VIRTUAL PK/PD MODELING OF BIOMARKER GUIDED ELRANATAMAB RESPONSE PREDICTION
Author(s)
Jesmitha J. M, PharmD1, Ganesan Rajalekshmi Saraswathy, PhD2.
1Student, M S Ramaiah University Of Applied Sciences, Bengaluru, India, 2Pharmacy Practice, M S Ramaiah University Of Applied Sciences, Bangalore, India.
1Student, M S Ramaiah University Of Applied Sciences, Bengaluru, India, 2Pharmacy Practice, M S Ramaiah University Of Applied Sciences, Bangalore, India.
OBJECTIVES: To develop a virtual population PK/PD model linking Elranatamab exposure to kappa Serum kappa free light-chain (FLC) suppression and evaluate the predictive value of early biomarker dynamics. A secondary objective was to develop an interactive Shiny-based platform for response visualization and prediction.
METHODS: A literature-informed PK/PD simulation framework was developed in R using rxode2. A one-compartment Elranatamab PK model was linked to an indirect response model describing kappa FLC suppression. A virtual population of 1000 patients were generated incorporating interindividual variability in pharmacokinetic and pharmacodynamic parameters. Simulations were performed using clinically relevant Elranatamab dosing schedules. Response thresholds at weeks 2, 4, and 8 were evaluated, and a Shiny application was developed to visualize biomarker trajectories and predicted response categories.
RESULTS: Simulations demonstrated substantial variability in kappa FLC suppression. At weeks 2, 4, and 8, 61.8%, 53.9%, and 37.8% of patients achieved predefined response thresholds, respectively. Median times to ≥25%, ≥50%, and ≥75% kappa decline were 13, 26, and 43 days. Patients achieving ≥50% kappa decline by week 2 demonstrated a 95.6% probability of week-8 strong response, compared with 1.3% among those with <25% decline. Simulated resistant patients exhibited attenuated biomarker suppression and reduced response rates.
CONCLUSIONS: Early kappa FLC suppression demonstrated strong potential for predicting subsequent Elranatamab response in RRMM. This virtual PK/PD framework and accompanying Shiny application provide a proof-of-concept platform for biomarker-guided response prediction and future precision dosing strategies.
METHODS: A literature-informed PK/PD simulation framework was developed in R using rxode2. A one-compartment Elranatamab PK model was linked to an indirect response model describing kappa FLC suppression. A virtual population of 1000 patients were generated incorporating interindividual variability in pharmacokinetic and pharmacodynamic parameters. Simulations were performed using clinically relevant Elranatamab dosing schedules. Response thresholds at weeks 2, 4, and 8 were evaluated, and a Shiny application was developed to visualize biomarker trajectories and predicted response categories.
RESULTS: Simulations demonstrated substantial variability in kappa FLC suppression. At weeks 2, 4, and 8, 61.8%, 53.9%, and 37.8% of patients achieved predefined response thresholds, respectively. Median times to ≥25%, ≥50%, and ≥75% kappa decline were 13, 26, and 43 days. Patients achieving ≥50% kappa decline by week 2 demonstrated a 95.6% probability of week-8 strong response, compared with 1.3% among those with <25% decline. Simulated resistant patients exhibited attenuated biomarker suppression and reduced response rates.
CONCLUSIONS: Early kappa FLC suppression demonstrated strong potential for predicting subsequent Elranatamab response in RRMM. This virtual PK/PD framework and accompanying Shiny application provide a proof-of-concept platform for biomarker-guided response prediction and future precision dosing strategies.
Conference/Value in Health Info
2026-11, ISPOR Europe 2026, Vienna, Austria
Value in Health, Volume 29, Issue 12S
Code
CO23
Topic
Clinical Outcomes, Methodological & Statistical Research, Patient-Centered Research
Topic Subcategory
Clinical Outcomes Assessment
Disease
Oncology, Personalized & Precision Medicine