I work within a team of experts in data life-cycle management who acquire and curate data for use in exploratory research, clinical development and evidence generation. My main responsibilities include:- Developing risk management strategies and proactively manage timelines to ensure successful oversight and delivery of studies, projects and coding responsibilities, including the implementation and adoption of new technologies. - Engaging with stakeholders across the business to understand their needs and influence their understanding of decisions made in our function. Inform stakeholders of status of key deliverables and act on changing milestones. - Partnering with relevant functions for external data vendor selection and management. Oversee development of data transfer agreements with vendors ensuring use of standards, fit-for-purpose data models and transfer intervals. - Acting as expert for data collection, advising teams and stakeholders on best practices and proposing innovative solutions. Ensuring a high quality of data and compliance with applicable pharma industry regulations and standards. - Using data surveillance tools and strategies to provide aggregate level reviews designed to identify patterns or anomalies in our data to ensure high quality results. - Organizing and integrating data collected from various sources. Maintain value of data through application of FAIR (Findable, Accessible, Interoperable, Reusable) principles.

As a clinical data manager specialized on nonCRF data, I’m involved in clinical trials across different therapeutic areas. My main responsibilities consist of:• Defining the strategies for the acquisition of nonCRF data (i.e. IxRS, Biomarker, Laboratory, Pharmacokinetics, etc.) during a clinical trial at a study specific level. • Liaising with external vendors and internal stakeholders to understand the needs of the study and ensuring acquisition of the required data in a GCP compliant fashion according to the team’s timelines. • Liaising with internal standard office to ensure data collection is compatible with and according to CDISC SDTM format.• Development and implementation of conformance checks to ensure nonCRF data quality.• Supporting the study data manager on data reconciliation processes ahead of study closeout phase.• Liaising with Clinical Research Associates (CRA’s) to ensure eCRF data reliability for data cleaning purposes.• Defining and reviewing eCRF study specific checks on Spotfire together with study data manager.

I carried out this internship at the Telomere Biology team of the IBPC. Under the supervision of Aurélia Barascu, PhD., I worked on oxidative stress and senescence in the model organism Saccharomyces cerevisiae.– Cell Biology– Signaling Pathways– PCR– Western Blot– Flow Cytometry