Transformative digital strategies are needed for faster study startup, to harmonize data from any source, and to streamline workflows. All to give today’s life sciences stakeholders what they need—quicker results, with treatments reaching patients faster.
Learn what new clinical trial methods will continue in the post-COVID world.
The swift transition to virtual clinical trials during the Covid-19 pandemic demonstrated that eClinical solutions for collecting data and conducting visits can bring real benefits to clinical research studies and, ultimately, patients.
Direct-to-patient data collection devices and applications have created a much larger infrastructure of required integrations. This shift in clinical trial complexity demands better data collection methods, which current electronic data capture (EDC) technologies are not designed to support.
Due to pressure for faster, more efficient clinical trials, the life sciences industry is moving away from segmented technologies and complex workflows that extend trial timelines and increase costs, making way for more cross-functional and collaborative approaches.
The increased pace of decentralization due to the pandemic has proven to be of real value in remote data collection, as well as virtual patient engagement, and now the industry must establish standards and best practices to support these new approaches.
Research insights into how the pandemic changed clinical trial operations.
Natalie Gagliordi, Senior Writer, Oracle
The methods utilized during the pandemic are likely to have a lasting impact on the future of clinical trials, according to a new research study conducted by Informa Pharma Intelligence and Oracle.Read the complete post
Covance discusses how they’re driving the implementation of decentralized trials globally, and the core tenets they abide by when executing decentralized trials.
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Beyond EDC—don’t just capture data, collect it.
Virtual components in clinical trials, such as wearables and remote monitoring, allow greater patient participation and significantly improve clinical trial data quality.
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