Alma Tan 1, Juliëtte Zwaveling 1, Rob Ter Heine 2, Dirk Jan Moes 1
1 Department of Clinical Pharmacy & Toxicology, Leiden University Medical Center (Leiden, Netherlands), 2 Department of Pharmacy, Pharmacology and Toxicology, Radboud University Medical Center (Nijmegen, Netherlands)
Introductions: Approximately 15-20% of breast cancers overexpress human epidermal growth factor receptor 2 (HER2), a molecular subtype associated with poor survival outcomes (1, 2). Trastuzumab emtansine (T-DM1) and trastuzumab deruxtecan (T-DXd) are the primary ADCs available for HER2-positive breast cancer. For both agents positive efficacy and safety profiles were determined at 3.6mg/kg for T-DM1 and 5.4 mg/kg for T-DXd. With a dosage algorithm of mg/kg one would expect a linear relationship of clearance (CL) with body weight (BW). However, for T-DM1 and T-DXd the allometric exponents of BW for CL are 0.49 and 0.37, respectively. Patients at BW extremes are, therefore, at more risk of toxicity or inefficacy. In addition, mg/kg dosing inherently results in relative high drug spillage with use of incomplete vials and, as both agents are very costly, spillage of health care budget. These limitations of linear mg/kg dosing can be addressed through development of alternative model-informed dosing regimens. From a regulatory perspective, the FDA endorsed the use of modeling and simulation for alternative dosing in the guidance document on PD-1/PD-L1 blocking antibodies (3). We propose that the more narrow therapeutic index status of ADCs warrants the application of the more stringent criteria (90-111%) to determine PK-equivalence (4, 5).
Objective: We aimed to develop alternative allometric dosing algorithms for T-DM1 and T-DXd to reduce costs, while maintaining equivalent exposure. 
Methods: Population pharmacokinetic models for T-DM1 and T-DXd, sourced from EMA public assessment reports, were used for Monte Carlo simulations in NONMEM V7.5. Both agents are described by a two-compartment model with linear elimination. A virtual patient population was derived from historical age and weight data from female patients at Radboud University Medical Center (Nijmegen, The Netherlands). BW distributions were matched to the population of the pivotal EMILA trial for T-DM1. (6). Exposure metrics were predicted for the approved regimens and alternative BW-band regimens using complete vials. Equivalence was assessed for the pharmacokinetic parameters; AUC and Ctrough at cycle 1 and steady state and confirmed when geometric mean ratios were within 0.9-1.11. For dose reductions, the goal was to maintain reduction percentages within 10% of the approved reduction percentages. Therefore, the use of half-vials was permitted, and BW-band groups from the initial regimen were preserved.
Results: Equivalent exposure was achieved with BW-band regimens for T-DM1 (<35 kg: 100 mg, 35-45 kg: 160 mg, 45-65 kg: 200 mg, 65-100 kg: 260 mg, 100-130 kg: 300 mg, ≥130 kg: 320 mg) and T-DXd (<65 kg: 300 mg, 65-120 kg: 400 mg, ≥120 kg: 500 mg), with geometric mean ratios for all pharmacokinetic parameters of 0.948 and 0.959, respectively. Following the BW-based regimen, exposure stratification across the BW range revealed similar exposure to the median patient throughout all BW categories. In contrast, patients at BW extremes showed considerable deviations with the approved linear mg/kg regimen. Overall exposure was accordingly reduced, with the standard deviation of steady state AUC decreasing by 10% and 7% for T-DM1 and T-DXd, respectively. All selected dose reductions deviated less than 10% from the approved reduction percentages. Implementation of these regimens could reduce drug costs by 14% for T-DM1 and 16% for T-DXd. Conclusions: The proposed model-informed BW-band dosing regimens for T-DM1 and T-DXd substantially reduce exposure variability across the BW range. Patients previously at risk of underexposure or toxicity now achieve exposures closer to the population mean. Clinical adoption could reduce drug costs by approximately 14% for T-DM1 and 16% for T-DXd. References: 1. Giaquinto AN, Sung H, Miller KD, Kramer JL, Newman LA, Minihan A, et al. Breast Cancer Statistics, 2022. CA Cancer J Clin. 2022;72(6):524–41. 2. Howlader N, Cronin KA, Kurian AW, Andridge R. Differences in Breast Cancer Survival by Molecular Subtypes in the United States. Cancer Epidemiol Biomarkers Prev. 2018;27(6):619–26. 3. (FDA) USFaDA. Pharmacokinetic-Based Criteria for Supporting Alternative Dosing Regimens of Programmed Cell Death Receptor-1 (PD-1) or Programmed Cell Death-Ligand 1 (PD-L1) Blocking Antibodies for Treatment of Patients with Cancer: Guidance for Industry. In: Oncology Center of Excellence CfDEaR, editor. 2022. 4. (CHMP) EMAECfMPfHU. Guideline on the Investigation of Bioequivalence. European Medicines Agency; 2010. Report No.: CPMP/EWP/QWP/1401/98 Rev. 1/Corr**. 5. de Goeij BE, Lambert JM. New developments for antibody-drug conjugate-based therapeutic approaches. Curr Opin Immunol. 2016;40:14–23. 6. Verma S, Miles D, Gianni L, Krop IE, Welslau M, Baselga J, et al. Trastuzumab emtansine for HER2-positive advanced breast cancer. N Engl J Med. 2012;367(19):1783–91.
Reference: PAGE 34 (2026) Abstr 12291 [www.page-meeting.org/?abstract=12291]
Poster: Clinical Applications