Quantitative Systems Pharmacology Modeler

1 day ago


Boston, Massachusetts, United States Takeda Full time
Job Title: Quantitative Systems Pharmacology Modeler - Scientist IIJob Summary:

As a Quantitative Systems Pharmacology Modeler - Scientist II in DMPK & Modeling, you will be empowered to interface between clinical pharmacology, clinical research, nonclinical drug safety, drug discovery, drug metabolism, translational medicine and pharmacovigilance to influence drug development.

Key Responsibilities:
  • Support decision making in the preclinical development of novel therapeutic agents to treat various diseases involving aberrant activation of the immune system, including irritable bowel disease (IBD), ulcerative colitis, liver fibrosis, dermatitis, and others.
  • Work on cross-functional teams with preclinical biology/pharmacology, clinical pharmacology, nonclinical safety assessment, and translational medicine to develop quantitative model-based understanding of both the target biological pathways and novel therapeutic agents.
  • May involve early feasibility assessment for novel targets, reverse translation from clinical comparators for validates ones, and/or building pharmacokinetic/pharmacodynamic (PK/PD), physiologically based pharmacokinetic (PBPK), and quantitative systems pharmacology (QSP) models for distribution, pharmacology, and efficacy of novel agents.
  • Implement a modeling & simulation strategy to assist and accelerate decisions around preclinical study design and interpretation, as well as prediction of first-in-human dose and safety margins for clinical trials.
Requirements:
  • Ph.D/Pharm.D in chemical or biomedical engineering, pharmaceutical sciences, mathematics, physics, or equivalent area.
  • Strong competency in building mathematical models is required (in commonly used languages such as MATLAB, SimBiology, NONMEM, Phoenix, Python, or R).
  • At least 2 years (8 years with MS) of industry experience in mathematical modeling of biological systems.
  • Demonstrated strong analytical skills to evaluate complex information and identify key scientific questions related to projects.
  • Ability to communicate complex modeling results clearly and concisely to cross-functional audience is critical.


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