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Supplementary Figure S1; Supplementary Appendix.

Purpose: This dose-escalation study evaluated the safety, tolerability, and pharmacokinetics (PK) of the oral Src inhibitor saracatinib (AZD0530) in patients with advanced solid malignancies. Tumor biopsy samples were taken to investigate the effect of saracatinib on Src activity in tumors.Experimental Design: Part A of the study followed a multiple-ascending dose design to establish the maximum tolerated dose (MTD) of saracatinib. Part B was a randomized, parallel-group, cohort-expansion phase to further assess tolerated doses. Safety, tolerability, and Src activity (immunohistochemistry and lysate-based methodologies) were assessed after 21 days of once-daily oral dosing. PK was assessed after single and multiple dosing.Results: In part A, 30 patients received once-daily saracatinib at doses of 60 to 250 mg; the MTD was established as 175 mg. In part B, 51 patients were randomized to receive 50 mg (n = 16), 125 mg (n = 16), or 175 mg (n = 19) of saracatinib. The most common grade ≥3 events considered to be treatment related were anemia, diarrhea, and asthenia. Tumor Src activity was reduced following saracatinib treatment. The area under the concentration-time curve and Cmax of saracatinib increased with increasing dose. Saracatinib accumulated 4- to 5-fold on once-daily dosing to reach steady-state exposure after 10 to 17 days of dosing. The half-life was ∼40 hours.Conclusions: Saracatinib was well tolerated in patients with advanced solid malignancies. A reduction in tumor Src activity was observed. PK data show that saracatinib is suitable for once-daily oral dosing. Based on this study, the recommended dose for the phase II studies was chosen to be 175 mg/d. Clin Cancer Res; 16(19); 4876–83. ©2010 AACR.

We assessed the impact of the coronavirus disease 2019 (COVID-19) pandemic on the statistical analysis of time-to-event outcomes in late-phase oncology trials. Using a simulated case study that mimics a Phase III ongoing trial during the pandemic, we evaluated the impact of COVID-19-related deaths, time off-treatment and missed clinical visits due to the pandemic, on overall survival and/or progression-free survival in terms of test size (also referred to as Type 1 error rate or alpha level), power, and hazard ratio (HR) estimates. We found that COVID-19-related deaths would impact both size and power, and lead to biased HR estimates; the impact would be more severe if there was an imbalance in COVID-19-related deaths between the study arms. Approaches censoring COVID-19-related deaths may mitigate the impact on power and HR estimation, especially if study data cut-off was extended to recover censoring-related event loss. The impact of COVID-19-related time off-treatment would be modest for power, and moderate for size and HR estimation. Different rules of censoring cancer progression times result in a slight difference in the power for the analysis of progression-free survival. The simulations provided valuable information for determining whether clinical-trial modifications should be required for ongoing trials during the COVID-19 pandemic.

Clinical development is the scientific process of exploring and confirming the product attributes and therapeutic role of potential new medical treatments. This chapter provides an overview of the clinical development of a pharmaceutical product for medical use, introducing and discussing the principles of clinical development and application of those principles on both a programmatic and a study level. While the development process is continuous, beginning during the discovery of an innovative potential pharmaceutical product and ending with the replacement of the innovative pharmaceutical by a more effective or safer alternative treatment, the process follows an orderly path of evidence-based, goal-directed development. This chapter focuses on the clinical development and registration of an innovative pharmaceutical product in the treatment of patients or of an additional indication for an existing pharmaceutical product.

Background In clinical trials that assess novel therapeutic agents in patients with non-small-cell lung cancer (NSCLC), early endpoints (e.g. progression-free survival [PFS] and objective response rate) are often evaluated as indicators of biological drug activity, and are used as surrogate endpoints for overall survival (OS). Compiling trial-level data could help to develop a predictive framework to ascertain correlation trends between treatment effects for early (e.g. odds ratio [OR] for PFS at 6 months) and late endpoints (e.g. hazard ratio [HR] OS). Methods A dataset was compiled, which included 81 randomized, controlled trials (RCTs; Phase II–IV) of NSCLC (Stages I–IV), with 35 drugs and 156 observations. The dataset was collected from multiple source databases, including Citeline, TrialTrove, clinicaltrials.gov, and PubMed. We applied random-effects meta-analysis to correlate a variety of treatment effects for early endpoints with HR OS. We performed meta-regression analyses across different data-strata, stratified by the mechanism of action (MoA) of the investigational product (programmed death protein-1/programmed death-ligand 1 [PD-1/PD-L1], epidermal growth factor receptor [EGFR], vascular endothelial growth factor receptor, and DNA damage response). Results Low (Spearman’s rho 0.3– 1, indicate benefit with the investigational product. Conclusions Using a comprehensive summary data set in the NSCLC space, we observed low-to-moderate correlations between treatment effects for early endpoints and HR OS across RCTs of agents with different MoAs, including trials of PD-1/PD-L1 checkpoint inhibitors. Exploration of additional endpoints, beyond RECIST, is required to identify other early indicators of efficacy that might predict HR OS. By incorporating additional trial-level parameters and building composite biomarkers using machine intelligence methods, in collaboration with innovative trial design efforts, we envisage to improve the prediction of HR OS from early endpoints.

We would like to thank the authors of the letter (Bartlett et al. 2020) for sharing their concerns regarding reporting treatment effect under nonproportional hazards (NPH), and we respect their pos...