BI 836880 Dose Optimization via Biomarker and PK/PD Modeling in Advanced Solid Tumors
Key Insights
Researchers utilized a comprehensive biomarker and modeling approach to optimize the dose of BI 836880, a VEGF (search)/Ang-2 (search) inhibitor, in advanced solid tumors (search).
Population PK/PD modeling integrated data from Phase I studies to predict BI 836880 concentrations and Ang-2 (search) inhibition, informing dose selection.
Simulations indicated the probability of achieving target Ang-2 (search) inhibition levels with different BI 836880 doses, supporting individualized treatment strategies.
BI 836880, a vascular endothelial growth factor (VEGF (search)) and angiopoietin-2 (Ang-2 (search)) inhibitor, has undergone dose optimization using a comprehensive biomarker and modeling approach in patients with advanced solid tumors (search). The study integrated data from two Phase I dose-escalation trials (1336.1 and 1336.6) to develop a population pharmacokinetic/pharmacodynamic (PopPK/PD) model, aiming to predict drug concentrations and Ang-2 inhibition levels, ultimately informing optimal dosing strategies.
Study Design and Methods
The trials enrolled adult patients with locally advanced or metastatic solid tumors (search) refractory to standard therapy. Patients received BI 836880 intravenously, either once every three weeks (q3w) or once weekly (qw). Biomarker data, including free and total VEGF-A (search) and Ang-2 (search), along with circulating angiogenic factors (sVEGFR3, sTie2, PlGF), were collected at various time points. Dynamic contrast-enhanced MRI (DCE-MRI) scans were performed to assess microvascular changes. A PopPK model was developed based on BI 836880 plasma concentrations, and a PD model was subsequently built using individual drug concentrations to predict Ang-2 levels. Simulations were then conducted to determine the probability of achieving target Ang-2 inhibition with different doses.
Biomarker Analysis and Modeling
Total VEGF-A (search) levels were determined using nano liquid chromatography high-resolution mass spectrometry (LC-HRMS). Free VEGF-A was measured using an electrochemiluminescence immunoassay. Total Ang-2 (search) was analyzed using a modified ELISA kit, while free Ang-2 was assessed using an ELISA developed at Boehringer Ingelheim. Circulating angiogenic factors were analyzed using a multi-analyte profiling immunoassay. DCE-MRI data were analyzed using dedicated software to quantify microvascular parameters such as iAUC60 and Ktrans.
The PopPK/PD modeling incorporated interindividual variability (IIV) and interoccasion variability (IOV). Covariate screening identified factors such as gender, body weight, human serum albumin (HSA), estimated glomerular filtration rate (eGFR), and alkaline phosphatase (ALP) as potential predictors of PK parameters. Sensitivity analyses were conducted to address the challenges of measurements below the limit of quantification (BLQ) for free Ang-2 (search).
Simulation and Target Attainment
The PopPK/PD model was used to simulate PK and PD profiles and to determine the probability of achieving minimal inhibition levels of free Ang-2 (search) (90% and 95%) at trough concentrations. Simulations involved 1000 patients with covariate values sampled from the observed data. Treatment cycles of three weeks (q3w) were simulated with BI 836880 doses of 40, 120, 360, 500, or 720 mg. The probability of target attainment was calculated as a function of treatment cycle and dose.
Clinical Implications
The findings support the use of biomarker-driven PopPK/PD modeling to optimize drug dosing in oncology. By predicting the probability of target attainment with different doses, clinicians can potentially individualize treatment strategies to maximize efficacy while minimizing toxicity. This approach is particularly relevant for drugs like BI 836880, where target engagement and downstream effects can be quantified through biomarker measurements.