Associate Director/Director, Clinical Pharmacology and Pharmacometrics

About Us

About the Role

The Associate Director, Clinical Pharmacology & Pharmacometrics will serve as a key quantitative sciences leader supporting the company's autoimmune/inflammation and neuromuscular disease portfolios. This individual will design, execute, and interpret quantitative systems pharmacology (QSP), population pharmacokinetic (PopPK), and exposure-response (E-R) analyses to inform first-in-human (FIH) dose selection, Phase 2 dose selection/rationale, and lifecycle formulation/device bridging strategies. The role requires deep hands-on modeling expertise (MATLAB, NONMEM, R) combined with the ability to translate complex quantitative outputs into clear, decision-enabling recommendations for cross-functional teams and regulatory submissions.

This is a unique opportunity where you have a chance to positively impact lives as part of the team driven by continuous innovation with very high scientific integrity. We are building a team who hold our core principles at the center of our operations, with the goal to elevate the care of our patients’ lives.

We are building a culture of individuals who hold our core principles at the center of our operations, with the goal to elevate the care of our patients’ lives. We are open to you working remotely.

Key Responsibilities

QSP Modeling & First-in-Human Dose Selection

• Develop and apply fit-for-purpose QSP models (MATLAB and associated MATLAB modules, e.g., SimBiology) to characterize target engagement/coverage, RO, PK/PD relationships, and disease-relevant biology in autoimmunity and inflammation programs.
• Conduct competitive landscape and benchmarking analyses, integrating publicly available competitor PK/PD/clinical data into modeling frameworks to contextualize internal program positioning.
• Integrate nonclinical (in vitro/in vivo/NHP PK/PD) data with competitor-derived and mechanistic assumptions to simulate human PK/PD and support translational dose projections.
• Lead quantitative dose-selection strategy for first-in-human studies, including starting dose justification, dose-escalation scheme simulation, and safety margin assessment.
• Use R for exploratory data analysis, visualization, and model diagnostics supporting QSP deliverables.

Population PK/PD and Exposure-Response Analysis

• Build, qualify, and apply population pharmacokinetic (PopPK) models in NONMEM using data from Single Ascending Dose (SAD) and Multiple Ascending Dose (MAD) Clinic studies.
• Perform exposure-response (E-R) analyses linking PK to relevant efficacy, safety, and biomarker endpoints across autoimmune/inflamation indications including Systemic Lupus Erythematosus (SLE), rheumatoid arthritis (RA), Sjögren's syndrome, and dermatomyositis.
• Translate PopPK/E-R findings into Phase 2 dose and regimen recommendations, presenting quantitative rationale to clinical development and regulatory teams and governance committees.
• Use R for dataset assembly (e.g., NONMEM-ready datasets), post-processing, diagnostics (goodness-of-fit, VPCs), and reporting of population modeling results.
• Author and review analysis plans, statistical/pharmacometric analysis reports, and relevant sections of regulatory documents (briefing books, IND/CTA, NDA/BLA modules).

Bioequivalence / Relative Bioavailability & Formulation Bridging

• Leverage existing PopPK models to conduct bioequivalence (BE) and relative bioavailability analyses supporting introduction of new subcutaneous (SC) formulations, delivery devices, and/or injection sites.
• Support commercialization readiness for late-stage/marketed assets in autoimmune/inflammation and neuromuscular disease/indications including but not limited to generalized myasthenia gravis (gMG), Chronic Inflammatory Demyelinating Polyneuropathy (CIDP), and Multifocal Motor Neuropathy (MMN) by quantitatively bridging PK across formulation/device/site changes.
• Design model-based simulation strategies to support waiver arguments or reduced clinical burden for formulation/device bridging studies, in collaboration with CMC, regulatory, and clinical teams.

Cross-Functional & Strategic Contributions

• Partner with Clinical Development, Research, Translational Medicine, Bioanalytical, Biostatistics, Regulatory Affairs, and CMC to align quantitative strategy with program milestones.
• Present modeling results and strategic recommendations to senior leadership, IND/NDA teams, and external regulatory agencies as needed.
• Contribute to health authority interactions (e.g., FDA/EMA meetings) by preparing quantitative pharmacology responses and briefing materials.
• Oversee CRO pharmacometricians/modelers and contribute to department-wide methodology and process improvements.

Experience

• Ph.D. in Pharmacometrics, Pharmaceutical Sciences, Clinical Pharmacology, Bioengineering, Systems Biology, or related quantitative discipline (PharmD with relevant pharmacometrics experience also considered).
• Minimum 6–8 years of relevant industry experience in clinical pharmacology/pharmacometrics, with demonstrated hands-on modeling ownership.
• Demonstrated proficiency in QSP model development using MATLAB (and modules such as SimBiology or equivalent).
• Strong hands-on expertise in population PK/PD modeling using NONMEM, including dataset preparation, model diagnostics, and simulation.
• Proficiency in R for pharmacometric data analysis, visualization, and reporting (e.g., tidyverse, xpose, ggplot2, or similar packages).
• Experience translating nonclinical and early clinical (SAD/MAD) data into human dose projections and Phase 2 dosing strategies.
• Experience with bioequivalence/relative bioavailability modeling approaches for formulation, device, or route/site bridging.
• Familiarity with autoimmune, inflammatory, and/or neuromuscular disease areas (e.g., SLE, Sjögren's syndrome, dermatomyositis, gMG, CIDP, MMN) strongly preferred.
• Experience authoring pharmacometric sections of regulatory submissions (IND/CTA, briefing documents, NDA/BLA).
• Excellent written and verbal communication skills, with ability to convey complex quantitative concepts to non-technical stakeholders.