Location:Mountain View, United StatesJob reference:
Sep. 16, 2016
This is a strategic and scientific role within Clinical Pharmacology & DMPK (CPD), which provides nonclinical and clinical PK/PD, pharmacometrics and bioanalytical support for biotherapeutics projects from discovery research to BLA registration and commercialization.
The pharmacometrician will conduct advanced population modeling and stochastic clinical trial simulations for late-stage biotherapeutics projects. In collaboration with clinical pharmacokineticists, statisticians and physicians, the pharmacometrician will work as a partner in cross-functional project teams providing sophisticated M&S support for clinical dose recommendation, exposure-response assessment, and regulatory filings.
Leverage M&S expertise to address key clinical development questions. Contribute to the statistical analysis and pharmacometrics plans for late-stage projects. Represent pharmacometrics in clinical data analysis teams and study-specific working groups.
* Use innovative quantitative approaches to integrate knowledge of PK, PD, efficacy, safety, patient demographics, and pathophysiological factors to characterize exposure-response relationship and evaluate potential covariate effects.
* Generate pharmacometrics technical reports, contribute to the regulatory submission packages, and participate in regulatory meetings as appropriate. Collaborate with clinical pharmacokineticists and monitor outsourced modeling activities to ensure quality and timely delivery.
* Actively promote MedImmune as a biopharmaceutical leader in the utilization of quantitative model-based drug development approach. Support MedImmune publication strategy. Present and report data in approved external conferences and scientific/medical journals.
* A doctorate degree with demonstrated experience in pharmacometrics and strong quantitative skills.
* <2 years of relevant industry experience. Prior experience in regulatory filings is desired but not required.
* Proven track record of working experience in population modeling and simulations using NONMEM. Familiarity with statistical software package Splus, R or SAS.
* Good communication and scientific writing skills, and ability to independently work in a matrix environment.