Bissan Al-LazikaniNobel Conference 56

Bissan Al-Lazikani is head of data science, computational biology and chemogenomics at the Institute of Cancer Research, London.

New cancer treatments often target specific genes or proteins within the cancerous cells. Before such a therapy can even be sought, researchers must identify genes that both regulate the cancer and are potentially responsive to a (still-only-hypothetical) drug. Researchers identify potential targets and potential drugs by studying patterns; what kinds of gene-drug combinations have worked before? Computer algorithms can do the same kind of pattern recognition, but much faster, using far more data. Machine learning enables scientists to increase the speed at which discoveries are made, while also decreasing the financial risks for companies doing the discovering. Access to data is crucial to this discovery process

Bissan Al-Lazikani has been instrumental in developing canSAR, a free, online database that combines biology, chemistry, pharmacology, structural biology, cellular networks, and clinical annotations to produce predictions that can inform drug design. Using canSAR, researchers can access information about proteins, compounds, cell lines, and structures, in order to explore the interactions among them and the roles they play in cancers. 

Professor Al-Lazikani is currently the head of data science at the Institute for Cancer Research in London, where she leads the Knowledge Hub Big Data Team. She focuses on applying big data and analytical modeling to cancer drug discovery and design. These techniques aim to better translate science into medical practice, ideally resulting in a better patient experience. Her multidisciplinary background--she holds degrees in molecular biology, computer science and computational structural biology--gives her research a comprehensive approach.