Prof Bissan Al-Lazikani speaks to ecancer in an online interview for the virtual ENA 2020 meeting about her work on big data, machine learning and drug discovery in oncology.
Prof Al-Lazikani talks about her work figuring out how to use vast amounts of interdisciplinary data to inform drug discovery and development decisions. She explains that the aim is to minimise risks and avoid misinvestment in targets or projects that may be dead ends.
She highlights the canSAR database, an integrated knowledge base that brings together experimental and clinical measurements from across different fields relevant to drug discovery. She then mentions some examples of how these techniques have been applied.
Prof Al-Lazikani goes on to discuss why it is important to have interdisciplinary data, how this work avoids having a disconnect with real-world data or practice, and how she can see this field developing in the foreseeable future.