Quantitative Translational Pharmacology Intern

StudentJob; Utrecht; Hybrid; EUR 7,100 - 9,600; Full time

Benefits offered by this job

Pension

Health insurance and wellness benefits

Paid time off

Employee support programs

Job summary

Genmab is offering a Masters internship in Quantitative Translational Pharmacology in Utrecht, Netherlands. You will contribute to a project modeling tumor growth inhibition to improve animal study decisions and patient exposure predictions.

You will integrate data from in vitro, preclinical, and clinical studies, calibrate models, and collaborate with a multidisciplinary team. Hybrid work and a 6–12 month duration are expected.

Qualifications

• Enrollment in a Master’s programme in Biopharmaceutical Sciences, Biomedical Sciences, Drug Innovation, Pharmacy, or similar in the Netherlands.
• Must be a mandatory part of degree for graduation; graduates or extraneous internships not considered.
• Basic knowledge of cancer biology/immunology.
• Familiarity with PK/PD, PBPK, and/or QSP modeling including calibration/evaluation.
• Experience with programming, preferably in R.

Responsibilities

• Implement a tumor growth inhibition model within the translational PBPK/PD framework.
• Compile, curate, and analyze in vitro, preclinical, and clinical datasets for translational modeling.
• Compare in vitro-only vs. combined in vitro/in vivo strategies for predicting patient exposure.
• Investigate reducing/refining preclinical animal studies via modeling.
• Perform exploratory analyses and evaluate model performance with diagnostics.
• Present findings through reports and presentations to the team.

Skills

R programming

PK/PD modeling

Quantitative modeling

English communication

Education

Master's student in Biopharmaceutical Sciences or related

Tools

R

Nonlinear mixed-effects modeling

Job description

Genmab is offering a Masters internship in Quantitative Translational Pharmacology in Utrecht, Netherlands. You will contribute to a project modeling tumor growth inhibition to improve animal study decisions and patient exposure predictions.

You will integrate data from in vitro, preclinical, and clinical studies, calibrate models, and collaborate with a multidisciplinary team. Hybrid work and a 6–12 month duration are expected.