I am an ICR Fellow and Junior Team Leader at the Institute of Cancer Research (ICR) in London, UK. I lead the Systems Chemical Biology Team within the Division of Cancer Therapeutics that aims at developing public chemical biology resources, uncovering how drugs work at a systems level and developing computational methods to design multi-target drugs that tackle cancer drug resistance.
I studied Organic Chemistry at Ramon Llull University (Barcelona, Spain). After working two years as an in silico medicinal chemist in the pharmaceutical company Laboratorios Salvat, I moved back to academia to pursue a PhD in Pharmacoinformatics at Pompeu Fabra University (Barcelona, Spain). During my PhD, I pioneered the application of polypharmacology prediction to chemical biology by uncovering distantly-related off-targets of chemical probes. After defending my PhD, I was awarded a prestigious Marie Curie Fellowship to join the Department of Data Science at the ICR to develop the first objective, quantitative and data-driven resource for the assessment of chemical probes, Probe Miner. Next, I secured the prestigious Sir Henry Wellcome Postdoctoral Fellowship to explore the polypharmacology of cancer drugs and their implications for precision oncology in collaboration between ICR, Columbia University, the Medicines Discovery Catapult and oncologists at the Drug Development Unit of the Royal Marsden Hospital. I have been invited to present my work at several national and international conferences and I serve as Associate Director of Cheminformatics at the non-profit Chemical Probes Portal. Having worked in industry and academia, I am interested translational research aiming to bridge applied industrial drug discovery with a much needed understanding of remaining fundamental questions in cancer chemical systems biology.
This personal webpage aims to comprehensively collect all my research and publications, from papers to presentations and science dissemination activities. I will also try to regularly comment on the science I feel more close to. Welcome!
VISION Most drugs inhibit multiple targets but polypharmacology is rarely exploited in new drug discovery projects due to the limited availability of the necessary integrated multidisciplinary data to solve a two-fold challenge: 1) identify which targets to hit and which to avoid and 2) design small molecules with the desired target profile. The current explosion of scientific data in oncology offers an unprecedented opportunity to steer polypharmacology to design multi-target drugs that overcome resistance – the biggest limitation we currently face in cancer treatment. Accordingly, it is urgent that we develop data science approaches to facilitate multi-target drug design comprehensively, consistently and at scale.