Our Technology

We are currently focused on Cheminformatics and drug discovery. Our software represents chemical compounds as graphs and applies patented techniques for similar compound retrieval, diversity analysis, and substructure mining. These developments come at an opportune time for the drug development industry. While the costs of developing new drugs have been increasing, the pipelines lie bare at the pharmaceutical companies. Meanwhile, the drug discovery process has seen a paradigm shift with the advent of several high throughput technologies. The resulting growth of data has been so phenomenal that new scalable software tools have become a necessity. Drug discovery and development pipelines want improved target identification and lead optimization through predictive modeling. The success rates for finding suitable entry points for medicinal chemistry are minuscule in the early stages. The cost of working with a compound that fails late in the discovery process is high. The challenge is to use analytical tools with high precision to filter irrelevant compounds as early as possible. Acelot's graph-based compound querying and mining suite achieves this and can add efficiency to any drug development program, opening new opportunities and cutting R&D costs for pharmaceutical and biotechnology companies.

Additional applications of our technology include the synergistic integration of the systems biology and Cheminformatics applications above, social networks, and business intelligence markets where networked representation of information and extraction of semantic graph patterns are routinely required.

The basic pillars of our technology are:

• CTREE: Novel technique that addresses subgraph and similarity querying in graph databases

• GRAPHSIG: Novel technique to identify statistically significant subgraphs from a given set of graphs.

• GRAPHQL: A novel query language which uses graphs as the basic operational unit.

We present an overview of our technology in this presentation.