Maximizing Quality and Efficiency of Go/No-Go Decisions in Early-phase Studies

Due to the size and scope of clinical trials in this therapeutic area, traditional early oncology development has evidenced high start-up costs and long durations to advance to the Phase II setting. While the website reveals that there are many products and programs in development, high costs, long timelines, and excessive failure rates result in relatively few investigational drugs progressing all the way to marketing approval. This is unfortunate for patients who may have benefited from pharmacotherapy earlier, and makes it challenging for biopharmaceutical companies to achieve a return on investment and hence to be in the financial position to continue with research and development (R&D) programs for other potential drug candidates.

The high attrition rate occurring between progression to clinical development and marketing approval suggests that initial candidate selection processes are not optimal. Given the high costs of development and the demands upon patients who participate in clinical trials, it is essential to select only those molecules from preclinical development programs that are truly worthy of advancing to Phase I clinical trials and likely to meet the criteria for success in later-phase trials. More focused and informed decision-making is therefore vital. Fortunately, advances in molecular biology and patient molecular profiling that may facilitate targeted therapy have ushered in new hope and enthusiasm for better clinical outcomes. Targeted therapy represents a transition from broader-acting cytotoxic agents with high toxicity levels toward agents with high specificity and hence therapeutic benefit for a well-defined group of patients with a particular molecular biological profile.

For such advances in clinical practice and outcomes to be maximized, it is important to better understand the biological consequence of treating a biological pathway of interest in the preclinical setting. Identifying candidate biomarkers for mechanism of action (MOA) and selection of patient to participate in a given clinical trial is of considerable importance, since drugs without a biomarker-based patient selection strategy are at a profound disadvantage. A vision of the future, therefore, would be for newly diagnosed patients to have a comprehensive molecular profile performed and then be matched to participate in the right trial based on that profile. Leveraging ‘intelligent biomarker selection’ of patients to participate in early phase clinical trials has potential to make more efficient go/no-go decisions on product candidates at the earliest possible stage.