In the age of the “lab of the future,” companies are embarking on multi-year journeys of pursuing automation, connectivity, digital transformation, data standardization, and a plethora of other buzzwords. While these are all worthwhile endeavors, one of the first initiatives companies can focus on is connecting their lab to the cloud.
What does it mean to connect to the cloud?
A cloud-connected lab is a physical lab enhanced with Internet of Things (IoT) technologies that allow parts of the lab to go from edge to cloud. Going from edge to cloud means that edge or on-site devices such as instruments and sensors collect and process data sent to cloud-based servers (Microsoft Azure, AWS, Google Cloud) for storage, analysis, and visualization. Depending on the lab, the extent to which instruments, software, data, and people are connected to the cloud can vary. The more a lab is cloud-connected, the more contextualized data you can capture, analyze, and store.
Why should I connect to the cloud?
Cloud connectivity leads to several benefits related to operating and managing your labs. Specifically, you can leverage:
- Complete data collection: Data generated by hardware, software, and people can be automatically captured and stored in real-time without being limited by local storage constraints
- Remote monitoring: Data collected at the edge that is sent to cloud-based servers can be accessed by users in real-time from anywhere an internet connection
- Remote control of your operations: By connecting to the cloud, users can react in real time to their lab by scheduling jobs or modifying in-flight runs remotely.
In addition, connecting to the cloud enables companies to leverage the significant advantages of computing power, deployment flexibility, and enhanced security infrastructure.
So, do I need a cloud lab?
Labs today can start leveraging the power of the cloud by using “cloud labs,” becoming a “cloud-connected lab,” or even a combination of both. While “cloud lab” and “cloud-connected labs” are often used interchangeably, key differences exist in how they are implemented.
A cloud lab is typically operated by an external vendor rather than in-house. In this case, scientific groups will ship their samples to this off-site lab for processing and analysis. As a result, these scientific teams do not own or maintain the instrumentation required for running their samples.
Outsourcing the operation and maintenance of a lab can be helpful for an early-stage company or scientific team with fewer team members and resources. However, companies that can invest in building their own physical labs or want to keep samples on-site can still bring their lab to the cloud. By bringing these capabilities in-house, groups can also achieve remote control of their lab, which is unlikely to be offered by cloud labs managing samples from multiple customers and labs.
How Artificial helps connect labs to the clouds
Building a cloud-connected lab can be daunting, even for the largest organizations, which is why Artificial has created the Artificial Suite. The Artificial Suite makes it easy for companies to turn their labs into cloud-connected, smart labs:
- A cloud-based platform: we’ve already built the infrastructure, so labs don’t have to. By using Artifical, they can immediately recognize the cloud's scalability, flexibility, and security.
- Vendor-agnostic: No matter how many different software or hardware systems a lab uses, Artificial can connect with it so that every part of the lab is connected to the cloud.
- Edge-to-cloud execution engine: Artificial is not just a visual dashboard; it provides an orchestration engine that executes workflows with the best resources available.
- Pre-built, intuitive UI: Artificial provides a single, human-centric UI that makes it easy for teams to monitor and operate all their labs in one place remotely.
If you’re ready to start taking the first step to make your lab smarter, request a demo today.
