The clinical diagnostic lab is a unique environment for laboratory informatics. Not only does it have to meet the challenges of laboratory management and instrument communications, but it also has to do it while interacting with patients, physicians, insurance companies and administrative systems through standardized interfaces. LIMS provide a pivotal role in its operations, managing testing and distributing data as needed. [Read More]

Research and development in the pharmaceutical and biotechnology industries is fast paced and getting faster, while the pressure is on to decrease spending and improve time to market. As the research and development sector evolves, so do the requirements for robust systems that can manage large volumes of data, ensure fulfillment of regulatory requirements, and streamline operations. A laboratory information management system (LIMS) is an important tool in fulfilling those requirements. This blog post will look at some of the ways a LIMS can support your preclinical lab when properly configured. [Read More]

Therapeutic antibodies are a revolutionary drug class that can treat a wide range of diseases. Secondary screens characterize the functional properties of candidate antibodies, narrowing the pool to those most likely to succeed in clinical trials. The wide range of micro-plate based assays that can test hundreds of variables at once requires accurate and complex plate maps that capture a variety of plate re-array options. Using LIMSense™, a modern LIMS from AduroSys, can ensure you keep track of all of your samples and identify the best antibodies for further development. [Read More]

Companies continually seek innovative strategies to optimize operations in an increasingly competitive, cost-conscious life sciences industry. One such strategy gaining prominence is outsourcing. By enlisting the expertise of external partners, life science companies can focus on their core competencies, streamline operations, and significantly reduce costs. This article will explore five effective methods through which outsourcing can help life science companies reduce expenses. [Read More]

Autoscribe Informatics are highlighting key developments in its Laboratory Information Management System (LIMS) at the UK’s largest dedicated exhibition for laboratory professionals, Lab Innovations 2023. New or updated features on show will include an improved laboratory execution system (LES), a new subcontracting module, an improved audit reporting function, and federated single sign-on (SSO) functionality. [Read More]

Laboratory courses in public and private education support a strong pipeline of upcoming generations in the laboratory and scientific communities. Ultimately, laboratory environments allow students to take a hands-on approach to learning about the world around them, and those educational labs should be celebrated and enhanced to support upcoming generations in laboratory and scientific learning. [Read More]

In this LIMS case study, we delve into how Comvita faced the challenges of rapid growth and evolving regulations head-on. Let’s discover how QLIMS revolutionized their processes, making data-driven decisions a breeze and boosting productivity by 20%.[Read More]

As technological, cultural, and environmental shifts continue to put pressure on the ways academic and private research is conducted, researchers must further strive to get the most out of their work. This holds true across a broad swath of scientific fields, including materials science. Noting the continuing expansion of laboratory automation and software-based tools like artificial intelligence (AI) and machine learning (ML), Tamura et al. emphasize that materials science and novel materials research can benefit greatly from adopting these tools. In this 2023 paper, the authors present their take on this trend, in the form of NIMS-OS, a Python-based system developed to take advantage of completely automated material discovery experiments. After presenting an introduction on the topic, the authors discuss the development philosophy and approach to making NIMS-OS, while also describing use of both the Python command-line tool and the graphical user interface (GUI)-driven version of the software. The authors conclude that their system demonstrates how "various problems for automated materials exploration to be commonly performed," while at the same time being "designed to be easily adaptable to a variety of original robotic systems in materials science."