Datathon identifies potential new treatments for chronic pancreatitis

A datathon organised by information analytics business Elsevier and non-profit alliance The Pistoia Alliance has identified five drug candidates for repurposing to potentially treat chronic pancreatitis.

The datathon had organisations from life sciences, technology and academia, apply AI, machine learning and statistical techniques to solve problems in drug repurposing. Participants used Elsevier’s Entellect platform to identify suitable drugs to be repositioned to treat chronic pancreatitis – a rare disease affecting around 1 million patients globally, for which there is no treatment.

Participants used multiple techniques, including target-based drug discovery, examining the perturbance of a drug on a specific gene known to be disease-modifying and symptomatic-based drug discovery, i.e., examining the perturbance of a drug on the body.

“The results of the datathon show that by working in unison, we can achieve breakthroughs that will have a real impact on patients’ lives,” said Dr Steve Arlington, president, The Pistoia Alliance. “In life sciences today, no one company has the resources to ‘go it alone’. So the datathon was the perfect opportunity to bring all the relevant experts together and pool our knowledge and resources. The results are very promising, and we look forward to seeing these therapies reach those in need.”

The five drug candidates have passed an expert review panel and are now being considered to proceed to patient trials.

The datathon was conducted in partnership with non-profit groups Cures Within Reach and Mission: Cure.

“We are very excited about the discoveries made in the Elsevier Entellect/Pistoia Alliance datathon. The problem-solving and teamwork focused on chronic pancreatitis was very exciting. We look forward to taking the promising candidates to the next step where we hope they will help us find effective treatments for this difficult, rare disease,” said Megan Golden, co-founder and co-director, Mission: Cure.

“Within 30 to 60 days of starting the datathon, drug candidates with really good repurposing opportunities came out. In such a short space of time, a small group of people using AI were able to achieve incredible things by showing mechanism of action,” said Bruce Bloom, CEO, Cures Within Reach.

“The goal of the datathon was to identify drug candidates for repurposing by using predictive analytics techniques, and we also wanted to explore best practice in the use of data science,” said Dr Jabe Wilson, consulting director, Text and Data Analytics, Elsevier. “This was the first public trial for our Entellect platform and it’s been a great success on all fronts. I want to thank all our partners and participants for their time and commitment to achieving this positive outcome.”