Only less than one in 10,000 potential drug compounds reach the clinic. As a result, drug discovery remains a complicated process. We provide phenotypic screening that evaluates the effects of potential drugs in vitro on the cultured cell lines. In addition, we efficiently analyze multiparametric data sets to predict drug response much earlier in the drug discovery process.

We apply advanced molecular techniques to identify and validate drug targets. The drug metabolism and mechanism of action studies at early stages can potentially deliver safer drugs to market.

Cell-based approaches allow a direct way to determine the mode of action of drugs at the fundamental level. In addition, we have a multispecies platform to investigate species differences to ensure better safety in clinical trials.

The iPSC-derived liver, cardiac and neurons are useful for predicting clinical pharmacokinetics and pharmacodynamics. We use samples from different ages, genders and ethnicities to represent the safety/toxicity risk in a population.

The processes are highly data-driven with high-resolution images, genomic and biological information, and molecular and metabolite profiles. Our approach for computational modelling allows data exploration to identify key features and create cognitive networks to automate toxicity prediction. It is a game-changing technology for precise drug discovery.