In addition to laboratory instruments and equipment, vendors have created software products to assist lab personnel in their work. Some acquire and process data from instruments, some help manage that data, and others manage the lab’s workflow. The bottom line for these systems is to improve productivity, reduce the amount of manual labor and time required, and, at the same time, provide better results. Those benefits are only possible if you understand the software systems, how to use them, and their limitations.
Education is a big part of people’s problems working with laboratory informatics. What are the components, how do they fit together, and how do I use them effectively are just a few of the questions that need to be addressed. That is the point of the following article. I hope it serves you well. If you’d like to discuss it, send a note to “joe.liscouski@gmail.com” or “joe.liscouski@laboratorysystemsengineering.com.”
This guide’s intent is to help the science student and instructors understand the roles that laboratory informatics plays in scientific work and to give them a starting point in learning more about the subject.
Purpose:
- Bridge the gap between academic science education and the practical needs of industrial laboratory settings.
- Provide students and instructors with a framework to understand laboratory informatics and its applications in industrial settings.
Main Topics Covered:
- Science vs. Lab Operations:
- Academic labs focus on learning principles and techniques.
- Industrial labs emphasize producing reliable data under regulatory and operational guidelines.
2. Levels of Knowledge in Laboratory Informatics:
- Competent User
- Administrator
- Support (e.g., Laboratory Systems Engineers, IT Specialists)
- Developer
3. Informatics Tools and Technologies:
| Key Systems | – Laboratory Information Management Systems (LIMS) – Electronic Laboratory Notebooks (ELN) – Scientific Data Management Systems (SDMS) |
| Other Tools | – Laboratory Execution Systems (LES) – Instrument Data Systems (IDS) – Robotics for automation – Data acquisition and control |
| Data Governance and Integrity: | – Frameworks like ALCOA-CCEA ensure data reliability – Regulatory requirements |
Sources for the article:
- LIMSwiki – popular source of information about lab informatics
- Researchgate
- This article (see below)
Laboratory Systems Engineering 