Quantitative Systems Pharmacology; QSP Lead – Rare Disease Portfolio

The Quantitative Systems Pharmacology (QSP) Lead is responsible for establishing and operationalizing QSP to support development decisions in rare disease programs. This role serves as the scientific and strategic owner of QSP across high-priority programs, with responsibility for both building an end-to-end QSP operating model and delivering modeling outputs that inform clinical and development strategy.

The incumbent will design and implement the full QSP workflow—from intake and prioritization through model development, technical review, and integration into development decisions—while ensuring outputs are reproducible, reviewable, and aligned with program needs. The role requires a balance of hands-on modeling and scientific oversight, including the effective use and management of external modeling partners, while retaining full ownership of modeling strategy and outputs.

This position operates in a highly matrixed environment and partners closely with cross-functional stakeholders to translate quantitative insights into actionable development decisions. The role is focused on high-impact rare disease programs, particularly those requiring integration across biomarkers, disease progression, and regulatory considerations, and is expected to define a roadmap for scaling QSP capabilities over time.

Duties and Responsibilities:

• Design and implement an end-to-end QSP operating model, including standardized deliverables, timelines, quality gates, documentation, and decision packages that ensure modeling outputs are reproducible, reviewable, and actionable in governance forums.
• Identify and prioritize high-impact QSP use cases aligned with key program decision points, translating modeling needs into focused work plans that maximize development impact.
• Develop and apply mechanistic or semi‑mechanistic disease and drug models (e.g., ODE‑based frameworks), ensuring strong documentation, version control, and reproducibility.
• Develop and apply mechanistic and semi-mechanistic QSP models, including virtual patient simulations and in silico trials, to inform dose selection, trial design, and risk assessment, ensuring strong documentation, reproducibility, and scientific rigor.
• Generate QSP models, virtual patients, and in‑silico trial simulations where appropriate and high‑value, particularly in early capability build‑out or critical decision moments. Balance hands‑on modeling with strategic oversight, determining when to execute internally versus leverage external partners based on impact, timing, and complexity.
• Identify, evaluate, and manage external QSP or disease‑modeling vendors, including scope definition, deliverables, timelines, and quality oversight.
• Retain full scientific and technical ownership of all externally generated outputs, ensuring alignment with internal assumptions, standards, and decision needs.
• Use virtual patient approaches and in‑silico trials to derisk development, explore dose and regimen options, and assess disease heterogeneity and scenario sensitivity.
• Produce clear, decision‑grade analysis packages explaining assumptions, limitations, sensitivity analyses, and implications for development and trial design.
• Develop and deliver clear, decision-focused modeling outputs, including assumptions, limitations, and sensitivity analyses, and translate complex quantitative insights into actionable recommendations for cross-functional teams, senior leadership, and governance bodies.
• Drive alignment on priorities, expectations, and delivery timelines in a matrix environment.
• Partner closely with Clinical Development, Clinical Pharmacology/PMx, Biostatistics, Translational, Regulatory, and other functions to align on QSP priorities, expectations, and delivery timelines in a matrix environment.
• Define a phased roadmap for scaling QSP capabilities over time, including recommendations for future hiring and optimal use of external partners.
• Other duties as assigned.

• PhD in Biomedical Engineering, Systems Biology/Pharmacology, Applied Mathematics, Computational Biology, or a related quantitative discipline preferred.
• 12+ years of experience in pharmaceutical/biotechnology…