Postdoctoral fellowship Translational disease modeling,

Job description

Mission
The candidate work will be dedicated in the field of joint modeling composite endpoints in oncology in clinical trials and real world setting.

More specifically, in the context of Multiple Myeloma (MM) clinical trials, a joint modeling approach for multiple composite endpoints, including IMWG response criteria's, progression-free and overall survival & HRQoL will be first implemented. This model will be used to quantify the importance of patient-related, disease-related, and treatment-related factors in MM to better predict relevant clinical trial outcomes.
Then a Bayesian joint model will be built to fit composite endpoints (response and survival outcome) collected in a real-world database in Relapse Refractory MM patients who have comparable characteristics to those included in phase 3 clinical trials.
Finally, clinical trial simulation will be performed to predict treatment benefit in overall survival in real-world patients with different subgroups of patient at risk and to compare with the competitors or standard of care therapies.
The candidate will present his work internally and externally (poster or publication) in congress

Skills Required
• Modeling, pharmacometrics, and computational experience
• Solid understanding of PK and quantitative pharmacology principles;
• Knowledge of biological pathways relevant to disease and application to model development in oncology

Expected Qualification / Experience
• PhD with a track record of productivity in the areas of pharmacometrics, disease progression modeling, computational biology, or related field, as demonstrated by publications and presentations;
• Modeling and computational experience, with good hands-on scientific computing and programming skills in a variety of computational tools such as MATLAB, Monolix, NONMEM, R, PFIM, STAN
• Strong knowledge of related disciplines (e.g., biostatistics, toxicology, regulatory) in the drug development process.

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