Abstract

SG is a novel antibody-drug conjugate (ADC) composed of an anti–Trop-2 antibody coupled to SN-38 via a proprietary, hydrolyzable linker. SG is approved for pts with mTNBC who received ≥2 prior chemotherapies (>1 in the metastatic setting) and has accelerated approval for pts with metastatic urothelial cancer who received prior platinum-containing chemotherapy and a PD-1/PD-L1 inhibitor. These analyses evaluated the PK of SG, Free SN-38, and Total Antibody (tAB) with SG administration. Population PK (PopPK) models were developed using data from 529 pts across 2 clinical studies, IMMU-132-01 (phase 1/2 in pts with advanced epithelial cancers including TNBC, UC, and lung cancer; PK n=276) and ASCENT (phase 3 in pts with mTNBC who received ≥2 prior therapies (>1 in the metastatic setting); PK n=253). Pts received SG at 8 to 18 mg/kg IV (IMMU-132-01) or 10 mg/kg IV (ASCENT) on d1 and d8, of every 21d cycle. Clinically relevant covariates were evaluated to assess their impact on exposure. The PopPK models of SG and tAB were developed independently. The model of Free SN-38 was developed in a sequential manner with a first-order release of Free SN-38 (payload) from SG (the ADC). The typical parameter estimates for clearance and steady-state volume of distribution were 0.133 L/hr and 3.68 L for SG and 0.0164 L/hr and 4.26 L for tAB. Bodyweight correlated with the clearance and volume parameters of all 3 analytes, but with limited impact on the exposure with the clinical regimen. There was no model-predicted accumulation of either SG or Free SN-38 with repeated dosing. Overall, mild to moderate renal impairment, mild hepatic impairment, age, sex, baseline albumin level, race, ECOG status, tumor type, UGT1A1 genotype or Trop-2 expression did not have a clinically relevant impact on exposure of any of the evaluated analytes. The PK of SG, Free SN-38, and Total Antibody were well characterized based on a robust dataset across two large trials. The analyses supported the approved 10 mg/kg clinical regimen and did not identify a need for dose-adjustment based on any of the evaluated patient demographics or disease characteristics.

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