Principal Scientist, Pharmacometrics Support in High Wycombe

Location: High Wycombe, United Kingdom

Responsibilities:

• Preparing R programming scripts to generate non-linear mixed effect modelling (NONMEM) analysis input dataset(s) for PK, PK/PD or Exposure-Response analysis, based on requests from PM leader or modelling leader.
• Modifying the variable definition file during dataset generation, which clearly defines each variable within this dataset with any additional information as needed.
• Creating NONMEM input dataset(s) for interim or final analysis, using various sources that may require extensive data cleaning and complex calculations.
• Generating analysis dataset Non-Compartmental Analysis (ADNCA) input datasets and associated Data Transfer Agreements and metadata.
• Quality checking (QC) NONMEM or ADNCA input dataset(s) generated by another PM support colleague, logging the QC process and findings in a QC document.
• Generating e-submission package for NONMEM analysis, including necessary files and supporting documents.
• Working closely with the EPOD team to ensure the e-submission package has the right structure and formats.
• Interacting with other departments and external vendors to communicate the needs of CPP in data collection, formatting, representation, and training.
• Promoting better understanding across different departments.
• Piloting the generation of the first draft AI-Authored data specification.
• Performing pharmacometric analysis QC activities in support of the PM Leader.
• Driving internal process improvements in dataset creation, QC procedures, and e-submission package preparation.
• Overseeing internal R package updates and maintenance.
• Creating required training decks for internal use.
• Actively participating in working groups related to AI-assisted code generation.
• Presenting cross-departmental process improvements within/outside the department.
• Carrying out functional responsibilities in accordance with applicable SOPs and regulatory requirements.

Qualifications / Requirements:

• A minimum of a Bachelor’s degree in Pharmaceutical Sciences, Clinical Pharmacology, Chemical/Biomedical Engineering or a related field with 8+ years of pharmaceutical development experience; or a Master’s degree with 6+ years; or a PhD with 4+ years of experience is required.
• Expertise with R programming language and R function creation is required.
• A fundamental understanding of clinical drug development and PK & PK/PD population PK modelling concepts is required.
• Good understanding of regulatory requirements and eCTD is required.
• Good understanding of AI-driven approaches within data programming is required.
• Data-handling skills and solid understanding of clinical database structures such as SDTM and ADAM is required.
• Excellent written and oral communication skills with strong attention to detail are required.
• Ability to build and improve working relationships inside and outside the department is required.
• Ability to collaborate in a diverse global environment is required.
• Self-motivation with the ability to work independently with minimal direction is required.

Preferred:

• R Shiny programming experience is preferred.
• Prior knowledge with ADNCA and ADPPK dataset standards is preferred.
• Knowledge of principles of non-linear mixed effect modelling is preferred.
• Prior experience with pharmacometric analysis QC would be an asset.
• Experience within oncology and immunology is an asset.