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 in-vitro and in-vivo 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 non-profit organization outside of Novartis (in life part will be outsourced)
• Work on your own Pharmacokinetic evaluation and modeling project under the guidance of senior-level 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.

• 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 PK-PD 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 problem-solving skills.