Senior Scientist, Advanced MIDD & Quantitative Systems Pharmacology

HYBRID NORTH CHICAGO IL PAY: $60-$65/hrREQUIRED: PhD or Master's degree with extensive experience in Quantitative Systems Pharmacology or Systems Biology model development,Proven scientific track record and practical experience in several of the following areas: Statistical modelingModeling with differential equations Model-Informed Drug Development (MIDD) Quantitative Systems Pharmacology (QSP) modelsScripting languages (R, Matlab, Python)Drug developmentCritical thinking and self-reflectivePersistent and resilientAbility to connect unrelated concept and to generate original or unique ideasFluency in English required, German would be a plusJob Description: Pharmacometrics is concerned with the mathematical and statistical analyses and modeling of biological, pharmacological, and physiological data and processes. It quantifies the various aspects of the (desired and undesired) effects of drugs in the context of disease. The models are based on clinical data, and provide a basis for informing efficient drug development, regulatory decisions, and optimal treatment of patients. Purpose:We are building comprehensive Model-Informed Drug Development (MIDD) capabilities in-house to create reusable platform models across our oncology portfolio. We seek a talented and motivated expert to develop advanced Quantitative Systems Pharmacology (QSP) models in oncology that enable Virtual Population simulations. You will act as a MIDD expert for oncology and integrate this knowledge into Clinical Pharmacology strategy for related development programs.This means:Develop QSP platform models for multiple oncology mechanisms including:Immune checkpoint inhibitors (IO/ICI) across colorectal, lung, and ovarian cancersAntibody-drug conjugates across lung, ovarian, and colorectal cancersT-cell engagers and bispecifics/trispecifics in multiple myelomaCAR-T therapies in hematologic malignanciesCreate and optimize Virtual Populations to capture patient heterogeneity and support clinical trial designImplement new methods to enhance QSP-driven MIDD, including AI/machine learning augmentation for literature screening, model drafting, and virtual population optimizationDeliver practical results that inform dose and regimen selection, optimal combinations, therapy duration, and study design for active development programs Work as part of a coordinated team under the oversight of a senior pharmacometrician within the PMx Oncology Group