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GlaxoSmithKline LLC Mechanistic biologics PKPD modeling scientist in Collegeville, Pennsylvania

Reference #: 278012Site Name: UK - Hertfordshire - Stevenage, USA - Pennsylvania - Upper ProvidencePosted Date: Jan 28 2021GSK is seeking a highly motivated and experienced mechanistic modeling scientist to join our Drug Metabolism and Pharmacokinetics modeling team. As a modeling scientist, the successful applicant will develop and drive the preclinical PK/PD strategy for projects with the aim to deliver a robust prediction of the human efficacious dose, with a positive impact on candidate drug selection and the early clinical development strategy.This role will provide YOU the opportunity to lead key activities to progress YOUR career. These responsibilities include some of the following:*Develop and execute a modelling-based strategy for preclinical projects and lead the project team discussions on the human dose prediction prior to candidate selection.*Use PKPD modeling as a tool to help generate better hypotheses and design better, model-informed experiments.*Develop and apply PKPD models to influence critical decisions in drug discovery and development, including target selection, lead optimisation, candidate selection and early clinical development.*Establish concentration-effect relationships from preclinical experiments and provide translation modeling to predict human effects, human doses and early design of clinical trials.*Work closely with other preclinical scientists and with matrix teams to aid the design of experiments and interpretation of the data generated to define project direction and decisions.*Communicate/ report modelling predictions to DMPK Project reps and other key stakeholders to facilitate strategy and decision-making* Active engagement with external modeling community and maintain awareness of new /emerging techniques relevant to the field.*Manage student and post doc programmesWhy you?Basic Qualifications:We are looking for professionals with these required skills to achieve our goals:Advanced degree (PhD) in relevant scientific discipline (e.g. Pharmacology, pharmaceutical sciences or related fields such as math, physics and engineering)5+ years experience in related field or area of study:Successful track record of applying translational PK/PD modeling, especially for large molecules.Providing PK/PD input into the design and interpretation of early preclinical in vivo studiesUtilizing the principles of ADME and pharmacokinetics, (non-compartmental, compartmental, PBPK) and the use of pre-clinical data for human efficacious dose predictionPreferred Qualifications:If you have the following characteristics, it would be a plus:Knowledge of regulatory requirements and drug development processThe ability to work independently, excellent interpersonal, organizational, oral/written communication and teamwork skillsAble to prioritise and work as part of a cross-functional teamActive contributions to external consortia; presenting at conferences and contribution to scientific publicationsWhy GSK?Our values and expectationsare at the heart of everything we do and form an important part of our culture.These include Patient focus, Transparency, Respect, Integrity along with Courage, Accountability, Development, and Teamwork. As GSK focuses on our values and expectations and a culture of innovation, performance, and trust, the successful candidate will demonstrate the following capabilities:Operating at pace and agile decision-making - using evidence and applying judgement to balance pace, rigour and risk.Committed to delivering high quality results, overcoming challenges, focusing on what matters, execution.Continuously looking for opportunities to learn, build skills and share learning.Sustaining energy and well-beingBuilding strong relationships and collaboration, honest and open conversations.Budgeting and cost-consciousnessIf you require an accommodation or other assistance to apply for a job at GSK, please contact the GSK Service Centre at 1-877-694-7547 (US Toll Free) or +1 801 567 5155 (outside US)

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