Cloud-based simulation of target drug compounds
Transinsight is a German SME which develops software products in the area of bioinformatics. This case study addresses the identification of existing drugs to treat illnesses other than those for which they are currently prescribed.
Start date: 01/07/2013
Duration in months: 18
Problem Description
The journey for a drug from invention to market is a long one. It has been estimated that the time required to develop a new drug de novo ranges between 10 and 17 years. The chance for a new drug to actually make it to market is only 1:5000. Repositioning existing drugs for new diseases could deliver the productivity increases that the industry needs. A prerequisite for drug repurposing is drug promiscuity, a drug’s ability to bind to several targets. Research indicates that there is a correlation between promiscuity and structural similarity as well as binding site similarity of protein targets.
Goals
Reduce time to solution
Challenges
Implement on HPC a discovery drug-target correlation system.
Innovation results
The use of an HPC-Cloud infrastructure combined with algorithmic improvements enabled substantially better computational performance. This was achieved through the parallelisation of the algorithms used combined with the more efficient use of memory. This resulted in a significant reduction in the time and cost of the evaluation of a single compound.
Business impact
Transinsight estimates that there are hundreds of potential users of its proposed service. Each user represents a potential profit of €2,000 per annum comprising around 4,000 queries regarding protein matching. For Transinsight this represents a potential increase in profits of around 3% per annum.