Dr. Mike Bowles, previously a founder of Com21 and IBeam Broadcasting (both of which went on to huge IPOs) and currently co-founder of Biomatica, talked about the application of Computational Biology to investigate drug toxicity effects, earlier in drug development process. It is an understatement to say that drug development is very expensive, often costing billions of dollars and years of research. The primary challenge is determination of long term drug toxicity side effects. If we can develop and deploy efficient technologies for early prediction of adverse side effects, then the costs of drug development can be noticeably reduced, said Bowles.
However, the toxicity studies often take place relatively late in the process. During first year of research, the focus is on identifying and validating target molecules from over 5000 compounds. Toxicity is not studied until much later in the development process. Liver damage is one of the worst potential side effects of drugs, taken alone or with other medicines. “We need a paradigm shift”, said Bowles, to include toxicity studies earlier in the development process. But animal studies are also time consuming and they leave many uncertainties about human risk potential. Often by the time the animal data is in, too much is invested and it is costly to cancel the compounds. So there is an incentive to go on, rather than to eliminate compounds with riskier profiles.
Biomatica addresses this challenge by replacing liver toxicology studies on live rats with machine learned models of liver damage that can be run on rat (or human) liver cells grown in culture. They have built models using microarray data from hepatocytes to predict animal and human toxicity. Toxicity does not occur through just one pathway and it is a diffused problem. But microarray can encompass all the changes going inside a cell, at any point in time. Microarray data is collected on rat liver or rat hepatocytes grown in cultures or human hepatocytes grown in cultures and used to find earlier the compounds that should be eliminated. Testing costs earlier on live rats and on microarrays are similar. But at following stages they start adding up, in case of live rats. For instance, for 36 rats, in later stage, while they come to about $20,000 with microarry, with live rats they go as high as $113,400. The early results are indicating very good prediction accuracy, said Bowles. The talk generated a lot of interest and was followed by Q&A.