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Simulation Framework to Investigate Efficacy and Ocular Safety of Belantamab Mafodotin Combinations in Relapsed/Refractory Multiple Myeloma
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DOI：10.1002/psp4.70276.png)
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Abstract
En 中文
Quantitative modeling can guide drug development and regulatory decisions by providing insights into pharmacokinetics, pharmacodynamics, efficacy, and safety. Integrating models allows simulations that support dosing considerations. A simulation framework for belantamab mafodotin (B) in relapsed/refractory multiple myeloma was developed using data from monotherapy studies and combination studies with bortezomib/dexamethasone (BVd) and pomalidomide/dexamethasone (BPd). Individual changes from baseline in serum M-protein concentrations were modeled using a tumor growth inhibition model. Changes in ophthalmic exam findings (OEFs) grades per the Keratopathy and Visual Acuity (KVA) scale were modeled using a continuous-time Markov model. Belantamab mafodotin concentrations were modeled with a population pharmacokinetic model. All final models adequately described the clinical data. The M-protein/KVA/pharmacokinetic models were integrated in a simulation framework, and simulations of treatment outcomes were performed. Simulated regimens included dose modifications (holds/reductions) for OEFs. Simulations of protocol dosing and dose modifications from the phase 3 DREAMM-7 (BVd) and DREAMM-8 (BPd) trials predicted similar results to the respective trials (for BVd simulations/DREAMM-7 data: very good partial response rates [VGPR+] 62.0%/62.0%, median progression-free survival [mPFS] 39.4/36.6 months, and grade ≥ 3 OEFs 87.5%/76.5%; for BPd simulations/DREAMM-8 data: VGPR+ rates 60.2%/68.0%, mPFS not reached/not reached, and grade ≥ 3 OEFs 77.2%/82.5%). Simulations of alternative BVd regimens indicated that a 2.5 mg/kg starting dose produces the highest efficacy, and schedule extensions after the first BVd dose can improve tolerability while continuing to demonstrate efficacy. This framework adequately predicted outcomes from DREAMM-7/DREAMM-8, supporting its use to predict benefit–risk profiles of alternate belantamab mafodotin dosing strategies.
Keywords:
Categorical data
dose
Markov chain
model based drug development
model evaluation
oncology
optimization
population pharmacokinetics–pharmacodynamics
trial simulation
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