Senior Scientist - PK​/PD modeling

About Abb Vie

Abb Vie's mission is to discover and deliver innovative medicines and solutions that solve serious health issues today and address the medical challenges of tomorrow. We strive to have a remarkable impact on people’s lives across several key therapeutic areas including immunology, oncology and neuroscience - and products and services in our Allergan Aesthetics portfolio. For more information about Abb Vie, please visit us at  Follow @abbvie on Linked In, Facebook, Instagram, X and You Tube.

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 for primarily large, but also small 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.

• 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

• Bachelors (B.S.), Masters (M.S.), or Doctorate (Ph.D.) in chemical, mechanical, or biomedical engineering; applied mathematics; quantitative pharmaceutical sciences or a related field, with at 10+ years of experience and Bachelors Degree, OR 8+ years of experience and Masters Degree., or Ph.D. and no experience necessary.
• Hands‑on experience with relevant modeling software and programming languages including MATLAB/Sim Biology, R, Python, Win Non Lin /Phoenix, etc. is required
• Understanding of small or large molecule drug modalities and relevant analytical methods for measuring drug and biomarker levels in preclinical and clinical study samples is highly desired
• Passion for data analysis, solving technical problems and applying new technologies to further scientific goals and answer key scientific questions enabling informed decision‑making
• Publication record demonstrating PK/PD or systems modeling examples is highly desired
• Highly‑motivated, self‑driven and results‑oriented person with excellent communication and presentation skills, capable of both leading and being lead
• High degree of flexibility in adapting to different projects and personalities as well as excellent networking and relationship‑building skills (both internal and external) required
• Must have strong communication skills and the ability to effectively communicate with both internal and external stakeholders, and to audiences of diverse backgrounds
• Prior experience in an experimental in vitro or in vivo biology field is desired
• Interest in developing skills to support projects as a QTAS project representative in future is highly desired

• Doctorate (Ph.D.) in chemical, mechanical, or biomedical engineering; applied mathematics; quantitative pharmaceutical sciences or a related field, with 1‑3 years of pharmaceutical industry experience