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 workflowfrom intake and prioritization through model development technical review and integration into development decisionswhile 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.

• 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 semimechanistic disease and drug models (e.g. ODEbased 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 insilico trial simulations where appropriate and highvalue particularly in early capability buildout 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 diseasemodeling 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 insilico trials to derisk development explore dose and regimen options and assess disease heterogeneity and scenario sensitivity.

• Produce clear decisiongrade 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.

Qualifications:

• PhD in Biomedical Engineering Systems Biology/Pharmacology Applied Mathematics Computational Biology or a related quantitative discipline preferred.

• 12 years of experience in pharmaceutical/biotechnology development with a minimum of 3 years of QSP modeling
• Demonstrated experience delivering QSP or mechanistic modeling to inform drug development decisions including dose selection trial design and/or regulatory strategy.
• Proven ability to operate in a matrix environment integrating quantitative insights into crossfunctional decisionmaking.
• Strong expertise in QSP modeling frameworks (e.g. MATLAB R Julia or Open Systems Pharmacology Suite) with strong emphasis on model development validation and reproducibility.
• Rare disease experience preferred.

Other Requirements:

• This position has significant managerial and decision-making authority.
• Ability and willingness to travel approximately 25-35% of the year both domestically and internationally
• Must live a commutable distance to our US Corporate Headquarters in Florham Park NJ. Office presence required at least 50% of the time per month.

Additional Information:

The base salary range for this full-time position is $260000 - $295000. Individual pay is determined by several factors which include but are not limited to: job-related skills experience and relevant education or training. The range does not include the comprehensive benefits bonus long-term incentive applicable allowances or any additional compensation that may be associated with this role.

Shionogi Inc. is an equal opportunity employer supporting individuals with disabilities and veterans. All qualified applicants will receive equal consideration for employment opportunities based on valid job requirements without regard to race color religion sex (including pregnancy) marital status national origin age ancestry citizenship disability genetic information status as a disabled veteran a recently separated veteran Active Duty Wartime or Campaign Badge Veterans and Armed Forces Service Medal Veterans or any other characteristic protected by applicable law. It is the policy of Shionogi Inc. to undertake affirmative action for protected veterans and individuals with disabilities in compliance with all federal state and local requirements to recruit a diverse pool of protected veteran and individuals with disabilities applicants and to ensure that our employment practices are in fact non-discriminatory.

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