Principal Scientist II/Senior Principal Scientist, PK Sciences Clinical Pharmacology Artificial Intelligence (AI) Lead (dual level posting)
Novartis
August 29, 2026
Remote friendly (Cambridge, MA)
United States
Clinical Research and Development
Key responsibilities:
- Lead development and use of AI-enabled strategies to transform clinical pharmacology support for new medicines.
- Identify, develop, and implement high-value AI use cases to improve clinical pharmacology planning, analyses, and decision quality.
- Represent PK Sciences in project teams; collaborate with stakeholders and regulatory agencies as appropriate.
- Provide expert pharmacokinetic (PK)/drug metabolism and clinical pharmacology input across the Research–Development–Commercial continuum.
- Use AI to accelerate understanding of nonclinical/clinical PK/PD relationships, and support development dosing strategy and prediction.
- Champion AI to accelerate delivery of dosage/PK/PD components for study protocols, reports, summaries, development plans; author regulatory sections (IND/IMPD, NDA/BLA) and responses to Health Authority questions.
- Drive interdisciplinary collaboration across PK Science, Drug Disposition (ADME/BA), and Modeling & Simulation (M&S) via PK science sub-teams.
- Work with clinicians to integrate PKS insights into study design, data interpretation, and decisions.
- Model AI/ML approaches for model-guided molecular design, automation of preclinical/clinical data, and regulatory document authoring.
Essential requirements:
- Ph.D./Pharm.D. with experience in clinical pharmacology, drug metabolism, and pharmacokinetics (or related).
- 0–2 years in drug discovery/development (academia, CRO, biotech, or Pharma).
- 2+ years (lead) in ADME/DMPK strategy or AI strategy for Principal Scientist II; 4+ years for Senior Principal Scientist.
- Deep PK knowledge (drug metabolism, PK/PD evaluation), global project-team experience, and awareness of drug development/regulatory science.
- Cross-functional, matrixed environment experience; strong oral and written communication.
Desirable requirements:
- Hands-on AI project experience with examples applying AI to clinical pharmacology topics.
- Lead development and use of AI-enabled strategies to transform clinical pharmacology support for new medicines.
- Identify, develop, and implement high-value AI use cases to improve clinical pharmacology planning, analyses, and decision quality.
- Represent PK Sciences in project teams; collaborate with stakeholders and regulatory agencies as appropriate.
- Provide expert pharmacokinetic (PK)/drug metabolism and clinical pharmacology input across the Research–Development–Commercial continuum.
- Use AI to accelerate understanding of nonclinical/clinical PK/PD relationships, and support development dosing strategy and prediction.
- Champion AI to accelerate delivery of dosage/PK/PD components for study protocols, reports, summaries, development plans; author regulatory sections (IND/IMPD, NDA/BLA) and responses to Health Authority questions.
- Drive interdisciplinary collaboration across PK Science, Drug Disposition (ADME/BA), and Modeling & Simulation (M&S) via PK science sub-teams.
- Work with clinicians to integrate PKS insights into study design, data interpretation, and decisions.
- Model AI/ML approaches for model-guided molecular design, automation of preclinical/clinical data, and regulatory document authoring.
Essential requirements:
- Ph.D./Pharm.D. with experience in clinical pharmacology, drug metabolism, and pharmacokinetics (or related).
- 0–2 years in drug discovery/development (academia, CRO, biotech, or Pharma).
- 2+ years (lead) in ADME/DMPK strategy or AI strategy for Principal Scientist II; 4+ years for Senior Principal Scientist.
- Deep PK knowledge (drug metabolism, PK/PD evaluation), global project-team experience, and awareness of drug development/regulatory science.
- Cross-functional, matrixed environment experience; strong oral and written communication.
Desirable requirements:
- Hands-on AI project experience with examples applying AI to clinical pharmacology topics.