At a time when we covet scientific innovation, organizations are also learning how to navigate our new normal. Achieving operational efficiencies in the laboratory is paramount for life sciences organizations to reach scientific milestones in a timely manner. That’s why the recent white paper from Scientific Computing World titled ‘Building a Smart Laboratory 2020’ is more relevant than ever before. We thought we’d highlight some of the key points that resonated with us from the paper.What is a smart laboratory? While there is no set definition for a smart laboratory, the general objectives of the smart laboratory are to deploy modern tools and technologies to improve the efficiency of the scientific method by providing seamless integration of systems, to create searchable repositories of data of proven integrity (that can be accessible remotely, which is highly valued in today’s world), and eliminate mindless and unproductive paper- based processes, all while complying with regulatory requirements. With that in mind, there are several ways for an organization to build a smart laboratory.
One simple approach is to turn so-called ‘dumb’ instruments into smart ones. Legacy instruments such as balances, pH meters, and centrifuges are utilized in common laboratory processes. However, the data they generate is captured in a lab notebook, captured locally on the instrument or not captured at all, creating a multitude of problems such as data silos, data transfer errors, data gaps, etc. Automating data capture from such instruments into an ELN or LIMS system alleviates these issues. Options for interfacing with ELN or LIMS include ethernet, or more recently, IoT (internet of things) technology, in the form of Raspberry Pi or Bluetooth devices that can seamlessly transfer data. Data accessibility through IoT also provides the added benefit of checking in on experiments during off hours. After all, scientific processes don’t always pause at the end of the day when you go home.
Any electronic data collected from lab instrumentation should support 21 CFR Part 11 compliance, especially for life science organizations. Practically, electronic data should also be easily accessible for regulatory audits. Having the ability to export relevant data portions into .csv or .pdf files allows for easy incorporation of files into reports, regulatory submissions, and other records.
Smart instrumentation is also the foundation of process automation in the laboratory. Detailed actions for sample preparation, sample introduction, and instrument processing can be automatically gathered and analyzed real-time to assess process validity, and in turn, respond with appropriate steps (eg. notifying scientists, aborting process, or repeating steps) should the process exhibit issues.
Source: Building a Smart Laboratory 2020 via Scientific Computing World
Additional infrastructure to achieve robust process automation in the laboratory is data integration. From start to finish, process data is gathered in a myriad of formats from various instrument sources. Automating responses to unique process scenarios requires being able to aggregate and make sense of data from one or multiple sources. This can be a time intensive process - imagine having to piece together process data again if you replace or add a piece of equipment to your process. Fortunately, there are organizations such as the Pistoia Alliance, Allotrope Foundation, and SiLA Rapid Integration that are working on establishing some guidelines and best practices for data reporting.
So what are some practical considerations when building out a smart laboratory? We share some top tips from industry experts:
- Mark Gonzales of Labware notes the desire to use mobile technology in the laboratory. We at Elemental Machines couldn’t agree more. Our Connected Lab Platform solution uses battery backed Gateway tablets to transport lab data onto our cloud-based platform. Additionally, users can receive SMS alerts on their phones when lab issues occur.
- Renaud Acker of Agilab states the need for user-friendly lab software. This is particularly important when managing big data that can be overwhelming on its own. Additionally, Renaud acknowledges the reservations many companies have when it comes to switching to new lab softwares due to the time- and cost-intensive efforts. Again, we at Elemental Machines agree with Renaud on both points. Our UX team has built an easy-to-navigate software to find the data you need when you need it. And our system is easy to setup and scale up. It only takes 60 seconds to start gathering data from your lab.
- Oscar Kox of iVention stresses the importance of upgradability of LIMS and ELN systems in particular. The Elemental Machines platform, which connects to several LIMS and ELN systems, is offered as a comprehensive service which routinely includes product updates and new features. Our cloud-based data is easily accessible through the use of RESTful API.
If you are interested in learning more about the Elemental Machines Connected Lab Platform, reach out to schedule a demo.