Job Description
The AbbVie portfolio consists of several marketed products in areas including eye care, immunology, oncology, virology, and women’s health as well as a pipeline containing multiple promising new molecules being studied in hundreds of clinical trials or advancing from Discovery into Development.
AbbVie is a global organization with US research sites in Boston (Cambridge and Worcester, MA), Chicago (North Chicago, IL), and the San Francisco Bay Area (South San Francisco, CA).
The biotherapeutics portfolio is comprised of diverse and tailored modalities including mono- and bispecific antibodies, antibody-drug conjugates, antibody fragments, gene therapies and cell-based therapies.
The Quantitative, Translational and ADME Sciences (QTAS) group is searching for a Senior Scientist to provide mechanistic and translational modeling and project support in all disease areas, informing decision-making in both small and large molecule projects from discovery through the early stages of clinical development.
The candidate will establish innovative translational modeling approaches, such as mechanistic PK / PD or systems modeling, across disease and therapeutic areas, as well as provide QTAS project support enabling translation of assets from Discovery into early Development.
The position requires close collaboration with Discovery and Development project teams, clinical pharmacology, and other stakeholders, to develop and execute QTAS and PK / PD strategies necessary to facilitate the advancement of our pipeline.
This position offers the flexibility to be based onsite in North Chicago, South San Francisco, or Worcester, and requires a minimum of three days per week on-site.
Key Responsibilities :
Develop and implement innovative, quantitative analyses and strategies for translational modeling across Discovery and Development projects
Liaise with Discovery biology, pharmacology, toxicology, biomarker, QTAS and clinical scientists to generate data and knowledge supporting the generation and implementation of translational models
Establish and maintain effective collaborations with key peer and team stakeholders within QTAS, Discovery and Clinical to facilitate knowledge and data integration for target prioritization, biomarker selection, candidate selection, guidance in (pre)clinical study design, human dose prediction and calculation of therapeutic index
Effectively communicate on strategies related to drug metabolism and pharmacokinetics (DMPK) and translational modeling and simulation
Maintain awareness of emerging literature and science in computational approaches and applications
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