Contact: Neisha Camacho/Terra Parsons - teamnt@penfieldsearch.com
No 3rd party candidates

Position Summary
The Associate Director, Pharmacometrics will serve as a strategic leader, accountable for driving model-informed drug development across programs. This role will oversee and conduct pharmacometric analyses — including population PK/PD, exposure–response, PBPK, and clinical trial simulations — to inform study design, dose selection, and regulatory interactions. The Associate Director will partner with senior leaders across statistics, clinical, regulatory, and research functions, lead collaborations with external vendors, and mentor internal team members to expand pharmacometric capabilities.

Primary Responsibilities

• Provide strategic leadership for pharmacometric approaches across multiple programs, ensuring alignment with development objectives and regulatory expectations.
• Lead pharmacometric analyses (population PK/PD, exposure–response, PBPK) and collaborate with statistics on clinical trial simulations to inform clinical study design, dose selection, and regulatory submissions.
• Serve as the primary pharmacometric representative in cross-functional development teams and regulatory interactions.
• Critically evaluate data quality and appropriateness for pharmacometric analyses, ensuring robust and transparent model development.
• Author and review pharmacometric sections of regulatory documents, including clinical study protocols, study reports, briefing books, and IND/NDA/BLA submissions.
• Guide development and execution of Modeling & Simulation (M&S) strategies, including disease progression models and clinical trial simulations, partnering with external vendors as appropriate.
• Mentor and train junior colleagues, fostering expertise in quantitative pharmacology tools and approaches.
• Communicate outcomes of pharmacometric analyses to diverse stakeholders, translating results into actionable insights for clinical and regulatory decision-making.
• Contribute to thought leadership through publications, conference presentations, and participation in scientific consortia.

Desired Experiences

• Experience collaborating with statistics on advanced statistical and modeling frameworks, such as model-based meta-analyses, Bayesian and hierarchical non-linear mixed-effects models, joint models for longitudinal and time-to event data, and TTE-PD models.
• Experience incorporating machine-learning into typical analyses to build stronger PK/PD models, such as ML to augment covariate detection, feature engineering and population clustering;
• Experience incorporating digital biomarkers, imaging biomarkers, omics, RWD and external controls into PK/PD frameworks
• Experience with FDA MIDD framework and QSP; knowledge of FDA/EMA MIDD pilots and lessons learned
• Knowledge of future-looking frontiers such as digital twin approaches, small-n Bayesian borrowing strategies and AI-accelerated model discovery.

Qualifications and Key Success Factors

• Advanced degree (PhD strongly preferred, or MSc) in Pharmacometrics, Clinical Pharmacology, Biostatistics, Bioengineering, or related quantitative field.
• PhD with 8–12 years or MSc with 10–14 years of experience in pharmacometrics, clinical pharmacology, or quantitative sciences within drug development.
• Demonstrated expertise in population PK/PD, exposure–response, PBPK, and clinical trial simulation to support decision-making in clinical development.
• Proven track record of regulatory submissions and interactions (FDA, EMA, etc.) involving pharmacometric analyses.
• Strong leadership experience, including mentoring, managing external vendors, and influencing cross-functional strategy.
• Hands-on expertise with pharmacometric and statistical software (e.g., NONMEM, Monolix, Phoenix NLME, SimCYP, R, Stan, NIMBLE, PyMC)
• Excellent scientific communication and writing skills, with the ability to clearly present quantitative analyses to technical and non-technical stakeholders.
• Ability to manage multiple projects under aggressive timelines with independence, creativity, and strategic vision.
• Commitment to innovation, openness to new methodologies, and alignment with company values.