About

Senior Director, Pharmacometric Services

Buffalo, NY, Lancaster, CA, Paris, France, Remote Work, Research Triangle Park, NC

Position Requirements:

 This leadership role is responsible for managing a multidisciplinary scientific consulting group engaged in collaborations with sponsors to use modeling and simulation in support of drug development and regulatory decision-making. In addition to providing direction and leadership to the group, this role may serve as the main point of contact for assigned clients and projects. Responsibilities also include an expert scientific review of client deliverables and the formulation of strategic development plans and pharmacometric analysis plans, ensuring the appropriateness of methods for data handling and analysis as well as compliance with current regulatory guidance. Assistance in furthering the development of scientific skills in direct and indirect reports by reviewing work products, providing direction and guidance in the interpretation of findings, and refinement of strategy, is also expected.

Duties and Responsibilities:

 The selected candidate will lead and manage a team of scientists and engage in technical activities ranging from consultations on study design through development and evaluation of models, the performance of simulations, and presentation of results.

Qualifications:

 Ph.D. in pharmacokinetics, pharmaceutics, pharmacology, or related field

  • 10-15 years post-PhD or MS/PharmD expert pharmacometrician and modeler
  • Experience managing a team of Scientists
  • Extensive experience implementing (hands-on skills a must) and providing strategic direction for pharmacometric analyses to guide drug development and regulatory decision making
  • Solid understanding of the regulatory review process and experience in responding to regulatory requests a must
  • Experience with Monolix, NONMEM, and R
  • Qualified candidates should be very familiar with population PK and PK/PD modeling, exposure-response analyses, clinical trial simulation, and disease progression modeling; experience with model-based meta-analysis, survival/time-to-event modeling, categorical endpoint analysis, and machine learning approaches ideal

 

Remote work options will be considered.

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