Novel Study Designs in Precision Medicine - Basket, Umbrella and Platform Trials.

The concept of 'one size fits all' - one treatment for patients with a particular disease, seems to be outdated. The advent of precision medicine has prompted profound changes in clinical research and it allows researchers to predict more accurately, the prevention and treatment strategies for a specific disease population. Novel study designs are, therefore, essential to establish safe and effective personalized medicine. Basket, umbrella and platform trial designs (collectively referred to as master protocols) are biomarker enrichment designs that allow for testing more than one hypotheses within a protocol, thus accelerating drug development. These trial designs tailor intervention strategies based on patient's risk factor(s) that can help predict whether they will respond to a specific treatment. Basket trials evaluate therapy for various diseases that share a common molecular alteration, while umbrella trials evaluate multiple targeted therapies for a single disease that is stratified into subgroups based on different molecular alterations/ risk factors. These designs are complex and their major limitations stem from the fact that it would be inappropriate to completely replace histological typing with molecular profiling alone. However, in the upcoming decades, these trial designs are likely to gain popularity and improve the efficiency of clinical research. This article briefly overviews the characteristics of master protocol designs with examples of completed and ongoing clinical trials utilizing these study designs.

Factors influencing recruitment and retention of participants in clinical studies conducted at a tertiary referral center: A five-year audit.

INTRODUCTION: A key determinant of the success of any study is the recruitment and subsequent retention of participants. Screen failure and dropouts impact both the scientific validity and financial viability of any study. We carried out this audit with the objective of evaluating the recruitment and retention of participants in clinical studies conducted over the last five years at our center. METHODS: Studies completed between 2014 and 2018 at our center were included. Screening ledgers and study trackers were hand searched for screen failures and dropouts. Four pre-identified predictors were evaluated - risk as per the classification of Indian Council of Medical Research 2017 Ethical Guideline, nature of funding, study design, and nature of participants. Association of the predictors with screen failures and dropouts was determined using crude odds ratios along with 95% confidence intervals. All analyses were done at 5% significance using Microsoft Excel 2016. RESULTS: A total of n = 19 completed studies had n = 2567 screened and n = 2442 enrolled participants with a screen failure and dropout rate of 5% and 4%, respectively. We found 59% screen failures due to abnormal laboratory values. The main reasons for dropouts were lost to follow-up 86 (88%). High-risk and interventional studies were the predictors for both screen failures and dropouts, but pharmaceutical industry-funded studies and healthy participants were predictors for only screen failures. CONCLUSION: Risk, funding, study design, and nature of participants are important to be considered while planning studies to minimize screen failures and dropouts.