From the moment your LIMS goes live, the data that drives your lab is in one convenient location. But what happens to the records from your old system? LabLynx data migration services turn your legacy data into an accessible resource. Part of the LabLynx services suite, our data migration processes streamline the transition to your new LIMS and optimize your lab’s efficiency. This value makes LabLynx data migration services a common choice by our clients. [Read More]

Biobanking is the process of collecting, storing, managing, and sharing biological samples  along with associated data  for use in research and clinical care. At first glance, biobanking could seem simple enough to handle with an Excel spreadsheet. However, managing and accurately tracking these samples and their data can be challenging. In this blog, we’ll explore how a Laboratory Information Management System (LIMS) specifically tailored for biobanking can help overcome these challenges, paving the way to success for your biobanking facility. [Read More]

L7|HUB, a cutting-edge app is designed to revolutionize scientific collaboration in the biotechnology sector. Gone are the days of cumbersome paper-based processes and inefficient communication channels. L7|HUB empowers scientists to collaborate and share Digital Scientific Content (DSC) effortlessly. With L7|HUB and DSC, scientists can digitalize their operations faster and more seamlessly, paving the way for groundbreaking discoveries and advancements. [Read More]

Moving from paper or Excel-based data to a Laboratory Information Management System (LIMS) is a significant step towards enhancing efficiency, accuracy, and productivity in laboratories. However, it’s essential to consider several key factors to succeed in the transition. In this blog post, we will explore the five key factors that contribute to a successful implementation when moving from paper or Excel to a LIMS. [Read More]

An Electronic Lab Notebook (ELN) serves as a digital replacement for traditional paper laboratory notebooks, specifically designed to streamline the documentation of research, experiments, and procedures in scientific and engineering labs. In the ever-evolving landscape of laboratory management, the selection and implementation of an electronic lab notebook (ELN) solution in 2023 present exciting opportunities and potential challenges. This blog delves into the frequently asked questions you would need to go over before selecting the ELN solution that is right for your lab. [Read More]

While the Environmental Protection Agency (EPA) regulates outdoor air quality by limiting pollutants from sources like chemical plants, utility companies, and manufacturers, the EPA does not regulate indoor air. Some of the most dangerous contaminants and health hazards may be currently polluting your own home due to certain household products you use every day, the materials used to build your home, and even the appliances you use to cook your family’s dinner. [Read More]

The relationship between data is extremely important to understand and effectively turn this data into information to help with business decisions. Even though large amounts of data are being stored this doesn’t seem to be enough, it isn’t until people can see those data points and how they correlate to other data points that it becomes of value. [Read More]

In this 2023 article published in the journal Journal of Cannabis Research, Chambers et al. of State University of New York present an analytical method for "the analysis and differentiation of C. sativa plant materials" that, on paper, represent a major boost over more traditional chromatographic methods. After providing some background on those traditional types of analyses, the authors then present their method of using direct analysis in real time high-resolution mass spectrometry (DART-HRMS) with advanced chemometrics, including results associated with use of their method in a controlled laboratory environment. After some discussion, the authors conclude that their developed method "was successfully used to create a prediction model that facilitated rapid high-accuracy differentiation of C. sativa hemp and marijuana plant materials obtained from multiple sources (i.e., commercial, DEA-registered, recreational)," while also noting that "100% accuracy in prediction was observed," making it an important potential future method "for the optimal differentiation of hemp and marijuana."