The pharmaceutical industry has gradually evolved to recognize the value of leveraging external real-world data and improving internal clinical data management processes, which is not surprising given the ever-increasing pressure to fast-track development and achieve new levels of efficiency in today’s complex landscape.
Many challenges can be found in the industry, ranging from viability to monitoring and reporting, and there are many ways to manage the countless data being collected, combined and applied with the help of informatics.
Using analytical capabilities that impact decision-making can be very helpful to advance clinical trial execution.
Evaluating viability and site selection
Precise estimating and benchmarking helps to quantify the speed of patient enrollment and to understand the impact of the enrollment criteria for sponsors. Sponsors often rely on past literature or legacy protocols in order to determine primary efficacy parameters and estimate the number of patients required.
Sponsors have been expanding their information sources, taking advantage of collected data sources, such as the global clinical trials processed through a central laboratory repository. They can evaluate the current competitive landscape, estimate relevant patient populations, identify ideal site locations and assess the impact of suitability criteria on recruitment and retention.
There are some leads that you need to keep in mind: it is crucial to identify problems, actively manage risk and intervene before issues can affect progress, but disparate data collection systems must work together to enable this full view. There needs to be a way to unite multiple platforms through one robust clinical trial management system that collects, validates, consolidates and integrates clinical trial data, allowing critical trial operational elements to come together.
Classifying and modifying trial risks
Sponsors need to adapt themselves to the quality-design and quality-risk management methodology in clinical trials, but many are still hesitant on how to transition to a risk-based monitoring approach.
Technology-based functions like medical review, data review and statistical monitoring allow sponsors to receive a broader, more flexible view of clinical data and quickly pinpoint risk. Informatics integrated with a risk-based management can enhance patient safety and data quality.