Platform Scientific Lead
Pharmetheus
Lourdes Cucurull-Sanchez (She/Her), Director, Clinical Pharmacology Modelling & Simulation (CPMS), R&D, GSK, Stevenage (UK), Chair of ISoP QSP SIG.
Dr Cucurull-Sanchez has 20+ years of experience within Pharma industry, 15+ in Quantitative Systems Pharmacology (QSP) and 8 in Machine Learning (ML) for QSAR (Quantitative Structure-Activity Relationships).
Lourdes has a passion for embedding innovative modelling methods into decision-making, in order to optimise the delivery of new medicines for patients. She enjoys strategic challenges, working across boundaries with multidisciplinary teams, and communicating science.
She is a Director of Clinical Pharmacology Modelling and Simulation at GSK, and former Senior Fellow. As part of the model-informed drug development (MIDD) paradigm, she leads the implementation of QSP modelling strategies, with focus on the Oncology Development portfolio. She is the current Chair of the QSP SIG (Special Interest Group) in ISoP (International Society of Pharmacometrics), and a founder and active board member of the UK QSP Network.
Prior to GSK, she spent 8 years at Pfizer, firstly as a ML computational chemist in the DMPK (Drug Metabolism and Pharmacokinetics) department, and later on as a QSP modeler. Before that she held a Postdoctoral Research Associate position with Unilever at the University of Cambridge (QSAR and Machine Learning, 2004) for 3 years. She obtained a PhD in Chemistry (Quantum Chemistry, 2000) at the Universitat Autonoma de Barcelona, and an MPhil in Chemistry (X-ray Crystallography, 1995) at The University of Newcastle upon Tyne.
She is a prolific scientific conference speaker and author (Google Scholar H-index = 18).
Disclosure(s): GSK: Employment (Ongoing), Ownership Interest (stocks, stock options, patent or other intellectual property or other ownership interest excluding diversified mutual funds) (Ongoing)
Monday, November 11, 2024
5:00 PM – 6:30 PM MST
Monday, November 11, 2024
6:00 PM – 6:30 PM MST
What is the future and impact of artificial intelligence and machine learning (AI/ML) in each SIGs
Wednesday, November 13, 2024
9:00 AM – 10:30 AM MST
Wednesday, November 13, 2024
10:00 AM – 10:30 AM MST