Decoupling data inputs from their isolated sources continues to be challenging for organizations. Data silos not only hinder organizational collaboration and decision making but also undermine an organization’s ability to unlock the potential of its most precious resource—its data. Advancements like cloud computing, platforms, and blockchain are giving most organizations the tools to transition away from traditional, physical data silos. However, are these tools and transitions truly eliminating data silos, or are they simply ushering in a new paradigm for maintaining them? What Are Data ..read more

Depending on how long you have been working in the lab informatics industry, you may have noticed that the list of acronyms feels almost endless. Since this blog was first written more than 10 years ago, that list of acronyms has only grown. This blog post updates the original list to provide insight into an expanded list of the most common acronyms.  Our original post provided overviews of LIMS, ELN, and LES. Now, we will look at the additional acronyms of CDS, ERP, LLM, MES, QMS, SaaS or PaaS, and SDMS—all of which are informatics systems that are just as important for informatics prof ..read more

Artificial intelligence (AI) is a term we see and hear a lot nowadays; you could say it’s trending and becoming a household term. It is associated with the things surrounding us daily: home electronics, cars, public transportation, shopping, and more. This term is inclusive and encompasses intelligent products designed to make our lives easier and use computational power to reduce analysis time and effort.  Has this trend reached the benches of the general research and development (R&D) lab yet? Can AI make the lives of R&D lab analysts easier? Well, yes, but not in all aspects o ..read more

Businesses in the life sciences sector are navigating complex decisions regarding their laboratory data management. They face demands for data accuracy, compliance, and integrity that drive decisions about data platform use. A platform serves as a bespoke hub for data regardless of which or how many data sources are involved. Your platform choice can be a game changer for accessibility, flexibility, and data management as the life sciences industry adapts to technological advancements. Let’s explore the differences between the types of platforms (industry-specific or enterprise) and the influ ..read more

The FDA’s Case for Quality initiative seeks to shift the focus from validation as a check-the-box regulatory activity to one that centers around quality. The shift will ensure that patients and end users have access to safe, effective care. Recognizing that innovation drives continuous improvement, which, in turn, leads to higher quality and efficiencies in products and healthcare; the FDA issued the Computer Software Assurance (CSA) draft guidance in September 2022 to make validation of regulated systems less burdensome and more strategic. It is important to note that as ..read more

There are a number of features of artificial intelligence (AI) that make it well suited for use in software validation. Some of these features are its capacity for pattern recognition and the ability to learn and adapt continuously. An emerging use for AI is in laboratory information management system (LIMS) validation. A LIMS is instrumental in laboratory data management. In recognition of the need for enhanced efficiency and accuracy, AI is increasingly integrated with the data in LIMS and has become a game changer. Validation teams can potentially leverage AI access to LIMS data to streaml ..read more

The goal of a manufacturing department is to get the product out the door on time and within specifications. With large batches of products being produced, some sort of quality management system (QMS) is needed to ensure the best and most compliant product is delivered to consumers. A QMS may start out as a paper-based system and slowly transition to a spreadsheet, but without a fully automated and validated system, manufacturers risk security and compliance issues. So—having a quality management system sounds great, right? It should be a no-brainer to have the QMS validated, right? But you m ..read more

Every industry has embraced the idea that digital technologies need to be fully integrated in the business processes to ensure successful competition. In the era of Industry 4.0, your organization’s data (digital assets) are now recognized as your most valuable assets. Within the life sciences, however, there are many constraints of the scientific operating environment, such as regulatory oversight, evolving digital technologies, the data integrity demanded by decision makers and regulators, and the remaining legacy technologies. All of these constraints, and more, have made it difficult for ..read more

In today’s corporate landscape, Learning Management Systems (LMS) play a pivotal role in delivering, tracking, and managing training programs. The LMS supports an organization’s overall regulatory compliance by tracking the needed certifications of all employees and ensuring that records are centralized. Ensuring the dependability, security, accessibility, and adherence to regulations of an LMS is crucial for regulated businesses, and shouldn’t be neglected by any business that requires continuing education of employees. This blog post explores the significance of validating LMS software, giv ..read more

Good manufacturing practices are the underpinning of every life sciences business. At the heart of the organization, ensuring end user safety is everyone’s goal. In many organizations, the quality management system (QMS), learning management system (LMS), and manufacturing execution system (MES) work together in service of this goal. This blog describes the essential functions of these systems, why they should be validated, and how they can be configured to ensure seamless data flow across your life sciences organization. ▶ Read More: Thinking Comprehensively About Your Data A Brief Overview ..read more