Bristol Myers Squibb Quantitative Clinical Pharmacology - Quantitative Systems Pharmacology in Princeton, New Jersey
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The scientist will join the Quantitative Clinical Pharmacology group to use Quantitative Systems Pharmacology to inform translational pharmacology and clinical development of BMS compounds in Oncology and Immuno-Oncology.
Position Description and Responsibilities:
The Quantitative Clinical Pharmacology (QCP) group within Clinical Pharmacology & Pharmacometrics (CP&P) is searching for a scientist with specific expertise in Quantitative Systems Pharmacology (QSP). The scientist will join the QCP group to develop predictive mechanistic mathematical models using the principles of Pharmacology and Systems Biology (i.e. Systems Pharmacology) to address drug-discovery and development questions in Oncology and Immuno-Oncology. The responsibilities of the scientist will include:
Providing leadership to and collaboration with multidisciplinary project teams to develop and apply Quantitative Systems Pharmacology (QSP) models to aid in target prioritization, therapeutic modality selection, chemical/biotherapeutic optimization, biomarker characterization and early clinical trial design
Working with external groups to accelerate the internal Systems Pharmacology efforts in key disease areas
Providing expert support to project teams to design, execute and interpret clinical studies
Maintaining an active relationship with colleagues in Clinical Pharmacology & Pharmacometrics at the project level as well as in the advancement of Pharmacometrics
Networking as appropriate with experts in Discovery Biology, Non-Clinical PK/PD and other groups to share learnings and enhance consistency in best practices
Network with stakeholders in Discovery Biology to identify and interpret experiments critical for model development and refinement
Learn and further the development of QSP virtual population workflows and script-based analysis packages
Keeping up to date with emerging literature and science in the systems biology/pharmacology modeling and simulation sciences Building a personal track record of publication in the area of QSP
Ph.D. in Engineering, Mathematics, Bioinformatics, Pharmacometrics, Systems Biology/Pharmacology or a related field, with 2+ years of mathematical modeling & computer simulation experience for biomedical/pharmaceutical applications (experience within the pharmaceutical industry or pharmaceutical consulting would be desirable). Candidates with M.S. degree and significantly more industry experience will also be considered
Excellent understanding of theory, principles and statistical aspects of advanced mathematical modeling and simulation. Knowledge of process control theory would be beneficial
Good understanding of the basic principles of pharmacokinetics and pharmacodynamics
Ability to learn new areas of biological sciences and build on solid foundation of quantitative skills to develop QSP models
Ability to communicate internally and externally on topics related to CP&P and QSP is required
Ability to keep up-to-date with and propose the implementation of scientific and technological developments in the area of Systems Pharmacology/Biology
Hands-on experience with modeling software like Matlab/SimBiology/Simulink, JDesigner/Systems Biology Workbench, Entelos PhysioLab Platform, DBSolve, etc. Experience with Matlab SimBiology would be particularly desirable
Experience with general programming and data analysis tools/languages such as Python, R, Matlab, Spotfire, etc., is required
Desire to interact as a modeling and simulation expert across clinical development teams with experts from different functional areas (pre-clinical and clinical)
Experience working in Oncology or Immuno-Oncology disease areas interest is desirable
Knowledge of current practices and issues in pharmaceutical R&D in disciplines such as clinical pharmacology, bioanalytical, biopharmaceutics, and toxicology would be a plus
Bristol-Myers Squibb is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.