generated from the data can be accessed. The database contains structural information, in vivo and in vitro data on most of the marketed pharmaceuticals and a variety of other reference compounds. The in vitro data generated consist of panels of pharmacology and early ADME assays. The in vivo data consist of ADR data extracted from drug labels, mechanisms of action, associated therapeutic areas, pharmacokinetic (PK) data and route of administration data. 

Statistical Associations between In vitro Assay Data and ADRs... 

The associations that met the above criteria were further developed using a series of binned IC50 data to quantify the ADR risks according to IC50 value for each assay. The IC50 bins are as follows ... 

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