Dr Pedro Rodriguez Cutillas

Pedro Rodriguez Cutillas


Turing Fellow

Partner Institution

Research areas


Pedro R. Cutillas is a biochemist with expertise in the development of computational methods for the analysis of complex biological data. He graduated with a PhD in 2004 from University College London. His studies used advanced proteomics methods in a project that investigated kidney physiology. He then completed postdoctoral training at the Ludwig Institute for Cancer Research (UCL branch). In 2007, He obtained a lectureship at Bart's School of Medicine (Centre for Cell Signalling). After a period in the MRC Clinical Sciences Centre (2012-2013), where he was Head of the Mass Spectrometry and Proteomics, he joined the Barts Cancer Institute at Bart's School of Medicine in 2013 as Reader in Cell Signalling and Proteomics.

Research interests

Dr Cutillas uses machine learning and other computational methods to investigate how the biochemistry of cancer cells affects their responses to treatment. He focuses on a group of drugs named kinase inhibitors, which target biochemical pathways involved in cell communication. It is now well established that essentially all tumours over-activate a group of enzymes named kinases, whose function in normal cells is to regulate metabolism, cell division and cell identity; tumour cells dysregulate this biochemical machinery leading to uncontrolled proliferation and invasion. There are over 500 different kinase genes in humans, forming an intricate network of biochemical reactions. However, the precise nature of kinase dysregulation varies among patients, making it challenging to identify the kinase inhibitor drug that may be most effective to treat a given patient.

Dr Cutillas uses advanced computational methods to interrogate large scale proteomic and biochemical data obtained from tumour biopsies. By associating different markers of kinase network circuitry with the phenotype of cancer cells, Dr Cutillas is providing insights into the fundamental properties of cancer biochemistry and he is also is developing predictive algorithms for personalised cancer medicine.