Director, Oncology Clinical Pharmacology MIDD AI/ML

Responsibilities

• Defining and executing model-based development strategies for oncology projects
• Planning, conducting and reporting exposure-response analysis, simulation-based trial design and dose selection, and population PK modelling
• Applying innovative methods such as drug-disease modeling, longitudinal exposure-response analysis, model-based meta-analysis, quantitative systems pharmacology and AI/ML informed analyses to enhance data use and trial efficiency
• Presenting strategy and defending outcome of model-based approaches to internal governance boards and regulatory agencies
• Contributing to clinical program design, trial protocols, analysis plans, study reports and regulatory submissions
• Writing or reviewing clinical pharmacology components of regulatory documents and responses
• Implementing best practices, trends, lessons learned from internal and external sources to further clinical pharmacology modelling and simulation contributions to R&D pipeline
• Promoting model-informed drug discovery and development through external collaboration, journal publication and conference presentation
• Working across matrix teams to innovate in methodologies, design efficiencies and create value

Qualifications

• A PhD in Quantitative Clinical Pharmacology and Pharmacometrics (e.g., pharmacology, engineering or statistics) or relevant Life Sciences discipline, and experience in using modelling/simulation to solve practical problems in industry or academia.
• A PharmD or Master degree in the same disciplines with an additional 4 years of relevant experience may be considered.
• 5+ years of utilizing skills in mechanistic PKPD and longitudinal disease modelling; and verifiable proficiency in pharmacometric tools
• 3+ years of experience in planning, performing, and reporting analysis of clinical data per industry and regulatory standards
• Expertise in applications of AI/ML in Clinical Pharmacology and Pharmacometric analyses with innovative methodologies and efficiency applications.