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 ..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 ..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 ..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 ..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 ..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 ..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 ..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 ..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 ..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 ..read more