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To make clinical trials faster, less costly and more successful, Biopharmaceutical companies are moving from fixed to flexible study designs.
A recent report, the largest ever study of clinical development success rates, analyzed 9,985 clinical and regulatory phase transitions, across 1,103 companies and concluded that of the 14 major disease areas Oncology had the lowest likelihood of approval (LOA) with just 5.1%.
New adaptive methodologies are far more flexible than traditional designs as they allow trialists to monitor the flow of information and adjust the trial without undermining the integrity and validity of the trial.
It is said that the negative impact of high uncertainty at design stage for a confirmatory trial can be mitigated by an sample size re-estimation design.
A sample size re-estimation (SSR) design is a flexible, adaptive design with the primary purpose of allowing sample size of a study to be reassessed in the mid-course of the study to ensure adequate power. Statistical analysis plans for adaptive trials should cover interim analyses to optimise efficiency with the final analyses and to draw final conclusions about the observed treatment differences.
An interim sample size reassessment aims to ensure sufficient power, adaptation of the allocation ratio to ensure more patients receive the superior treatment, dropping of inferior treatments, addition of new treatment arms to save time and resources, population “enrichment” to narrow scope of the clinical trial, or transition directly from one trial phase to another.
Source BMJ: Key design considerations for adaptive clinical trials: a primer for clinicians
A recent paper featured in Applied Clinical Trials recommends the following three steps for advancing oncology drug development:
It is accepted that a very low number of drugs in development will be successful in demonstrating efficacy - so earlier information and better-focused evaluation are critical to improving success rates. This is where sample size re-estimation can help.
- New nQuery Adaptive Function - Arriving May 2019 -
Led by customer demand and the need to overcome the difficulties oncology trials face, the May 2019 release of nQuery Advanced (version 8.4) will include a new section dedicated to unblinded sample size re-estimation with interim monitoring for survival analysis.
So what does this mean for Biostatisticans? With this addition to nQuery, Biostatisticians can easily conduct sample size re-estimation for survival analysis, using a nQuery - the highly trusted and validated sample size platform. Using the familiar and easy to use spreadsheet interface, researchers can now quickly improve their research capabilities.
From mid May 2019, nQuery customers on the Pro Package can simply update their software to unlock this new function.
If you are not on the Pro Package of nQuery, there are great pre release discounts.
You must register your interest before the launch date, so for the greatest savings submit your details now.