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DISCOVERY AND EXPLORATORY STATISTICS INTERNSHIP 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’s Experiential Interns.
Discovery and Exploratory Statistics (DIVES) is part of the Data and Statistical Sciences (DSS) group within the Statistical Science and Analytics (SS&A) organization in AbbVie R&D. We provide biostatistical collaborations for various groups in Discovery, Development Sciences, and the exploratory needs in Drug Development. The DIVES group is currently seeking two Interns, one with a focus on control data borrowing and the other with a focus on missing data handling.
Control Data Borrowing
The Intern will support the development of predictive analysis pipeline for early-phase oncology trials with borrowed control. The intern will evaluate a variety of historical oncology trials as well as real-world data resources that can potentially be used for control data borrowing, in a close collaboration with our prediction medicine partners. Another component of the project includes thorough evaluation of the matching method. We expect well-matched controls can greatly improve the robustness and efficiency of predictive biomarker analysis workflows. The enhanced predictive biomarker analysis workflow with borrowed controls can further facilitate our support for the biomarker projects regarding patient selection and treatment decision for early-phase oncology trials within AbbVie.
Missing Data Handling
The Intern will support the development of a unified missing data handling strategy for both PD and predictive biomarker analysis in our internal pharmacodynamic (PD) and predictive biomarker analysis workflows. The Intern will design simulations to evaluate imputation methods to provide guidance for different scenarios under the framework of biomarker analysis workflows. The enhanced PD and predictive biomarker analysis workflow incorporating the missing data strategy can further facilitate our support for the biomarker projects with the objectives of dose selection, mechanism of action (MOA) identification, patient selection and treatment decision for oncology trials within AbbVie.
Key responsibilities could include:
Work with Precision Medicine scientists to identify potential historical trials/real world data resources and evaluate the inclusion/exclusion criteria as well as the biomarker/clinical data included in the datasets. Write a guidance document for the control data warehouse including key variables for matching and recommended analysis.
Literature and resource review of matching methods for causal inference or current missing data imputation methods
Must be enrolled in university during the internship period
Expected graduation date between August 2023 - December 2025
Exposure to biomarker analysis, statistical genetics/genomics
Course work of linear and nonlinear mixed effect models, survival analysis, causal inference, deep/machine learning preferred
BENEFITS AND AMENITIES
Travel, transportation and lodging support for eligible students
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.