Principal Scientist - PKDM, Modeling and Simulation

Amgen•South San Francisco, CA

13d

About The Position

Join Amgen’s Mission of Serving Patients At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do. Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. Amgen is advancing a broad and deep pipeline of medicines to treat cancer, heart disease, inflammatory conditions, rare diseases, and obesity and obesity-related conditions. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives. Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career. Principal Scientist-PKDM, Modeling and Simulation What you will do Let’s do this. Let’s change the world. In this vital role you will contribute to Amgen’s diverse discovery and development portfolio of therapeutic modalities with a focus on understanding the pharmacokinetics and pharmacodynamic properties of small and large molecule drug candidates being developed across multiple therapeutic areas in Amgen’s pipeline. This role is responsible for supporting PKPD-related and mathematical modeling activities in the PKDM space for drug discovery and development. You will work directly with other PKDM stakeholders to apply quantitative solutions in the development of novel therapeutics through various activities including target/compound evaluation, design of preclinical studies, investigation of exposure-response relationships, execution of translational strategies, and influencing clinical study design.

Requirements

Doctorate degree PhD OR PharmD OR MD and 2 years of experience applying quantitative PKPD principles to drug development or other relevant experience OR Master’s degree and 5 years of experience applying quantitative PKPD principles to drug development or other relevant experience OR Bachelor’s degree and 7 years of experience applying quantitative PKPD principles to drug development or other relevant experience

Nice To Haves

Doctorate (Ph.D.) in chemical or biomedical engineering; applied mathematics; quantitative pharmaceutical sciences or a related field with 2+ years of experience in drug discovery and development
Proven record of applying systems modeling and simulation approaches in biological systems and/or drug development to support strategic decision making
Proficiency with systems modeling approaches such as differential equations, nonlinear mixed effects modeling, logic, stochastic, agent-based, or other advanced mechanistic modeling approaches is essential
Hands-on experience with relevant software or programming languages (e.g. R, Simbiology, MATLAB, R, or C) is essential
Critical thinking and demonstrated ability to communicate with team members across broad disciplines
Highly motivated, self-driven, can perform well both working independently and in team settings
High degree of flexibility with ability to adapt to different projects and teams
Excellent oral and written communication skills

Responsibilities

Devise and implement quantitative analysis and strategies to inform decision making in drug development by using mathematical modeling and quantitative pharmacology principles with a focus on mechanistic and translational modeling
Collaborate with project team representatives within PKDM and multi-disciplinary teams to generate key knowledge to inform these quantitative strategies
Conduct hands-on work on fit-for-purpose mathematical models (PK-PD, QSP, PBPK) using specialized relevant modeling tools.
Apply AI-ML strategies to modernize traditional PK-PD modeling strategies
Document and archive contributions including data analyses, mathematical models, summary presentations and reports to be shareable with other scientists and foster a collaborative environment
Summarize and articulate salient findings, communicate conclusions back to project team representatives and cross-functional teams and actively participate in team discussions supporting decision making in drug development
Build effective collaborations with peers and stakeholders within and outside the PKDM department including chemistry, biology, toxicology, biomarkers and protein scientists

Benefits

A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
Stock-based long-term incentives
Award-winning time-off plans
Flexible work models where possible

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