What are the most important features in a modern laboratory information management system (LIMS)?

‍Blog Summary

Intelligent automation, also known as hyperautomation, is a strategy that combines different automation tools, like Robotic Process Automation (RPA) and Artificial Intelligence (AI), to create efficient workflows. While RPA handles repetitive, rules-based tasks, AI adds cognitive capabilities like machine learning and natural language processing to handle more complex activities. Low-code platforms are the key enablers of intelligent automation. They provide an easy-to-use layer that allows operational staff, rather than just technical experts, to quickly create, manage, and scale automations. This approach helps businesses increase process efficiency, reduce costs and risks, and ultimately allows employees to focus on higher-value, innovative work.‍

Key Questions Answered by the Article

What is intelligent automation and how is it different from AI or RPA alone?‍

Intelligent automation is a holistic approach that uses the right tool for the job. It combines the strengths of RPA for simple, repetitive tasks with the cognitive power of AI for more complex, data-driven decisions. Unlike AI's high cost and lengthy development or RPA's limited capabilities, intelligent automation provides a comprehensive solution for end-to-end workflow optimization.

What role does low-code play in the successful implementation of intelligent automation?‍

Low-code platforms act as the enabling layer for intelligent automation. They democratize the process by making it quick and inexpensive to create and manage automations. This allows operational staff, who have deep knowledge of business processes, to directly build solutions without needing to rely on a technical team. This ease of use is crucial for achieving value at scale.

What are the key benefits a business can achieve with intelligent automation?‍

By using intelligent automation, a business can achieve significant benefits. These include increasing process efficiencies, optimizing back-office operations, improving the overall user experience, and reducing costs. This approach ultimately leads to a leaner, more rapidly scaling company by freeing employees from tedious tasks so they can focus on more innovative and strategic pursuits.

Transform your business processes with intelligent automation, powered by low-code

A laboratory information management system (LIMS) is like the brains of the laboratory – it helps to keep everything running smoothly and efficiently. But just like our own brains, a LIMS needs to keep up with the times and be able to handle all the modern-day challenges that come its way.

Slingr Labs gives customers the power to connect and manage their data via automation, enable system modifications to meet the growing needs of modern laboratories, and ensures strong security with a gold-standard level of privacy, in an easier, and more affordable package. 

“In an industry as mission-critical as healthcare, you cannot afford for systems to fail when they’re needed most, and especially not because of the incompatibility of software to the modern world,” says Grace Schroeder, founder and CEO of Slingr. 

So what are the most important features in a modern LIMS? Here are a few to consider:

1. A robust sample management system. This includes the ability to track samples from the moment they are received in the lab until they are disposed of or archived. It should also be able to manage sample processing, including the creation of sample chains of custody, assigning samples to specific users or instruments, and recording the results of any tests or analyses.

2. The ability to handle a wide range of data types and formats from multiple instruments and devices. This includes everything from traditional numeric data to images, spectra, and other complex data types. The LIMS should also be able to handle data from a variety of instruments and devices, including chromatographs, mass spectrometers, and microscopes. It should also be able to integrate with other systems, such as electronic lab notebooks or enterprise resource planning (ERP) systems, to ensure that all relevant data is captured and managed.

3. Regulatory compliance. This includes the ability to generate reports and documents that meet the requirements of regulatory agencies, as well as the ability to track and manage user training, certifications, and approvals. It should also have features that help to ensure data integrity, such as data validation checks, audit trails, and electronic signatures.

4. Workflow and process management. This includes the ability to create and manage protocols and standard operating procedures (SOPs), as well as the ability to track and manage the progress of different projects and tasks. It should also have features that help to streamline communication and collaboration, such as document sharing, task assignments, and real-time notifications.

And that's not all – modern LIMS can also offer custom reporting, data analysis and visualization, and integration with other systems and tools. Some even have advanced features like machine learning or AI to take things to the next level.

So if you're running potency tests on the latest cannabis product or trying to keep up with the ever-changing landscape of Covid testing, don't let your lab fall behind. Let Slingr Labs help you streamline your testing processes from start to finish with their low-code LIMS solution. 

To find out more about how Slingr Labs can bring you up to speed, contact us here.