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With constant pipeline pressures intensifying the demand for speed and productivity in clinical trials, there is an impulse among trial leaders to dive right into data collection. But unless you take the time on the front-end to define and validate your testing methodologies and data collection processes, you can waste a lot of time and money while lessening the quality of your results. Without such validation, clinical trial teams risk collecting less valuable data, and creating inconsistencies in the data they do collect that at best requires added time and testing to clarify, and at worst leads researchers to the wrong conclusions. 

Establishing best practices and training investigators and staff on those best practices requires added time and expertise in the planning stage, but it leads to increased quality and efficiency across the lifecycle of the trial. 

We are currently demonstrating these benefits through our BIOSPIT initiative, a study to harmonize methodologies across dedicated centers for multicenter trials using induced sputum as a primary outcome measure for asthma and COPD studies. 

In an effort to develop personalized therapies for asthma and other respiratory illnesses, researchers want to identify biomarkers earlier in clinical trials. Yet, even though there are presently an estimated 300 compounds for these diseases in various stages of development, there is no standardized approach to gathering sputum biomarker readouts. 

We recognized that this lack of consistency and harmonization across trial sites would dilute the quality of data collected, so before beginning the trial, our team investigated the efficacy and outcomes of multiple collection techniques for our particular compound and disease group. Through this initial research, they identified best practice methodologies based on measuring and analyzing sputum, which can indicate differences in phenotypes that might suggest whether a patient will produce a change in a biomarker. Once they determined which methodologies were the best practice option for this study and validated the choices with key opinion leaders across the industry, they established standardized sputum processing techniques and created a best practice training program for staff across designated centers of excellence. 

By taking this time up front, the team has been able to harmonize sputum outcomes performance and data collection across all of multi-center trials of respiratory diseases. This standardization of best practices eliminates much of the variability that trial leaders often seen in data, and highlights the remaining discordance that suggests differences among patients – not collection techniques. 

This enables the team to capture more valuable data in a shorter time period with a modest number of patients as compared to trials that do not adhere to best practice strategies. As a result, we should be able to more accurately predict the compound’s safety and efficacy, as well as better determine which patients will respond to which treatments at what treatment quantities and intervals, all while cutting the time it takes to make a go/no-go decision on a respiratory therapy. 

Clinical trials are expensive and the risk of failure is high. Taking the steps up front to identify and solidify best practices for data collection and training staff to adhere to these practices will reduce your costs and risks, while increasing the odds that the decisions you make will be based on the best possible collection of data.