Scientific Director, Pharmacometrics

EMD Serono Research & Development Institute•Billerica, MA

38d

About The Position

The role of Scientific Director, Pharmacometrics, in Quantitative Pharmacology within the broader Clinical Measurement Sciences organization, is a scientific and cross-functional role, responsible for developing and executing Model Informed Drug Development (MIDD) plans and strategies from the early translational to the late-stage clinical development in cross functional drug discovery and development project teams in close collaboration with colleagues in Clinical Pharmacology, Translational Quantitative Pharmacology, Biostatistics, Data Sciences, Patient-Focused Real-World Evidence, Clinical Biomarkers and Diagnostics, Research, Clinical Development and other colleagues within the R&D organization. In this role, the incumbent will participate in activities to strengthen pharmacometrics platform capabilities by contributing to the strategic use of modeling & simulation (M&S) methodologies across disease areas, in alignment with the clinical development plan. There will be close engagement with all key stakeholders to ensure timely and high-quality pharmacometrics deliverables for the program. The incumbent will be responsible for pharmacometrics activities executed internally or in collaboration with external CROs and will provide close scientific and technical supervision. The incumbent will also be expected to independently manage multiple projects simultaneously and participate in discussions and presentations. This position reports to the Global Head of Pharmacometrics and Systems Pharmacology.

Requirements

PhD in Pharmacometrics or a related disciple (e.g. Clinical Pharmacology, Statistics, Engineering, Mathematics)
5+ years of experience with hands-on pharmacometrics modeling and application of MIDD principles in a drug-development setting.
Position requires both domestic and international travel up to 20% of time
Excellent knowledge of and experience in application of population PK/PD models, exposure-response models, disease progression models, clinical trial simulations, Bayesian methodologies, and model-based meta-analyses to drive MIDD
Thorough understanding of global regulatory guidelines relevant to MIDD (e.g., Population PK, exposure-response, pediatric extrapolation)
Ability to translate highly mechanistic systems models to population PK/PD frameworks in clinical development
Experience in pharmacostatistical modeling methods and sound understanding of the principles of statistics including Bayesian methodologies as applicable for advanced pharmacometrics modeling and clinical trial simulations
Experience with model-informed development of both small molecules and biologics and across all phases of clinical development is required.
Good command of NONMEM and R is an absolute prerequisite.

Nice To Haves

Knowledge of emerging areas of pharmacometrics including applications of machine learning/ artificial intelligence for model-informed precision medicine development
Experience with other tools (e.g., MONOLIX, PsN, Xpose, SAS, Stan, Python, MATLAB and Simcyp) is desired.
General knowledge of oncology, neurology and/or immunology, is desirable

Responsibilities

Prepare, execute, present, report and/or supervise modeling & simulation projects; responsible for summarizing and reporting pharmacometrics content in relevant regulatory submission documents (e.g., HA Briefing Documents, CTD 2.7.2)
Develop and execute MIDD strategies/plans which are fully integrated with the overall clinical development plan
Apply MIDD methodologies to contribute to decision making at critical milestones based on quantitative principles in close collaboration with partner functions
Practice and promote quantitative decision-making by leveraging the totality of evidence approach and enable the integration of all relevant data within and outside the development program (including literature and competitor data, and Real World data) using state-of-the-art disease models, clinical trial simulations and Bayesian probabilistic frameworks to enhance clinical trial design and inform assessment of probability of success
Collaborate with Translational QP to appropriately transition Quantitative Systems Pharmacology models developed in Research and preclinical development to population PK/PD M&S frameworks that preserve adequate mechanistic resolution for applications in clinical development.
Keep up to date with scientific advancements in pharmacometrics and share expertise with colleagues.