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Company Description
AbbVie'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 – immunology, oncology, neuroscience, and eye care – and products and services in our Allergan Aesthetics portfolio. For more information about AbbVie, please visit us at www.abbvie.com. Follow @abbvie on X, Facebook, Instagram, YouTube, LinkedIn and Tik Tok.
Job Description
The Quantitative, Translational and ADME Sciences (QTAS) organization plays a vital role in increasing the probability of success of AbbVie’s pipeline by supporting Early Discovery and continuing through all phases of clinical development. QTAS scientists mechanistically investigate how drug molecules are absorbed, distributed, excreted, metabolized, and transported across the body to predict duration and intensity of exposure and pharmacological action of drug candidates in humans. QTAS is responsible for:
Quantitative Translational Mechanistic Modeling Group
ADME Sciences
Bioanalysis
Project Support Model
Locations: Lake County IL, Worcester MA, Bay Area and Irvine CA, Ludwigshafen Germany
There are Key Roles that work together to mechanistically understand drug behavior, generate critical data, provide scientific guidance throughout the drug development lifecycle. See Below for more information regarding each pillar and criteria for each role.
Quantitative Translational Mechanistic Modeling
Translational modeling utilizes mathematical equations with parameters informed by relevant in silico, in vitro, nonclinical in vivo and clinical data to predict human pharmacokinetics (PK) and pharmacodynamics (PD) for new drugs. Human PK is projected using methods including but not limited to allometric scaling and physiologically based pharmacokinetic (PBPK) modelling. These models can be used to predict, e.g., tissue exposures, drug-drug interactions (DDI), food effect, ethnic or genetic difference in pharmacokinetics, and integrated into PK/PD models to project safe and efficacious human doses. Empirical PK/PD approaches typically relate systemic drug exposure directly to efficacy, while mechanistic models may also incorporate elements of tissue/cellular distribution, target engagement and downstream pharmacology. These translational modeling approaches are being rapidly adopted in Discovery at early stages to inform target selection, modality selection and property optimization strategies, and at later stages to project efficacious dosage regimens and rationally design first-in-human clinical trials.
Quantitative Translational Mechanistic Modelers
Develops and applies mathematical models to predict human pharmacokinetics (PK) and pharmacodynamics (PD) for new drugs.
Uses in silico, in vitro, nonclinical, and clinical data to inform model parameters.
Projects tissue exposures, drug-drug interactions, food effects, and genetic differences in PK.
Supports target selection, property optimization, and dosage regimen design for clinical trials.
ADME Sciences
ADME refers to the study of the absorption, distribution, metabolism, and excretion of drugs using cell cultures, tissue, preclinical species, or humans. The four criteria influence the drug levels and kinetics of drug exposure to tissues and hence influence the performance and pharmacological activity of the compound as a drug. ADME assays help identify drug candidates that are more likely to be successful in clinical trials and advancing drug candidates that are more efficacious, less toxic, and easier to administer.
ADME studies throughout drug discovery and development provide critical data required to determine the safety and efficacy of a potential new drug. The information provides insights on how a drug is absorbed, distributed, metabolized, excreted from the body, and pharmacokinetic behavior to drive molecules to the market. The data generated is used to influence drug design/chemistry, understand risks associated with drugs (drug-drug interactions, reactive metabolites, safety coverage, active metabolites, toxicological activity, clearance mechanism), provide data required for regulatory filing, and provide scientific advice to project teams.
ADME Scientists
Studies absorption, distribution, metabolism, and excretion of drugs using various biological systems.
Conducts assays to identify drug candidates with optimal clinical profiles.
Provides critical data for drug safety, efficacy, and regulatory filings.
Advises project teams on drug design, risks, and regulatory requirements.
Bioanalysis
Bioanalysis is the measurement or identification of analytes in biological matrices. QTAS has comprehensive analytical platform capabilities, extensive experience, significant internal capacity, and maintains well-established external partnerships to measure and characterize a wide variety of analytes, including small and large molecule drugs, drug metabolites, anti-drug antibodies, soluble biomarkers, cells, and intracellular signaling molecules from whole blood, plasma, serum, tissues, and many other sample types, from a variety of species. The methods to measure such analytes in diverse matrices are characterized/validated following fit-for-purpose principles and subsequently used for sample testing in non-regulated or regulated laboratories, as appropriate.
Bioanalytical Scientists (non-Regulated and Regulated)
Measures and identifies analytes in biological matrices using advanced analytical platforms.
Characterizes small and large molecule drugs, metabolites, biomarkers, and more from diverse sample types.
Validates methods for regulated and non-regulated laboratory testing.
Maintains internal capacity and external partnerships for comprehensive bioanalytical support.
Project Support Model
QTAS project representatives are the primary point of contact to ensure QTAS support of projects across all modalities. Typically, project support starts in Discovery lead generation and goes through the entire life cycle of a program (up to and including post-marketed products). QTAS project representatives are skilled in different aspects of QTAS science (e.g. ADME sciences, pharmacokinetics, bioanalytical, translational modeling) and work closely with other subject matter experts (SMEs) within QTAS to ensure the right studies are conducted at the right time to successfully advance/support a program. QTAS reps work cross functionally within Development Sciences and with partners across R&D to ensure projects are fully supported.
Project Support Representatives
Serves as the primary QTAS contact for project support across all modalities.
Supports projects from Discovery lead generation through post-marketed products.
Collaborates cross-functionally within Development Sciences and R&D.
Ensures the right studies are conducted at the right time to advance/support programs.
QTAS regularly hires in these four key areas. If you have interest in any of the following roles, please submit your resume/CV to stay connected.
Search “QTAS” as a keyword on our careers page: https://careers.abbvie.com/en/
Additionally, we also may have openings in our Clinical Pharmacology department. Search “clinical pharmacology”.
Qualifications
Qualifications:
Qualifications vary based level of role, but typically we look for:
- Bachelor’s degree, Master''s Degree or Ph.D in biochemistry, chemistry, pharmacology, chemical, mechanical, or biomedical engineering; applied mathematics; quantitative pharmaceutical sciences or related fields.
Additional Information
All your information will be kept confidential according to EEO guidelines.
AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives and serving our community. Equal Opportunity Employer/Veterans/Disabled.
US & Puerto Rico only - to learn more, visit https://www.abbvie.com/join-us/equal-employment-opportunity-employer.html
US & Puerto Rico applicants seeking a reasonable accommodation, click here to learn more:
https://www.abbvie.com/join-us/reasonable-accommodations.html
Salary: $35,000 - $172,500
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