Eusoft, has had significant experience helping companies to migrate from on premises or web-based solutions to a fully cloud-based LIMS platform, claims Pasquale de Tullio, the firm’s international marketing manager. ‘We start all our LIMS projects with a thorough understanding of every requirement that the client has. This allows us to configure the system to their exact needs and demonstrate each benefit, which ultimately helps them to move into the cloud with our SaaS LIMS. In some instances it is the vendor who has to point out to clients that moving a software system such as a LIMS into the cloud has benefits above finance (cost savings), support and computing power, de Tullio adds. ‘Unlike on premises solutions that may have a lifespan of, say, five to seven years before the client decides to move to a new generation of software, cloud solutions are ideally suited to innovation in informatics. By implementing a SaaS solution, clients can be ready to adopt innovation, and help to inform the direction of new developments.’ Headquartered in Italy, and with a UK office, Eusoft released the first version of a re-engineered, cloud-based LIMS solution, EuSoft.Lab 10, about three years ago, de Tullio explains. Developed as part of a restructuring programme that started in 2009, the SaaS platform is designed for clients in different industries, including food and beverage, oil and gas, environment, chemicals, and different manufacturing sectors. ‘We have also continued to address industry needs with the launch at the 2015 Paperless Lab Academy of a mobile app that allows users to upload results and track the progress of tests from a smartphone or tablet. This is not only important for remote, or field-based activities, but also aids collaboration and flexibility that cannot generally be achieved by using on-premises solutions.’
Adopting LIMS Innovation
News Feb 23, 2016
Artificial intelligence (AI) experts at the University of Massachusetts Amherst and the Baylor College of Medicine report that they have successfully addressed what they call a "major, long-standing obstacle to increasing AI capabilities" by drawing inspiration from a human brain memory mechanism known as "replay."