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PurposeA novel single-dose regimen of 300 mg tremelimumab in combination with durvalumab [Single Tremelimumab Regular Interval Durvalumab (STRIDE)] has demonstrated a favorable benefit-risk profile in the phase I/II Study 22 (NCT02519348) and phase III HIMALAYA study (NCT03298451). This study evaluated the pharmacokinetics, exposure-response, and exposure-pharmacodynamics relationships of tremelimumab in patients with unresectable hepatocellular carcinoma (uHCC).Patients and methodsA previous tremelimumab population pharmacokinetic model was validated using data from parts 2 and 3 of Study 22. Exposure-response analyses explored relationships of tremelimumab exposure with efficacy and safety. Pharmacokinetics and pharmacodynamics relationships were evaluated using linear and nonlinear regression models.ResultsThe observed pharmacokinetics of tremelimumab in uHCC were consistent with predictions; no significant covariates were identified. Tremelimumab exposure was not significantly associated with adverse events, objective response rate, or progression-free survival. Overall survival (OS) was longer for patients with tremelimumab exposure, minimum serum drug concentration (Cmin1) ≥ median versus Cmin1 < median (18.99 months vs. 10.97 months), but this exposure-survival analysis might be confounded with baseline characteristics of albumin level and neutrophil to lymphocyte ratio, which had a significant impact on OS (P = 0.0004 and 0.0001, respectively). The predicted Cmin1 of tremelimumab in STRIDE regimen (12.9 μg/mL) was greater than the estimated concentration of tremelimumab eliciting half-maximal increases (EC50 = 5.24 μg/mL) in CD8+Ki67+ T-cell counts.ConclusionsOur findings support novel insights into tremelimumab pharmacokinetics and exposure-response relationships in HCC and support the clinical utility of the STRIDE regimen in patients with uHCC.

In this study, we developed a method for coordinating and optimizing the train connection plans of different lines under the conditions of urban rail transit (URT) network operation. The method allows trains of different lines to form good connections at transfer stations, which can shorten the waiting time of passengers for transfers and reduce passenger retention. A mathematical model was developed to simulate the interaction between passengers and trains. Two optimization models were developed for the train connection plan of network transfer stations based on different optimization objectives during peak and off-peak hours. Subsequently, a corresponding solution method based on a genetic algorithm and simulation was designed. Finally, the Suzhou URT network was used as a case study, and the passenger flow of the transfer station was simulated and calculated using relevant automatic fare collection (AFC) data. The results indicated that the average waiting time and the number of passengers stranded were reduced using the proposed method. The calculation example demonstrated the effectiveness of the model and algorithm, which can guide the coordinated preparation of a network train connection plan., Author(s): Ruihua Xu [1]; Xuyang Song [1]; Feng Zhou [1]; Fangsheng Wang (corresponding author) [1] 1. Introduction With the development of the urban rail transit (URT) network, the number of [...]

Aims: Tremelimumab, a cytotoxic T‐lymphocyte‐associated protein 4 human monoclonal antibody of the immunoglobulin G2 κ isotype, has been studied in oncology clinical trials as both monotherapy and in combination with durvalumab. This study characterized the pharmacokinetics of tremelimumab as monotherapy and in combination with durvalumab and evaluated the impact of patient covariates on pharmacokinetics. Methods: A pooled‐analysis population pharmacokinetics model was built using NONMEM methodology. Pharmacokinetic data from 5 studies spanning different tumour types and therapy regimens were pooled for model development (956 patients). A dataset pooled from 4 additional studies was used for external validation (554 patients). Demographic and relevant clinical covariates were explored during model development. Results: Tremelimumab exhibited linear pharmacokinetics, well described by a 2‐compartment model, with time‐varying clearance (0.276 L/day at baseline) associated primarily with therapy regimen and linked with changes in disease status. As monotherapy and combination therapy, tremelimumab clearance over 1 year increased by ~16% and decreased by ~17%, respectively. Pharmacokinetic behaviour was consistent across patient demographics and cancer subtypes. Patients with higher bodyweight and lower albumin levels at baseline had significantly higher clearance; however, no dosage adjustments are warranted. A flat dose (75 mg) was projected to provide comparable exposure to weight‐based dosing (1 mg/kg) in adults. Conclusion: Tremelimumab exhibited linear pharmacokinetics but consistently opposite trends of time‐varying clearance as monotherapy and in combination with durvalumab. Baseline bodyweight and albumin were significant covariates, but conversion from weight‐based dosing at 1 mg/kg to flat dosing at 75 mg had no clinically relevant impact. [ABSTRACT FROM AUTHOR]