Current in vivo and in vitro models can't keep up with the demand for the safety assessment of large numbers of compounds emerging from high-throughput strategies. Pharmaceutical companies and start-ups are therefore building new systems that they hope will be capable of predicting the toxicity liabilities of new compounds. Cheminformatics can help week out toxic compounds at the lead selection and optimization stage; toxicogenomics may provide a toxicity diagnostic capability at all stages of drug development. For both toxicology approaches, there is not yet enough high quality data to build predictive models. Toxicology-focused cheminformatics programs attempt to consolidate data from hitherto untapped sources; toxicogenomics companies are engaged in the fussy and expensive process of manufacturing data from scratch and validating them with biological experiments.

Thanks to high throughput screening, more than 10,000 compounds with biological activity against specific targets are entering the drug discovery process each week. But unless those compounds can pass the hurdles of bioavailability and safety, comprising a series of tests known as ADMET (for absorption, metabolism, distribution, elimination and toxicity), they will never be successful drugs. Today, the tests that make up ADMET evaluation are low throughput, and are apparently not informative or accurate enough to predict a drug's probability of success, given the high failure rate of compounds at all stages of development. Drug discovery companies are therefore looking to re-engineer the ADMET process, moving it up the early discovery chain. The goal is to predict, very early in the process, perhaps even before compounds are synthesized, which compounds pass the test for a good drug. Doing so will require new assays, new computer models, and large volumes of consistent, high quality data on drugs in man, across diverse sets of chemistries. No one company has it all; partnerships and consortiums aim to bring together the necessary resources to integrate absorption, metabolism, and toxicity into a single platform.

Scimagix is developing an information informatics system that can store, transmit and manipulate small images at high speeds and high resolutions, making it appropriate for research, as well as clinical applications.

The focus of Astex Technology Ltd., which aims to imrpove the efficiency of protein X-ray crystallography, reflects the drug development background of its founders. X-ray crystallography can be used as a target validation tool, and also in drug discovery, to optimize ligand-protein interactions. Astex will first aim to introduce tools for the latter market.