Summer Studentship Project ‐ Development of an in silico database to predict the safety of new medicines for respiratory disease in humans

Whilst lung diseases such as asthma and COPD are increasing globally, few new inhaled medicines have reached the market in the past thirty years to treat these conditions. One of the main factors for the lack of new inhaled therapies is the poor understanding of how these medicines interact with the immune system in the airways. Regulatory bodies are unable to approve new medicines that appear to sensitise the immune system in animal models, despite not knowing fully if these observations are adverse in human patients. Current preclinical inhalation studies rely on the rat model for assessing the safety and efficacy of new inhaled medicines. However, it is widely recognised that the rat does not provide a good predictive model of inhaled toxicity in humans mainly due to the smaller size of their airways and that they predominantly breath through their nose.

We have developed several human cell-based assays which are able to accurately quantify responses to different compounds in the airways. This has generated a large bank of information which will enable the prediction of toxicity without the need for animal experiments. The aim of this project is to use this existing data to develop a database to make the information accessible and useable. This will allow information which is most predictive of lung toxicity to be developed into a decision tree. The decision tree tool will ultimately provide a more predictive non-animal based assessment of the safety of new inhaled medicines to the lung, replacing the need for using animals to test the safety of inhaled drug molecules in early pre-clinical studies and allowing more inhaled medicines to reach the market.