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Data Evaluation of pharmacokinetic parameters in human FcRN mice allometric scaling and data evaluation of FcRn binding characterization using in vitro modelsJob Description
This project aims to evaluate the feasibility and effectiveness of using in vitro and in vivo models to characterize FcRn binding and to estimate the elimination PK parameters of antibody drug candidates in human. This will include: data analysis comparison of invitro and invivo data data mining in silico models reporting.
Major accountabilities:
This internship will focus to work on a discovery pharmacokinetic screening project using a new established hMice model in collaboration with a nonprofit organization outside of Novartis (in life part will be outsourced)
Work on your own Pharmacokinetic evaluation and modeling project under the guidance of seniorlevel quantitative scientists
Analyze data from various sources (e.g. animal studies) as well as in vitro investigations
Attend seminars and other activities to enhance the understanding of the drug development process
Present your project results to quantitative scientists and other stakeholders
Minimu Requirements:
Current enrolled in Master or PhD studies in Pharmacokinetic or Mathematics/Statistics Physics Bioinformatics Biomedical Sciences or Pharmaceutical Sciences/Pharmacy
Good theoretical knowledge in antibody pharmacokinetics as well as PK analysis (e.g. NCA compartmental modelling) and data analysis
Ideal candidate should have understanding of pharmacokinetics and predictive PKPD modeling
Candidate should have proficiency with modelling and simulation software (NONMEM/Monolix MatLab R WinNonLin/Phoenix
Experienced with data sciences (mathematical biostastatistical data analysis)
Candidates must have excellent oral and written communication skills in English as well as strong problemsolving skills
Why Novartis:Helping people with disease and their families takes more than innovative science. It takes a community of smart passionate people like you. Collaborating supporting and inspiring each other. Combining to achieve breakthroughs that change patients lives. Ready to create a brighter future together Desired
Required Experience:
Intern
Full-Time