News & Views
Merger brings together Experts in Trial Design
Oct 15 2020
Drug development solutions company Laiya Consulting, specialising in Bayesian adaptive trial designs and implementation, has been acquired by Cytel Inc. The deal follows the recent release of Cytel’s East Alloy platform for easy access to verified Bayesian tools aimed at broadening industry access to innovative clinical trial design methods.
"As we look to make the benefits of sophisticated Bayesian methods ever more accessible to drug developers, we’re taking strategic leaps to both bolster our core offerings and streamline their delivery to the market," said Yannis Jemiai, Chief Scientific Officer at Cytel. "The release of East Alloy was a tremendous milestone here — effectively removing the daunting computational barriers to more widespread, easy Bayesian method implementation. Partnering with Laiya allows us to smoothly feed into our broad Bayesian software capabilities with ever greater levels of statistical innovation and expertise. We look forward to welcoming Dr Yuan Ji and his colleagues to the team."
Founded in 2010, Laiya pioneered the delivery of trial design software using SaaS, which aligns with Cytel’s goal of making all its design software available as a cloud-based service. Laiya’s co-founder Dr Yuan Ji is a Fellow of the American Statistical Association and a global authority on Bayesian statistics, having invented multiple Bayesian trial designs and authored more than 150 papers and book chapters on the topic. He also jointly holds an appointment as Professor of Biostatistics at the University of Chicago.
"Bayesian approaches, when applied correctly, open an abundance of opportunity in clinical development, evidenced by our own and Cytel’s extensive work in this field," said Dr Yuan Ji, Co-founder of Laiya Consulting. "Merging with Cytel means unifying two rich sources of statistical proficiency to continue setting new standards for Bayesian design, which will ultimately help us to further enable drug developers to profitably solve the most intricate clinical challenges."
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