Laboratory Information Management Systems (LIMS) are crucial in managing data, workflow processes, and reporting in modern laboratories. While Excel is a widely used tool for managing data due to its accessibility and ease of use, databases provide a more robust, scalable, and secure solution for laboratories that require efficient data management. This article will explore the key reasons why a database is a better choice than Excel for managing a LIMS. [Read More]

The Australian branch of Autoscribe Informatics, Autoscribe Informatics Pty Ltd, is thrilled to announce it has moved to new offices in West Lakes Adelaide, to better service its growing customer base across the Asia Pacific region. The operation is headed by Jodie Poole Director, Asia Pacific for Autoscribe who has over 23 years’ experience in information technology and laboratory informatics. [Read More]

Implementing LIMS (Laboratory Information Management System) can be a game-changer, because there might be resistance and reluctance to the new routines which require significant adjustments. In this blog post, we will dive into implementing a LIMS to prevent the challenges beforehand.  The laboratory management plays an important role here to support and encourage this transition. [Read More]

Laboratories and industries everywhere are realizing that technological innovations are moving at a rapid and ever-increasing pace. These technological initiatives require organizational change management (OCM) to ensure success. Some of these initiatives include the following: Cloud-based computing, Data lakes, Generative artificial intelligence, and Software as a Service (SaaS) laboratory information management systems (LIMS) with regular releases using the Agile methodology. Is your company prepared to face the associated OCM challenges of technological innovations? [Read More]

Clinisys, a global provider of intelligent laboratory informatics solutions, announces the release of new offerings within the latest version of Clinisys Laboratory Solution™: Clinisys Food & Beverage Laboratory™ and Clinisys Contract Services Laboratory™. [Read More]

In a manufacturing lab, an advanced laboratory information management system (LIMS) offers immediate data processing for quick decision-making, streamlined sample management for easy tracking and identification, and automated workflows to reduce errors and boost efficiency. Additionally, quality control, efficient inventory management, and data security measures like user authentication and audit trails enhance the value of a LIMS, boosting lab productivity, ensuring regulatory compliance, and improving overall operational quality. [Read More]

Sapio Sciences, the science-aware^TM lab informatics platform, today announced the launch of its new multimodal registration capabilities. This new functionality unifies small-molecule, large-molecule, and multimodal discovery workflows, including entity registration, on a single platform. With these latest features, Sapio is helping R&D teams overcome the collaboration and efficiency challenges traditionally associated with the development of multimodal therapies and products. [Read More]

In this brief article in Journal of Privacy and Confidentiality, Jang et al. of Inter-university Consortium for Political and Social Research (ICPSR) at University of Michigan review the current approach of researchers towards restricted data management and how it may need to evolve given certain challenges. They offer this review in the scope of increasing demands for FAIR (findable, accessible, interoperable, and reusable) data in research and journal communities. After a brief introduction, the authors discuss three main elements of managing restricted date: data use agreements, disclose review, and training. While the Five Safes framework is effective under this scope, the authors concludes that such "safeguards could generate unintended challenges to certain groups of individuals (e.g., institutional approval that could exclude researchers without institutional affiliation) or in different areas (e.g., rigorous output checking that requires extensive insights from experts)." They add that organizations may need develop more thoughtful and standardized data management policies that still remain flexible under the scope of FAIR data.