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Using In silico Pharmacokinetics Prediction to Guide Compound Selection

The pharmaceutical industry is under considerable pressure to reduce R&D costs and improve efficiency. Virtual screening approaches are now common for predicting efficacy and are critical for reducing the vast number of possible molecules in a library to a more manageable number for further synthesis and screening against biological targets. However, to reach the market, it is now well recognised that drugs not only need good activity but this must be balanced with favourable pharmacokinetics and a low risk in terms of toxicity. Therefore, virtual screening must encompass and integrate all of these areas in order to lead to the best chance of success.

chemPK™ is an in silico tool built on the open source KNIME Analytics Platform that uses robust PBPK modelling techniques to predict human oral and IV pharmacokinetics directly from chemical structure.

The chemPK™ workflow process is illustrated below.

in silico pharmacokinetic prediction

Our research on virtual PK prediction was presented at the recent EFMC meeting in Manchester where we demonstrated the model development procedure and the validation statistics for chemPKTM. These data illustrate chemPKTM to be a valuable tool for early prediction of pharmacokinetics. By combining chemPKTM with other virtual screening approaches, it will ensure that only molecules with the optimal chance of success are synthesised thus reducing the cost and increasing the speed of drug discovery process.

This research was presented at the EFMC International Symposium on Medicinal Chemistry. Download the poster.