Postdoctoral Fellow, Epidemiology & Oncology RWE

Therapeutic Area Description

The appropriate use of Real-World Data (RWD) across the full cycle of drug development is critical in the pharmaceutical industry. The FDA defines RWD as "data relating to patient health status and/or the delivery of healthcare routinely collected from a variety of sources." RWD is most often used by pharma for post-approval evaluation of treatment uptake and efficacy in clinical practice versus the randomized clinical trial (RCT) setting.

Pharma R&D is also increasingly using RWD in the pre-market setting to inform clinical development programs and support regulatory submissions. At AstraZeneca, the late oncology and real-world evidence (RWE) team within the broader AZ Oncology Data Science organization ensures all Phase 2/3 clinical trials, from investment decisions through regulatory filing and commercialization, are informed with robust RWD/E. Originally collected from various sources such as electronic health records and medical claims for non-research purposes, RWD has limitations versus RCTs. Therefore, careful study design and advanced methods are critical to control numerous sources of bias that arise with non-randomized study designs. In the setting of oncology drug development, databases of NGS-tested patients introduce additional sources of rich molecular data coupled with clinical data, but these data sources present additional methodological challenges.

While our day-to-day work generates RWE for internal decision-making on clinical trial study design and interpretation (e.g., control arm selection, expected control arm performance, study population definitions, trial interim analyses), our work is increasingly expected to impact regulatory submissions, providing supportive and eventually pivotal evidence.

Role Summary

Do you have expertise in, and a passion for, the development and application of advanced epidemiology methods to ensure rigorous insights for patients? Would you like to apply your expertise to impact early and late oncology clinical development in an organization that follows the science and turns ideas into life-changing medicines?

Purpose of this Position

To realize AstraZeneca oncology’s long-term strategic goals to demonstrate Real World Data, we seek a postdoctoral researcher to develop, adapt, and rigorously evaluate epidemiological methods for bias correction to ensure our study findings are relevant and comparable to clinical trials and ultimately fit to support FDA submissions.

What's Involved in the Role

The postdoc will design and implement several demonstration projects, testing approaches to correct or minimize the impact of various biases we encounter in our day-to-day use of claims, electronic health records, and multi-modal data. Results from these methods will be compared to AZ's status-quo analytic approaches and validated against historical clinical trials' SoC arms.

Why Should They Apply?

You will have the opportunity to formulate and address key scientific questions motivated by AstraZeneca’s oncology portfolio strategy. These questions will drive innovative research of broad interest to the pharmacoepidemiology and clinical-genomics scientific communities. You will produce high-impact publications on innovative research questions in the fields of pharmacoepidemiology and causal inference and simultaneously advance AstraZeneca’s use of RWE to accelerate and streamline drug development. Furthermore, you will have access to extensive sources of RWD and clinical trial data, and the support of teams with in-depth knowledge of data sources, clinical expertise, and mentorship from internal and external methods experts.

Collaborations

You’ll join a highly motivated, fast-paced team of epidemiologists and data scientists committed to rigorous research, bringing novel RWD insights to AstraZeneca’s Oncology pipeline. Your experience will be enriched through collaboration with a diverse internal community, including statistical innovation, applied data science, artificial intelligence, clinical teams, and the broader community of AstraZeneca postdocs. In addition to the team at AstraZeneca, you will have the opportunity to be mentored by two academic advisors, Dr. Issa Dahabreh from the T.H. Chan Harvard School of Public Health, and Dr. Camille Maringe at the London School of Hygiene and Tropical Medicine.

Essential Skills, Experience & Behaviors

Solid understanding of epidemiological study design. Experience or knowledge of working with Real World Data such as claims, electronic health records, or experience with analyzing clinical trial data. Significant experience with bias and methods to correct bias, such as propensity score weighting/matching, instrumental variable analysis, matching adjusted indirect comparisons, etc. Familiarity with approaches for generalizability and transportability. Experience coding in R (or similar).

Essential Qualifications / Education

PhD in fields such as Epidemiology, Pharmacoepidemiology, Biostatistics, Statistical Genetics, Clinical Informatics, Computer Science, Health Informatics.

Desirable Skills, Experience & Behaviors

• Oncology
• Understanding of drug development
• Understanding of causal inference, Bayesian methods, and/or quantitative bias analysis
• Prior experience in pharma, clinical trials, or engagement with regulators

Personal Characteristics & Behaviors

• Collaborative, innovative, curious, goes above and beyond for patients.

Stages of Interview

• Applicants are reviewed for fit/skills and invited to each step.
• You may not be invited to each step.

1. One-way video interview

2. Virtual interview panel with presentation

We anticipate a high volume of applicants, so do not delay, apply today!

Compensation for this role, depending on years of research experience, is a minimum of $96,000 up to a maximum of $104,000 + short-term incentive. Some relocation supplements depend on distance and location at the employer's discretion.

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AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorization and employment eligibility verification requirements.