Job Description

Working fully embedded within one of our pharmaceutical clients, with the support of Cytel right behind you, you'll be at the heart of our client's innovation. As a Senior Statistical Programmer you will be dedicated to one of our global pharmaceutical clients; a company that is driving the next generation of patient treatment, where individuals are empowered to work with autonomy and ownership. This is an exciting time to be a part of this new program.

Position Overview

The position is responsible to support the PM leader or CPP leader who is the modeling lead in development and execution PK/PD Modeling and Simulation activities related to the research, design, implementation, data analysis, interpretation, reporting, and publication of CPP sponsored and -supported studies for products in any phase of development. The supports are mainly focused on data related and e-submission related aspects.

Our Values

• We believe in applying scientific rigor to reveal the full promise inherent in data.
• We nurture intellectual curiosity and encourage everyone to approach new challenges with enthusiasm and the desire for discovery.
• We believe in collaboration and invite a diversity of perspectives, drawing on a variety of talents to create a wealth of possibilities.
• We prize innovation and seek intelligent solutions using leading-edge technology.

Responsibilities

How you will contribute:

• Prepare programming scripts (e.g. R, SAS) to generate NONMEM analysis input dataset(s) for PK and/or PD analysis, based on requests from PM leader or CPP leader who is the modeling lead. During dataset generation, PM support also modifies the variable definition file (PM leader or CPP leader is the main author of this document) which clearly defines each variable within this dataset with any additional information as she/he sees fit. The NONMEM input dataset(s) to be created could be for interim or final analysis. The source used could be interim (uncleaned) or final SDTM/ADAM datasets or in sources in other formats, in some cases extensive data cleaning and complex calculation are needed.
• Upon request, QC NONMEM input dataset(s) generated by another PM support. Log which QC script is used, which subjects were checked per study, what other aspects were checked within the dataset, the findings of the QC and the follow-up actions of those findings in a QC document.
• Generate e-submission package for NONMEM analysis. In general, the package includes NONMEM input datasets, NONMEM control file, output parameter files, output table files and other files, in addition to supporting documents such as define and var-names-descr files. PM support renames the files provided by PM leader or CPP leader so they fit the naming convention requirements for e-submission package if needed, converts these files into the appropriate formats, and places them into the right folder structure then links them to the define and var-names-descr files. PM support works closely with EPOD team to ensure the e-submission package has the right structure, correct formats and being placed in the right assembly server directory.
• Provide guidance to new or junior members of the CPP community for the DataFlow process. The steps in the DataFlow process include but are not limited to: Kickoff meetings to outline the scope of work (e.g. PK and/or PD), timelines (e.g. before or after database lock) and support needed from other departments (e.g. Data Management (DM), programming, Bioanalysis (BAN)/ Biologics Development Science ( BDS) etc); initiation, reviewing and signing off of tsDTA; setting up secured exchange medium; monitoring timeline during dataset preparation stage (e.g. if source datasets are delivered on time); answering questions from PK office vendor during dataset preparation stage; monitoring delivery (e.g. if datasets are delivered on time); reviewing received datasets and sending feedback/requests back for modification due to programming mistakes if needed.
• Provide guidance to new or junior members of the CPP community for the Data Collection Tools review process. Data collection tools include eCRF, diary (if applicable), lab requisition form (if applicable) and completion guidelines etc.
• Interact with other departments (including but not limited to Data Management, Programming, BAN/BDS, EPOD) and external Vendors (including but not limited to PK office vendors) to communicate the needs of CPP in data collection, data formatting and data representation group discussion and cross departmental trainings if needed. Promote better understanding across different departments.
• Revise, update and create (if needed) SOPs, Job aids, templates, training materials for CPP internal processes and other cross departmental processes as needs arise.
• Improve CPP internal processes in dataset creation, dataset QC (e.g. a standard QC R script with a checklist) and e-submission package preparation (e.g. R script which can automate the linking of documents).
• Support the needs of CPP community in Secure exchange medium set up.