Teva to Acquire Gecko Health Innovations
News Oct 01, 2015
“Teva is committed to optimizing respiratory care through the development of new therapies and novel delivery systems to better serve patients living with respiratory conditions,” saidMichael Hayden, M.D., Ph.D., President of Global R&D and Chief Scientific Officer at Teva.
“The acquisition of Gecko Health Innovations further enhances Teva’s ability to develop and deliver truly patient-centered solutions by utilizing eConnected, data-driven technology to improve the management of respiratory diseases,” said Rob Koremans, M.D., President and CEO of Teva Global Specialty Medicines.
Through the agreement, Teva will acquire CareTRx™, a novel cloud-based solution developed by Gecko Health Innovations, designed to simplify chronic respiratory disease management, connecting patients and caregivers through remote monitoring and real-time adherence tools. Together with Gecko Health Innovations founders, Mark Maalouf and Dr. Yechiel Engelhard, Teva will explore innovative ways to apply the CareTRx technology to its robust pipeline and portfolio of respiratory products with the goal of enhancing clinical outcomes for patients. CareTRx is a solution comprised of a hardware device which attaches to most metered-dose inhalers (MDIs) as well as a software program which synchronizes and stores data through an app-based user interface.
“During the last three years, we have designed and built a system to support respiratory disease management by intuitively connecting caregivers, patients, and families,” said Dr.Yechiel Engelhard, CEO and Founder of Gecko Health Innovations. “In founding Gecko Health Innovations, our vision was to connect chronic medication management into one platform, leveraging this information to support and empower patients by partnering with leading players in the healthcare and pharmaceutical industries. We are very excited to realize this vision as it aligns to Teva’s focus on innovative patient solutions.”
Computer scientists at Carnegie Mellon University say neural networks and supervised machine learning techniques can efficiently characterize cells that have been studied using single cell RNA-sequencing (scRNA-seq). This finding could help researchers identify new cell subtypes and differentiate between healthy and diseased cells.