Intern, Clinical Pharmacology & Quantitative Science (Project: Translational PBPK Modeling for [...]

Genmab; Utrecht; Hybrid; EUR 8,000 - 9,000; Full time

Benefits offered by this job

Pension

Health insurance

Paid time off

Employee support programs

Job summary

Genmab in Utrecht, Netherlands, offers a 6–12 month internship in quantitative pharmacology and translational modeling. You will build a mechanistic ocular PBPK framework for ADCs and payloads, connecting systemic kinetics to eye compartments.

The role requires master’s enrollment and strong PK modeling skills, with a hybrid work arrangement. You will calibrate the model with case studies, review ocular PK models, and deliver reproducible code, data, figures, and a manuscript-ready report in

Qualifications

• Currently enrolled in a Dutch university Master’s program in pharmacometrics, pharmaceutical sciences, biomedical engineering, systems biology, quantitative biology, bioinformatics, toxicology, biomedical sciences, or related field.
• Internship must be a formal, mandatory component of degree; not for graduates or extracurricular internships.
• Minimum 6 months; 9–12 months preferred.
• Experience with R or Python and interest in mechanistic PK modeling.

Responsibilities

• Conduct structured literature reviews on cytotoxic agents, ADC payloads, and ocular toxicity patterns.
• Build a curated evidence base covering ocular adverse events, PK data, and tissue data.
• Review published ocular PK/BiPK models and define a fit-for-purpose ADC/payload model structure.
• Implement an ocular PBPK model in R or equivalent, linking systemic kinetics to eye compartments.
• Calibrate and evaluate the framework across case studies with different targets and payloads.
• Perform sensitivity analyses to identify drivers of local ocular exposure and toxicity mechanisms.
• Run prospective design scenarios to assess payload properties and dosing impact on ocular exposure.
• Translate results into a practical risk‑assessment workflow for ADC design.

Skills

R or Python experience

Mechanistic PK modeling

PBPK/ODE familiarity

Education

Master's degree program (Dutch university)

Tools

RxODE2

mrgsolve

PK-Sim

R

Job description

At Genmab, we are dedicated to building extra[not]ordinary® futures, together, by developing antibody products and groundbreaking, knock-your-socks-off KYSO antibody medicines® that change lives and the future of cancer treatment and serious diseases. We strive to create, champion and maintain a global workplace where individuals’ unique contributions are valued and drive innovative solutions to meet the needs of our patients, care partners, families and employees.

Our people are compassionate, candid, and purposeful, and our business is innovative and rooted in science. We believe that being proudly authentic and determined to be our best is essential to fulfilling our purpose. Yes, our work is incredibly serious and impactful, but we have big ambitions, bring a ton of care to pursuing them, and have a lot of fun while doing so.

Why Genmab

Our internship program provides interns with hands-on experience and relevant projects that directly align with our company's goals. Additionally, we believe our program provides a valuable opportunity to learn, thrive, and build a strong network.

The Role

Are you interested in understanding why some antibody-drug conjugates (ADCs) cause ocular adverse effects while other ADCs with related targets or payloads do not? Would you like to combine pharmacokinetics, mechanistic modeling, ocular biology, and translational safety to help design safer cancer therapeutics? Keep on reading!

We are looking for a highly motivated intern to join our quantitative pharmacology and translational modeling team in Utrecht. You will develop a mechanistic ocular physiologically based pharmacokinetic (PBPK) framework for systemically administered ADCs and their released cytotoxic payloads. The framework will connect published antibody and small-molecule ocular distribution models with an existing systemic ADC modeling framework to predict local exposure in relevant eye compartments and cell types.

Central hypothesis: Ocular risk is driven by local exposure rather than plasma exposure alone, and local exposure reflects the interaction of systemic ADC disposition, linker stability and payload release, ocular barrier transport, tissue partitioning, target expression and internalization, intracellular sequestration, and clearance.

You will test this hypothesis by retrospectively reconstructing historical ADC and cytotoxic-agent case studies with contrasting ocular safety profiles. The model will distinguish, as supported by the available data, intact antibody or ADC, conjugated payload, and released payload. Candidate mechanisms will include target-related uptake, non-target-mediated uptake, lysosomal trapping, melanin binding, protein and phospholipid binding, transporter effects, and payload permeability. Where suitable data are available, predictions may also be linked to concentration-response information from human eye-derived organoids or other new approach methodology (NAM) systems.

Responsibilities

• Conduct a structured literature review of small-molecule cytotoxic agents, ADC payloads, and historical ADCs with and without reported ocular toxicity.
• Build a curated, analysis-ready evidence base covering clinical ocular adverse-event patterns, systemic pharmacokinetics, ocular tissue data, vulnerable ocular cell types, target expression, payload class and physicochemical properties, linker design and stability, drug-to-antibody ratio, and relevant nonclinical findings.
• Review published ocular PK and PBPK models for antibodies and small molecules, including the Shah/Betts antibody biodistribution framework and models of systemic-to-eye distribution, and define a fit-for-purpose model structure for ADCs and payloads.
• Implement a reproducible ocular PBPK model in R or a comparable modeling environment, linking systemic ADC and payload kinetics to compartments such as the choroid/retina, vitreous, aqueous humor, iris-ciliary body, cornea, and other tissues as justified by the data.
• Retrospectively calibrate and evaluate the framework using selected case studies across contrasting targets, payload classes, linker properties, and ocular safety outcomes; clearly separate model calibration, evaluation, and exploratory application.
• Use sensitivity and uncertainty analyses to identify the principal drivers of local ocular exposure and to distinguish plausible target-related from target-independent toxicity mechanisms.
• Run prospective design scenarios to assess how payload properties, linker stability, antibody distribution, target biology, and dose influence ocular exposure and the predicted separation between efficacy-relevant tumor exposure and local ocular exposure.
• Translate the results into a practical risk‑assessment workflow for early payload, linker, and ADC design decisions, with transparent assumptions and confidence levels.
• Deliver documented model code, a curated dataset and data dictionary, publication-quality figures, an internal scientific presentation, and a manuscript-ready report or draft publication.
• Work closely with colleagues in quantitative pharmacology, toxicology and safety, ADC discovery, bioinformatics, and translational research.

Requirements

• Currently enrolled in a Master's degree program at a Dutch university in pharmacometrics, pharmaceutical sciences, biomedical engineering, systems biology, quantitative biology, bioinformatics, toxicology, biomedical sciences, or a related field.
• This internship must be a formal, mandatory component of your degree program required for graduation; we cannot consider candidates who have already graduated or who are seeking an extracurricular internship.
• Available for a minimum of 6 months; 9 - 10 months is preferred for completion of the full modeling and manuscript scope.
• Experience with R or Python and a strong interest in mechanistic pharmacokinetic modeling. Experience with ordinary differential equations, PBPK, population PK, RxODE2, mrgsolve, PK‑Sim, or similar tools is an advantage.
• A sound understanding of pharmacokinetics, drug distribution, or quantitative pharmacology. Familiarity with ADCs, ocular biology, drug safety, or small-molecule physicochemical properties is desirable but can also be developed during the internship.
• Ability to search and critically assess scientific literature, curate heterogeneous data, document assumptions, and communicate results clearly to both modeling and non-modeling colleagues.
• Curious, rigorous, collaborative, and comfortable working across disciplines in a research environment.

General Information

• Internship duration: 6-12 months; 9-12 months preferred.
• Start date: 1 November, 2026.
• Location: Utrecht, Netherlands.
• This is a full-time hybrid internship position.
• The final project scope will be calibrated to the internship duration and the availability of suitable public and internal data.

The proposed gross annual/monthly base salary range for this position, in the primary location, based on a full time schedule is:

EUR750,00---750,00

The final salary offer will depend on several factors, including your skills, qualifications, and experience.

In addition to base salary, this position is eligible for additional forms of compensation, such as discretionary bonuses and long-term incentives.

Benefits

When you join Genmab, you become a part of a culture that supports your physical, financial, social, and emotional well-being. Our benefits include, but are not limited to:

• Pension
• Health insurance and wellness benefits
• Paid time off
• Employee support programs

Further details on eligibility for compensation and benefits based on the role will be provided during the recruitment process.

About Genmab

Genmab is an international biotechnology company with a core purpose to improve the lives of patients through innovative and differentiated antibody therapeutics. For 25 years, its hard-working, innovative and collaborative team has invented next-generation antibody technology platforms and harnessed translational, quantitative and data sciences, resulting in a proprietary pipeline including bispecific T-cell engagers, antibody-drug conjugates, next-generation immune checkpoint modulators and effector function-enhanced antibodies. By 2030, Genmab’s vision is to transform the lives of people with cancer and other serious diseases with Knock-Your-Socks-Off (KYSO®) antibody medicines.

Established in 1999, Genmab is headquartered in Copenhagen, Denmark with international presence across North America, Europe and Asia Pacific. For more information, please visit Genmab.com and follow us on LinkedIn and X.

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Please note that if you are applying for a position in the Netherlands, Genmab’s policy for all permanently budgeted hires in NL is initially to offer a fixed-term employment contract for a year, if the employee performs well and if the business conditions do not change, renewal for an indefinite term may be considered after the contract.