Research Fellow, Translational Modeling
AbbVie (NYSE:ABBV) is a global, research-based biopharmaceutical company formed in 2013 following separation from Abbott Laboratories. The company's mission is to use its expertise, dedicated people and unique approach to innovation to develop and market advanced therapies that address some of the world's most complex and serious diseases. AbbVie employs approximately 28,000 people worldwide and markets medicines in more than 170 countries.
Oncology is a key therapeutic area for AbbVie, with a portfolio consisting of three marketed products — Imbruvica, Venclexta, and Empliciti — and a pipeline containing multiple promising new molecules that are being studied in nearly 200 clinical trials in 19 different types of cancer.
AbbVie is expanding its oncology hub on the West Coast, with three sites in the San Francisco Bay Area (Redwood City, South San Francisco, and Sunnyvale) focused on the discovery and development of novel oncology therapies. More than 1,000 AbbVie scientists, clinicians, and product developers with strong entrepreneurial roots work across these three sites. They combine their expertise in immuno-oncology, stem cells, and cell-signaling with their knowledge of bispecific antibodies, antibody-drug conjugates (ADCs), and covalent-inhibitor technologies to discover and develop novel cancer treatments.
The Drug Metabolism, Pharmacokinetics & Translational Modeling (DMPK-TM) Department is searching for a Research Fellow in Redwood City, CA to provide project and translational modeling support in Oncology, enabling biologics progression from discovery to early stages of clinical development. The Research Fellow will establish innovative translational modeling approaches, such as mechanistic PKPD modeling mechanistic physiological-based PK (PBPK) modeling, and quantitative systems pharmacology (QSP) in Oncology as well as DMPK project support in Discovery and Development enabling compound progression from discovery to early stages of clinical development.
- Develop and implement innovative and quantitative strategies for translational modeling across Oncology Discovery and Development projects
- In a matrix manner, lead and mentor junior modelers within the global DMPK-TM organization in translational modeling approaches and best practices, ensuring that translational modeling strategies and technologies are aligned with project and functional deliverables
- Liaise with discovery biology, pharmacology, toxicology, biomarker, BA and clinical scientists to generate data and knowledge supporting the generation and build-up of translational models
- Build and maintain effective collaborations with key senior stakeholders within DMPK-BA, discovery and clinical to enable 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
- Build strong external network in the field of modeling & simulation (e.g. academia, consortia) and strive for external collaboration with consortia, academic partners, CROs.
- Effectively communicate and influence, at a senior level, on strategies related to DMPK and translational modeling and simulation
- Maintain awareness of, and lead DMPK modelers to contribute to, emerging literature and science in modeling approaches and applications
QualificationLevel and compensation will be commensurate with experience.
- Bachelors, Masters, or Doctorate (Ph.D.) in PBPK modeling, Pharmaceutical sciences or related field, with at least 18+ (BS), 16+(MS), or 10+(Phd) years of pharmaceutical industry experience.
- Hands-on experience in modeling software like MatLab/Simbiology, Phoenix, WinNonlin, etc. is required
- Must have a strong understanding of DMPK, PKPD modeling and human dose prediction of oncologic agents, and able to give clear recommendations for the design of preclinical and clinical studies. Strong understanding of the implication of QSP is desirable.
- Understanding of large and small molecule oncology drug development (including ADCs) and relevant analytical methods for measuring drug and biomarkers in preclinical study samples is highly desired
- Publication record with PKPD modeling examples is required
- Must have strong communication skills and the ability to influence, negotiate and communicate with both internal and external stake holders
- Highly motivated, self-driven and results-oriented person with excellent communication and presentation skills, capable to work both as team player and project driver. High degree of flexibility in adapting to different projects, persons and excellent networking and relationship-building (both internal and external) skills are required.
- Passion for data analysis, solving technical problems and applying new technologies to further scientific goals.
- Doctorate (Ph.D.) in PKPD modeling, Pharmaceutical sciences or related field, with at least 10+ years of pharmaceutical industry experience.
- Builds strong relationships with peers and cross functionally with partners outside of team to enable higher performance.
- Learns fast, grasps the "essence" and can change course quickly where indicated.
- Raises the bar and is never satisfied with the status quo.
- Creates a learning environment, open to suggestions and experimentation for improvement.
- Embraces the ideas of others, nurtures innovation and manages innovation to reality.
Equal Opportunity Employer Minorities/Women/Veterans/Disabled