New

Clinical Pharmacology Intern

Spectraforce Technologies
United States, California, San Diego
May 05, 2026
Job Title: Clinical Pharmacology Intern - Oncology Duration: 2 Months and 20 days Location:San Diego,CA Internship Overview Support translational PK-PD modeling efforts for antibody-drug conjugates (ADCs) with vedotin payload Investigate variability in preclinical tumor static concentration (TSC) estimates Collaborate with clinical pharmacology and translational modeling teams Contribute to early ADC candidate selection and development decisions Project Description Analyze variability in TSC estimates across vedotin ADCs despite similar PK and safety profiles Evaluate translational relevance of TSC as a preclinical efficacy metric Integrate xenograft PK/PD models with ADC-specific attributes Explore alternative modeling frameworks using in vitro and in vivo preclinical data Improve interpretation of preclinical efficacy signals Key Responsibilities Curate, harmonize, and quality check preclinical (in vitro and in vivo) datasets Standardize xenograft PK/PD model structures and TSC estimation methods Perform multivariate and model-based analyses to identify drivers of TSC variability Evaluate assumptions in existing translational PK/PD models Develop alternative mechanistic or systems-based modeling strategies Interpret results for translational relevance and early-stage decision-making Prepare final technical report and presentation with recommendations Required Qualifications Enrolled in MS, PhD, PharmD, or equivalent in: Pharmacometrics Clinical Pharmacology Biomedical Engineering Biostatistics Quantitative Biology or related field Strong quantitative and analytical skills Experience with R (or similar statistical programming tools) Knowledge of PK/PD concepts and multivariate analysis Ability to communicate complex quantitative findings clearly Preferred Qualifications Experience in PK/PD or mechanistic modeling (oncology/biologics preferred) Familiarity with xenograft and tumor growth inhibition (PK-TGI) models Knowledge of ADCs, payload pharmacology, or target-mediated drug disposition Experience integrating in vitro and in vivo data Interest in model-informed drug development (MIDD) Learning Outcomes Hands-on experience in translational PK/PD modeling for ADCs Understanding of drivers behind preclinical efficacy metrics like TSC Exposure to best practices in interpreting preclinical PK/PD data Contribution to early oncology drug development and decision-making