South San Francisco, CA, 94080, USA
13 hours ago
2025 Human Pharmacokinetics (PK) and Drug-Drug Interaction (DDI) Prediction Intern
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 Twitter, Facebook, Instagram, YouTube and LinkedIn. Job Description Human PK and DD Prediction Intern Overview Envision spending your summer working with energetic colleagues and inspirational leaders, all while gaining world-class experience in one of the most dynamic organizations in the pharmaceutical industry. This is a reality for AbbVie Interns. The intern will support the Translational Pharmacokinetics and Drug-Drug Interaction (DDI) Sciences group within the Quantitative, Translational & ADME Sciences (QTAS) department at AbbVie. This group’s main function is to utilize in vitro and in vivo preclinical data to predict human pharmacokinetics (PK) and DDI parameters of investigational small molecules and provide dose/DDI projections to facilitate their successful transition into first-in-human studies. This often involves mathematical modeling and simulation (M&S) methods such as physiologically-based pharmacokinetic (PBPK) models. The intern will explore the utility of incorporating preclinical animal PBPK models in benefiting human PK predictions and may execute various other prediction methods including, but not limited to, allometric scaling and in vitro-in vivo extrapolation (IVIVE), to provide a comprehensive evaluation of predictive performance using both internal and external data. This work will contribute to the team’s strategies in employing these techniques and enabling rational decision-making to support the development of new potential drug candidates. This position will be based in South San Francisco, CA. Key responsibilities include: + Conduct a comprehensive literature review to gather and synthesize relevant information regarding human PK and DDI prediction methods + Perform mathematical predictions of human PK/DDI parameters in compounds from both external data and AbbVie's internal database + Evaluate predictive performance against clinically observed data + Analyze and interpret data and present findings to the QTAS department and other relevant stakeholders Qualifications Qualifications + Currently enrolled in university, pursuing a Master’s or PhD in Pharmaceutical Science, Pharmacology, Biology, Biochemistry, or other related field + Must be enrolled in university for at least one semester following the internship + A strong understanding of basic ADME principles, in vivo pharmacokinetics (e.g., clearance, F%), and PK modeling concepts is highly desired + Strong analytical and problem-solving skills + Excellent attention to detail and ability to work independently + Enthusiasm and willingness to learn + Proficiency with MS Office Suite Preferred Qualifications + Expected graduation date between December 2025 and June 2026 + Experience with modeling software (e.g. Phoenix WinNonlin, Simcyp, Gastroplus) Benefits and Amenities + Competitive pay + Relocation support for eligible students + Select wellness benefits and paid holiday / sick time + Break rooms stocked with complimentary coffee, tea, cold beverages, healthy snacks, and cold breakfast items + Onsite café and fitness center Equal Employment Opportunity At AbbVie, we value bringing together individuals from diverse backgrounds to develop new and innovative solutions for patients. As an equal opportunity employer we do not discriminate on the basis of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information gender identity or expression, sexual orientation, marital status, protected veteran status, or any other legally protected characteristic. Additional Information Applicable only to applicants applying to a position in any location with pay disclosure requirements under state or local law: ​ + The compensation range described below is the range of possible base pay compensation that the Company believes in good faith it will pay for this role at the time of this posting based on the job grade for this position. Individual compensation paid within this range will depend on many factors including geographic location, and we may ultimately pay more or less than the posted range. This range may be modified in the future.​ Note: No amount of pay is considered to be wages or compensation until such amount is earned, vested, and determinable. The amount and availability of any bonus, commission, incentive, benefits, or any other form of compensation and benefits that are allocable to a particular employee remains in the Company's sole and absolute discretion unless and until paid and may be modified at the Company’s sole and absolute discretion, consistent with applicable law. ​ ​ AbbVie is an equal opportunity employer and is committed to operating with integrity, driving innovation, transforming lives, serving our community and embracing diversity and inclusion. It is AbbVie’s policy to employ qualified persons of the greatest ability without discrimination against any employee or applicant for employment because of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information, gender identity or expression, sexual orientation, marital status, status as a protected veteran, or any other legally protected group status. 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
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