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Monica Simeoni, PhD

Director
Clinical Pharmacology Modelling and Simulation, Precision Medicine, GSK, United Kingdom

Monica Simeoni is a director in the Clinical Pharmacology Modeling and Simulation department and the Model-Based-Meta-Analysis lead for Respiratory and Immunology therapeutic areas at GSK which she joined in 2006.
After obtaining a Ph.D. in Biomedical Engineering from the Polytechnic of Milan, Italy, she has been an employee of the Department of Computer Science and Systems Engineering, University of Pavia, Italy, assigned to collaborative projects with pharma industry.
She has more than 20 years of experience in the pharmaceutical field. Her therapeutic areas of expertise are immuno-inflammation, neurosciences, oncology and glucose-insulin metabolism. She has experience in non-linear mixed-effect population modelling applied to the pharmacokinetics and pharmacodynamics at clinical and preclinical level, including efficacy and toxicity evaluation and target mediated drug disposition modelling. Further areas of interest are disease progression modeling, joint modelling, estimation methods, covariate analysis, model based meta-analysis.
She is an active memeber of various international scientific organizations:
• She is a member of the Scientific Organizing Committee of the Population Approach Group in Europe (PAGE) conference since 2022.
• She is currently the pharmacometrics (PMx) co-chair elect in the Stats and Pharmacometrics (SxP) SIG.
o She is also member of the MBMA Special Interest sub-Group (subSIG) which she joined in September 2021 and of which she has been the co-chair from August 2022 till April 2024.
o Additionally, she recently joined the AI/ML subSIG in November 2023.
SxP SIG together with its MBMA and AI/ML subSIGs are sponsored by the American Statistical Association (ASA) and International Society of Pharmacometrics (ISoP).

Disclosure(s): GSK: Employment (Ongoing), Ownership Interest (stocks, stock options, patent or other intellectual property or other ownership interest excluding diversified mutual funds) (Ongoing)

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