Director, PK Sciences Clinical Pharmacology Artificial Intelligence (AI) Lead

Novartis•Cambridge, MA

1d•$185,500 - $344,500•Onsite

About The Position

Novartis is seeking an enthusiastic and motivated PK Sciences representative to lead the development and use of AI-enabled strategies that transform clinical pharmacology support for new medicines. The role focuses on developing AI-based solutions to automate, innovate, and accelerate PK Sciences and clinical pharmacology deliverables, while providing strategic, scientific, and operational leadership. The scope may span small molecules, biologics and therapeutic proteins, antibody drug-conjugates, radioligand therapies, and/or cell therapies across major therapeutic areas. Late discovery through clinical development experience is preferred. The role fosters close interdisciplinary collaboration among PK Sciences, Drug Disposition (ADME, BA), Modeling & Simulation, and Operations, and works with broader cross-disciplinary project teams to integrate PK Sciences strategies into project plans and scientific discussions. The position is based in Cambridge, Massachusetts, and cannot be located remotely. It reports to a Therapeutic Area Unit head within PK Sciences in Translational Medicine, Biomedical Research. PK Sciences is a global, enterprise-wide organization within Translational Medicine, the clinical research arm of Biomedical Research. It works across Biomedical Research and Development to advance pharmacokinetics, metabolism, and clinical pharmacology, bridging drug discovery and clinical application.

Requirements

Ph.D. or Pharm.D. with relevant experience in clinical pharmacology, drug metabolism and pharmacokinetics, or a related background.
At least 8–10 years of experience in drug discovery and/or development in a relevant environment, such as academia, a CRO, biotech, or Pharma.
Six or more years of experience, preferably in a lead role overseeing ADME/DMPK project strategy in translational/clinical development or in AI strategy.
Extensive and in-depth knowledge of pharmacokinetics, including drug metabolism and PK/PD evaluation.
Experience working in project teams, preferably global teams.
Sound awareness of recent developments in drug development and regulatory sciences.
Experience in a cross-functional, matrixed, project-team environment.
Strong oral and written communication skills.

Nice To Haves

Experience in late discovery through clinical development.
Hands-on project experience with AI approaches and examples of applying AI to clinical pharmacology topics.

Responsibilities

Lead development and oversee implementation of the AI strategy for clinical pharmacology within PK Sciences.
Use enterprise AI and digital tools to support strategic, scientific, and operational leadership in clinical pharmacology.
Identify, develop, and implement high-value AI use cases to improve clinical pharmacology planning, analyses, and decision quality.
Represent PK Sciences in project teams, stakeholder interactions within the organization, and interactions with regulatory agencies as appropriate.
Provide expert pharmacokinetic, drug metabolism, and clinical pharmacology input to drug candidates across the Research, Development, and Commercial continuum.
Work with teams to use AI to improve understanding of nonclinical and clinical PK/PD relationships and development dosing strategies and predictions.
Use AI to accelerate and enhance dosage and PK/PD components of study protocols, reports, project summaries, and development plans.
Author pharmacokinetic, clinical pharmacology, and biopharmaceutics sections of INDs/IMPDs and NDAs/BLAs, and prepare appropriate responses to Health Authority questions.
Drive interdisciplinary collaboration among PK Sciences disciplines, Drug Disposition (ADME, BA), and Modeling & Simulation through PK science sub-teams.
Collaborate with clinicians and clinical development colleagues to integrate PK Sciences insights into study design, data interpretation, and project decision-making.
Model the use of AI/ML approaches for model-guided molecular design, preclinical and clinical data automation, and authoring regulatory documents.