The re-use of data is an ever present issue within the pharmaceutical industry. Publicly available data is an important resource for companies looking to develop new drugs, and find new uses for current ones. The search has just become easier with the publication of the DrugMatrix database by the National Toxicology Program.
DrugMatrix is a large molecular toxicology reference database and informatics system. It contains data on the effects of more than 600 therapeutic, industrial and environment chemicals at a variety of doses and exposure times. For each of these compounds, relevant data curated from the literature is available, as well as assay results for inhibition of 132 protein targets. These have been chosen for their importance in drug development, and so among them, we can find drug-metabolizing enzymes or proteins involved in important toxicities.
The core of DrugMatrix is a set of highly standardised toxicological experiments performed in male, Sprague-Dawley rats, resulting in a wealth of data regarding histopathology, clinical chemistry and gene expression responses elicited by 638 compounds. The main strength of this database is that it provides the basis to linking macroscopic observations to alterations in genetic pathways. And the great news is, Safety Intelligence Program (SIP) users can now access this fantastic resource, with the addition of ~88,000 curated assertions with DrugMatrix evidence. The inclusion of the DrugMatrix data in SIP makes it possible to answer questions that were currently not addressable through the DrugMatrix interface, as the data is now integrated with knowledge extracted from several other relevant sources such as Medline, DailyMed and FDA NDAs.

DrugMatrix interface showing the results of an experiment where the administration of 2mg/kg Cisplatin for 3 days caused a 1.4-fold increase in blood urea nitrogen.
To give an example, let’s look at the effects of Cisplatin in rats. According to DrugMatrix, this compound increases blood urea nitrogen level, which is an important safety signal because it is an indicator of renal health. If the kidneys are not working properly and the glomerular filtration rate decreases, blood urea nitrogen will increase. This compound level can also be associated with heart failure, dehydration, fever or high-protein diet.

SIP ToxPath knowledgebase summary matrix showing that Cisplatin-induced increases in blood urea nitrogen occur in different species and relevant datasources
The next thing we might be interested in knowing is whether the effect is replicated in other animal species. While DrugMatrix only includes rat information, a quick search in SIP will point to the answer. Firstly, we will see that apart from DrugMatrix, there are Medline records describing the same observation in Sprague-Dawley and Fischer 344 strains. Increases in blood urea nitrogen are also described in mouse and rabbit. More importantly, this finding is also seen in humans according to DailyMed and the Electronic Medicines Compendium.
But should we worry about kidney function because of this increase? We can search SIP to see if Cisplatin is known to be associated with kidney dysfunction in patients. Again, we can see that Cisplatin is linked to liver disorder-related biomedical observations in 43 assertions from 6 different datasources. This makes sense, as Cisplatin is a well-known nephrotoxicant and kidney toxicity is dose-limiting in this type of chemotherapy.

Summary matrix of associations between Cisplatin and kidney disorder in humans, and the sources where the data has been obtained from.
Finally, we might also be interested in assessing whether compounds that cause an increase in blood urea nitrogen share a similar structure or protein target. While DrugMatrix is an excellent tool for this task, it only queries the 600+ compounds that are included in the dataset. Conversely, at present, SIP contains 85,996 compounds and 22,036 proteins, which are part of 2,574,454 assertions, and this allows the users to expand the search and increases the likelihood of finding meaningful results.
This is a very good example that when it comes to toxicology and pathology data, there is certainly strength in numbers, and when two powerful tools such as these are put together, their usefulness is greatly enhanced.

A small subset of curated SIP assertions linking Cisplatin to kidney disorder in humans.


