Education – Laboratory Systems Engineering

Guide for Management: Successfully Applying Laboratory Systems to Your Organization’s Work

Laboratory informatics involves a collection of technologies that range from sample storage management and robotics to database/workflow management systems such as laboratory information management systems (LIMS) and electronic laboratory notebooks (ELN), with a lot of task-specific tools in between. These components were designed by a number of vendors who saw specific needs and developed products to address them. Those products in turn were presented to laboratories as a means of solving their instrumental data collection and analysis, sample preparation, data management, and document management issues. With many needs and so many ways to address them, how do you go about choosing a set of products that will work for you?

That is what this set of webinars is all about. We introduce the technologies and position them for you so that you can see how they may or may not apply to your work. Then we address the very real world topic of justifying the investment needed to put those tools to use in your laboratories.

Once that foundation has been put in place we cover:

Technology planning and education: Planning is essential for success in this work. We look at how to go about it, who to involve, and methodologies for carrying out the work. We also look at the associated knowledge necessary to be effective.
Implementation: Informatics systems can be a challenge to implement. We look at what is needed to minimize risks and make the implementation easier, as well as the support requirements needed to manage their use in your laboratory environment.
Regulatory guidelines and compliance: We also address regulatory guidelines and compliance and how they can affect every laboratory application.
The future: What developments will arise and be needed in the future? We wrap up the series with those details.

The material in the link below gives you access to a series of slides and transcripts of a webinar series consisting of an introduction plus:

Laboratory Informatics Technologies
Laboratory Informatics and Return on Investment
Technology Planning and Education
LIMS/LIS, ELN, SDMS, IT, and Education
Supporting Laboratory Systems
Instrument Data Systems
Laboratory Processes

This link give you access to the material through LIMSwiki.

Notes on Instrument Data Systems

The goal of this brief paper is to examine what it will take to advance laboratory operations in terms of technical content, data quality, and productivity. Advancements in the past have been incremental, and isolated, the result of an individual’s or group’s work and not part of a broad industry plan. Disjointed, uncoordinated, incremental improvements have to give way to planned, directed methods, such that appropriate standards and products can be developed and mutually beneficial R&D programs instituted. We’ve long since entered a phase where the cost of technology development and implementation is too high to rely on a “let’s try this” approach as the dominant methodology. Making progress in lab technologies is too important to be done without some direction (i.e., deliberate planning). Individual insights, inspiration, and “out of the box” thinking is always valuable; it can inspire a change in direction. But building to a purpose is equally important. This paper revisits past developments in instrument data systems (IDS), looks at issues that need attention as we further venture into the use of integrated informatics systems, and suggests some directions further development can take.

There is a second aspect beyond planning that also deserves attention: education. Yes, there are people who really know what they are doing with instrumental systems and data handling. However, that knowledge base isn’t universal across labs. Many industrial labs and schools have people using instrument data systems with no understanding of what is happening to their data. Others such as Hinshaw and Stevenson et al. have commented on this phenomenon in the past:

Chromatographers go to great lengths to prepare, inject, and separate their samples, but they sometimes do not pay as much attention to the next step: peak detection and measurement … Despite a lot of exposure to computerized data handling, however, many practicing chromatographers do not have a good idea of how a stored chromatogram file—a set of data points arrayed in time—gets translated into a set of peaks with quantitative attributes such as area, height, and amount.^[1]

At this point, I noticed that the discussion tipped from an academic recitation of technical needs and possible solutions to a session driven primarily by frustrations. Even today, the instruments are often more sophisticated than the average user, whether he/she is a technician, graduate student, scientist, or principal investigator using chromatography as part of the project. Who is responsible for generating good data? Can the designs be improved to increase data integrity?^[2]

We can expect that the same issue holds true for even more demanding individual or combined techniques. Unless lab personnel are well-educated in both the theory and the practice of their work, no amount of automation—including any IDS components—is going to matter in the development of usable data and information.

The IDS entered the laboratory initially as an aid to analysts doing their work. Its primary role was to off-load tedious measurements and calculations, giving analysts more time to inspect and evaluate lab results. The IDS has since morphed from a convenience to a necessity, and then to being a presumed part of an instrument system. That raises two sets of issues that we’ll address here regarding people, technologies, and their intersections:

1. People: Do the users of an IDS understand what is happening to their data once it leaves the instrument and enters the computer? Do they understand the settings that are available and the effect they have on data processing, as well as the potential for compromising the results of the analytical bench work? Are lab personnel educated so that they are effective and competent users of all the technologies used in the course of their work?

2. Technologies: Are the systems we are using up to the task that has been assigned to them as we automate laboratory functions?

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The Application of Informatics to Scientific Work: Laboratory Informatics for Newbies

The purpose of this piece is to introduce people who are not intimately familiar with laboratory work to the basics of laboratory operations and the role that informatics can play in assisting scientists, engineers, and technicians in their efforts. The concepts are important because they provide a functional foundation for understanding lab work and how that work is done in the early part of the twenty-first century (things will change, just wait for it).

Intended audience

This material is intended for anyone who is interested in seeing how modern informatics tools can help those doing scientific work. It will provide an orientation to scientific and laboratory work, as well as the systems that have been developed to make that work more productive. It’s for people coming out of school who have carried out lab experiments but not corporate research projects, for those who need to understand how testing labs work, and for IT professionals who may be faced with supporting computing systems in lab environments. It’s also for those who may be tasked with managing projects to choose, install, and make informatics tools useful.

Figure 1 shows the elements we’ll be discussing in this piece. The treatment of the technical material will be on the lighter side, leaving in-depth subject matter to other works. Instrument data systems will be covered lightly, as any serious discussion becomes lengthy and discipline-specific very quickly; additionally, that material has been covered in other works.

Figure 1. Elements we’ll be covering

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What is Laboratory Systems Engineering?

LSE is intended as a multi-disciplinary field of work encompassing an understanding of:

The relevant science. This is necessary because the LSE would connect with laboratory personnel and their work environment, understand what they are doing, and translate their needs into working systems. This could be a specialization point for an LSE in electronics, life science applications, physical sciences, etc. However, the basic principles of data acquisition, processing, storage, analysis, etc., are common across sciences, so moving from one scientific discipline to another would not be difficult.
Laboratory Informatics includes LIMS, ELN, SDMS, LES, IDS, digital communications connections (serial, parallel, GPIB, etc.), relevant protocols, analog data acquisition, and related processes etc.
Robotics, including electronics and mechanical engineering principles, and the application of commercial systems to lab work.
Information Systems Technologies, including hardware, operating systems, database applications, and communications. LSEs would not be a replacement for or duplication of traditional IT services. They would bridge the gap between IT services roles and applying those technologies to lab work. In many lab applications, the computer is just one piece of a system that is only fully functional if all the components work together. While this is less of a concern when a system (instruments and computers) is purchased and installed by the vendor, it becomes a significant problem when mixed vendor solutions are being used, for example, the connection of an instrument data system to a LIMS, SDMS, or ELN.

Their skill set should include working with teams and the ability to lead them in the successful development, execution, and completion of projects. This would require interpersonal skills to work with people at various management levels.

Part of the LAE’s role is to examine new technologies and see how they can be applied to lab work. Another is to assess the lab’s needs and anticipate technologies that need to be developed.

An earlier version of this skill set was described under “Laboratory Automation Engineering,” drafted in 2005/2006**. In the almost two decades since that article was released, laboratory informatics and information technologies have become more demanding and sophisticated, requiring a change in the field’s name to reflect those points.

It would also be helpful to have a background in General Systems Theory – This field of work will help LSEs and those they work with describe and understand the interactions between the laboratory informatics systems used in laboratory work. Why is that important in this context? Laboratory Informatics is an interconnected set of components that ideally will operate with minimum human intervention. General Systems Theory* will help describe those components and their interactions.

“Systems are studied by the general systems theory—an interdisciplinary theory about the nature of complex organizations in nature, society, and science, and is a framework by which one can investigate and/or describe any group of elements that are functioning together to fulfill some objective (whether intended, designed, man-made, or not).”, from: https://doi.org/10.1016/B978-0-12-381414-2.00004-X.

** “Are You a Laboratory Automation Engineer?”