Phesi adds country selection to trial site platform

By Jenni Spinner

- Last updated on GMT

(Who_I_am/iStock via Getty Images Plus)
(Who_I_am/iStock via Getty Images Plus)
The company’s AI-powered Clinsite investigator site intelligence platform now offers country selection, designed to help streamline trial efficiency.

Clinical development technology firm Phesi has added country selection functionality to its ClinSite investigator site intelligence platform. According to the company, the capability was added to help clinical research teams avoid the problems associated with including non-performing sites and countries in their trials.

Phesi reports that in an analysis of global trials, an average of 31% of participating countries failed to contribute patients adequately. Gen Li, Phesi founder and president, told Outsourcing-Pharma that the analysis showed non-performing sites and countries are a leading cause of trial delays and extraneous costs.

An analysis of more than 3,000 trials shows that, on average, each trial has four under-performing countries, costing up to $2.4 million per trial. Without access to real-time data from live trials, it’s almost impossible to gauge the performance of a country or individual site, which is why non-performing sites are often erroneously chosen when using traditional planning methods​,” he said.

Those conventional methods, Li explained, often rely on outdated information and techniques in the selection process.

Traditionally, a trial team would use limited historical data and previous experience (often this can just be ‘gut feel’) to decide which countries to bring their clinical trials to​,” he said. “An experienced investigator with a track record of enrollment performance in the indication under study (including biomarkers, comparator, etc.), and with limited competition at site from other trials is what sponsors are looking for, but because their decisions are based on insufficient data and insight, they later find out that the country does not have access to the right patient population​.”

Another common problem, Li told OSP, is thinking a high number of experienced sites automatically leads to satisfactory recruitment results.

This does not guarantee the country will deliver patients​,” Li told us. “This could have been caused by competition; for instance, competition for patients in cancer trials in the US is very high.​”

We therefore need better methods of analyzing data to make sense of it. No longer can manual data processing or previous good experiences be relied on alone; sponsors need data-driven decision making​,” he added.

Li explained that ClinSite’s artificial-intelligence (AI) powered platform enables sites to avoid such challenges by enabling more effective site selection and management.

ClinSite collects and analyzes live data from 4.2 million physicians and 600,000 investigators, from over 80,000 sources in over 200 countries and territories across all therapeutic areas​,” Li explained. “It cleans and structures all of these data points so users can easily filter and see which countries will provide the patients required for their clinical trial and which sites are most successful from a site activation, enrolment and data quality perspective​.”

Li also told us that effective country selection is especially important with the COVID-19 pandemic impacting clinical trials worldwide.

Failure to take a data-driven approach and establish which countries have the most high-performing investigator sites for their indication will continue to waste resources and delay treatments reaching patients​,” he said. “Compounding this, live data is essential as the pandemic moves in waves and affects different locations at different times, necessitating lockdowns or travel restrictions which must be taken into account during a clinical trial​.”

Related news

Show more

Related products

show more

Saama accelerates data review processes

Saama accelerates data review processes

Content provided by Saama | 25-Mar-2024 | Infographic

In this new infographic, learn how Saama accelerates data review processes. Only Saama has AI/ML models trained for life sciences on over 300 million data...

More Data, More Insights, More Progress

More Data, More Insights, More Progress

Content provided by Saama | 04-Mar-2024 | Case Study

The sponsor’s clinical development team needed a flexible solution to quickly visualize patient and site data in a single location

Using Define-XML to build more efficient studies

Using Define-XML to build more efficient studies

Content provided by Formedix | 14-Nov-2023 | White Paper

It is commonly thought that Define-XML is simply a dataset descriptor: a way to document what datasets look like, including the names and labels of datasets...

Related suppliers

Follow us

Products

View more

Webinars