Penfield Search Partners
Contact: Linda Aronova – 646.882.9021 – firstname.lastname@example.org
Job Summary: The purpose of this job is to oversee statistical vendor deliverables, perform programmatic review of analysis datasets and Table, Listing, and Figures (TLFs) generated by vendor, ensure deliverable quality, and expedite the preparation of oncology compound regulatory submission. It will also be to maintain institutional knowledge across oncology compounds and support building up oncology programming standard on datasets and TFLs to improve efficiency and quality.
By leading internal programming contractor or by self, perform programmatic review of analysis datasets and TLFs generated by statistical vendor, ensure deliverable quality for the pivotal studies, Integrated Summary of Efficacy(ISE)/Integrated Summary of Safety (ISS) for oncology submission compounds, and expedite the preparation of regulatory submissions. Responsibilities include:
- Review Case Report Form (CRF) annotation and Study Date Tabulation Model (SDTM) dataset, identify data inconsistencies and support data review, review analysis dataset specifications and ensure correct interpretation of SAP, develop independent programs to validate analysis dataset and TLFs generated by vendor, ensure analysis dataset in compliance with CDISC and submission requirement, review submission data package and ensure its quality and integrity
Oversee statistical programming vendor on project planning and execution to ensure high quality deliverables and timelines met. Responsibilities include:
- Review and agree on vendor project timelines and resource planning, work in tandem with Biostatistics and Data Management members to ensure best vendor performance, monitor analysis dataset and TLFs transfers for ongoing and complete trials, confirm data use and output quality, proactively ensure the resolution of programming related issues prior to database lock analysis, be accountable and verify completeness of study programming deliverables, maintain all required study programming documentation required for Trial Master File (TMF)
Maintain institutional knowledge across oncology compounds and support building up oncology programming standard on datasets and TFLs to improve efficiency and quality. Responsibilities include:
- Contribute to CRF and SDTM standard development, support develop, implement, and maintain Analysis Data Model (ADaM) dataset and TLF standard, develop sample programs to generate standard ADaM dataset and TLFs, support training and ensure implementation of ADaM and TLFs standard in clinical trials analysis
Provide programming support to prepare regulatory requested analyses and help submission team in quick turnaround in response to regulatory agencies. Responsibilities include:
- Create TLFs to support submission Q&As in a quick turnaround, support ad-hoc and exploratory analysis requested by clinical team, provide programming supports in agency response or potential Advisory Committee Meeting
Develop and maintain programming macros to effectively support internal data review and monitoring. Responsibilities include:
- Work with Biostatistics member to define the requirements of efficacy data review, develop macros and support the internal data review and monitoring on an ongoing basis
Qualifications: Successful candidates will be able to meet the qualifications below with or without a reasonable accommodation.
- Bachelor’s degree from an accredited institution in a technical field such as computer science or mathematics; Master’s degree in bio/statistics preferred
- Bachelor’s degree with minimum 7 years (or Master’s degree with minimum of 5 years) proven experience within pharmaceutical industry, or CROs supporting statistical analysis of clinical trials programming
- Advanced working knowledge of all aspects of the SAS programming language used in clinical trials programming.
- Advanced working knowledge of CDISC SDTM and ADaM, and extensive experiences of their implementation in clinical trials analysis
- Advanced understanding of statistical concepts in support of analyses and reporting of clinical trials.
- Having knowledge of all phases of drug development, including early and late phase clinical development and submission
- Having solid background of applied statistics
- Solid knowledge of new advanced statistical methods using SAS and R
- Knowledge in database structures and set-up
- The candidate should have successfully provided programming expertise at the Project level for at least two global development projects that have been submitted to regulatory agencies