PK Modeling of L-4-Boronophenylalanine and Development of Bayesian Predictive Platform for L-4-Boronophenylalanine PKs for Boron Neutron Capture Therapy.

L-4-[(10B)]Boronophenylalanine (BPA) is an amino acid analogue with a boron-10 moiety. It is most widely used as a boron carrier in boron neutron capture therapy. In this study, a Bayesian predictive platform of blood boron concentration based on a BPA pharmacokinetic (PK) model was developed. This platform is user-friendly and can predict the individual boron PK and optimal time window for boron neutron capture therapy in a simple way. The present study aimed to establish a PK model of L-4-boronophenylalanine and develop a Bayesian predictive platform for blood boron PKs for user-friendly estimation of boron concentration during neutron irradiation of neutron capture therapy. Whole blood boron concentrations from seven previous reports were graphically extracted and analyzed using the nonlinear mixed-effects modeling (NONMEM) approach. Model robustness was assessed using nonparametric bootstrap and visual predictive check approaches. The visual predictive check indicated that the final PK model is able to adequately predict observed concentrations. The Shiny package was used to input real-time blood boron concentration data, and during the following irradiation session blood boron was estimated with an acceptably short calculation time for the determination of irradiation time. Finally, a user-friendly Bayesian estimation platform for BPA PKs was developed to optimize individualized therapy for patients undergoing BNCT.

Pharmacokinetic and Pharmacodynamic Modeling Analysis of Delpazolid (LCB01-0371) in Adult Patients with Pulmonary Tuberculosis.

Delpazolid (LCB01-0371) is a novel oxazolidinone derivative with a good safety profile for treating gram-positive pathogenic infections such as Mycobacterium abscessus, a highly pathogenic drug-resistant Mycobacterium. In this study, we evaluated the pharmacokinetics (PK) and pharmacodynamics (PD) of delpazolid after 14 days of multiple oral administration, using data from adult patients with pulmonary tuberculosis. 800 mg once a day, 400 mg twice a day, 800 mg twice a day, and 1200 mg once a day delpazolid for 14 days were tested in 63 patients with pulmonary tuberculosis. For PK blood collection, inpatient and outpatient scheduling were separately implemented. Plasma concentrations of delpazolid were measured at visits 2, 4, 6, and 8 in outpatients, and four sparse blood samples were measured in inpatients. PD models were sequentially fitted using individual PK parameter estimates obtained from PK compartmental models. For PK modeling, 180 plasma concentrations of delpazolid from 56 patients were included. A two-compartment mixed first- and zero-order absorption model best described the time course of plasma concentration. For the PD model, 448 bacterial titer data from 60 patients were used. The time course of bacterial titers (log10 CFU/mL) was described by a model that consists of the growth and killing rate of bacteria with the sigmoid Emax model. The PK-PD simulation suggested that the bacterial titers are the lowest on the 800 mg bid regimen among the four, consistent with observed data, as all regimens substantially decrease. In the dose-response relationship, the effectiveness of delpazolid was suggested.

Safety and efficacy of selumetinib in pediatric and adult patients with neurofibromatosis type 1 and plexiform neurofibroma.

BACKGROUND: The MEK inhibitor, selumetinib, reduces plexiform neurofibroma (PN) in pediatric patients with neurofibromatosis type 1 (NF1). Its safety and efficacy in adults with PN and effectiveness in other NF1manifestations (e.g., neurocognitive function, growth reduction, and café-au-lait spots) are unknown. METHODS: This open-label, phase 2 trial enrolled 90 pediatric or adult NF1 patients with inoperable, symptomatic, or potentially morbid, measurable PN (≥ 3 cm). Selumetinib was administered at doses of 20 or 25 mg/m2 or 50 mg q 12 hrs for 2 years. Pharmacokinetics, PN volume, growth parameters, neurocognitive function, café-au-lait spots, and quality of life (QoL) were evaluated. RESULTS: Fifty-nine children and 30 adults (median age, 16 years; range, 3-47) received an average of 22±5 (4-26) cycles of selumetinib. Eighty-eight (98.9%) out of 89 per-protocol patients showed volume reduction in the target PN (median, 40.8%; 4.2%-92.2%), and 81 (91%) patients showed partial response (≥ 20% volume reduction). The response lasted until cycle 26. Scores of neurocognitive functions (verbal comprehension, perceptual reasoning, processing speed, and full-scale IQ) significantly improved in both pediatric and adult patients (P <0.05). Prepubertal patients showed increases in height score and growth velocity (P <0.05). Café-au-lait spot intensity decreased significantly (P <0.05). Improvements in QoL and pain scores were observed in both children and adults. All adverse events were CTCAE grade 1 or 2 and were successfully managed without drug discontinuation. CONCLUSION: Selumetinib decrease PN volume in the majority of pediatric and adult NF1 patients while also showing efficacy in non-malignant diverse NF1 manifestations.

Exposure-response analysis using time-to-event data for bevacizumab biosimilar SB8 and the reference bevacizumab.

Purpose: This analysis aimed to characterize the exposure-response relationship of bevacizumab in non-small-cell lung cancer (NSCLC) and evaluate the efficacy of SB8, a bevacizumab biosimilar, and Avastin®, the reference bevacizumab sourced from the European Union (EU), based on the exposure reported in a comparative phase III efficacy and safety study (EudraCT, 2015-004026-34; NCT02754882). Materials and methods: The overall survival (OS) and progression-free survival (PFS) data from 224 patients with steady-state trough concentrations (Css,trough) were analyzed. A parametric time-to-event (TTE) model was developed using NONMEM®, and the effects of treatments (SB8 and bevacizumab-EU) and patient demographic and clinical covariates on OS and PFS were evaluated. Simulations of median OS and PFS by bevacizumab Css,trough were conducted, and concentrations required to achieve 50% and 90% of the maximum median TTE were computed. Results: A log-logistics model with Css,trough best described the OS and PFS data. Treatment was not a predictor of the hazard for OS or PFS. Simulations revealed steep exposure-response curves with a phase of rapid rise before saturating to a plateau. The median Css,trough values of SB8 and bevacizumab-EU reported from the clinical study were on the plateaus of the exposure-response curves. The concentrations required to achieve 50% and 90% of the maximum effect were 82.4 and 92.2 µg/mL, respectively, for OS and 79.7 and 89.1 µg/mL, respectively, for PFS. Conclusion: Simulations based on the constructed TTE models for OS and PFS have well described the exposure-response relationship of bevacizumab in advanced NSCLC. The analysis demonstrated comparable efficacy between SB8 and bevacizumab-EU in terms of OS and PFS based on their exposure levels.