Template:Justifying LIMS Acquisition and Deployment within Your Organization/Introduction to LIMS and its acquisition and deployment/LIMS acquisition now

1.4 LIMS acquisition now

Today, laboratories of all kinds face a variety of factors that drive them to become better at managing their operations. The tools for this improvement are available, and regulatory agencies expect labs to use the best technologies to meet regulatory requirements. Although it has been technically possible to meet regulatory requirements without computing technology—using paper-based systems—electronic systems make the work much easier and less costly, while improving the lab’s ability to meet inspectors' requests promptly, as well as the lab's workflows themselves. In the pre-electronic era, paper-based approaches to conducting lab operations were the only option, and these approaches tended to be slow, inefficient, and expensive. This changed in the late 1970s and into the 1980s, as computerized systems held promise in speeding up lab processes and making them more efficient, though they were still expensive to implement. Today, laboratory informatics options are less expensive, while also living up to the promise of improving lab operations. Laboratories produce data and information as their primary product; the ability to put those products to work and gain value from them is paramount. Continuing to use a paper-based system places limitations on that ability while incurring additional hidden and apparent costs to the lab. A LIMS and other informatics solutions make more sense than ever, particularly given stronger economic and competitive pressures.

Regulatory pressures have also increased as the regulatory landscape has changed. During the mid-1980s, when Mr. Golden's analysis was presented, regulatory requirements were beginning to gain new ground. The EPA and FDA had records retention requirements, and companies were starting to understand the FDA's guidelines, first published in 1978. There were still a lot of open issues; the words were there, but the intent wasn't clear. What did "validation" mean? What was the "first written record" of a result? The latter point made sense on paper, but what did it mean when applied to computers acquiring data and writing results into memory?

In the next few years:

• regulatory requirements were produced by OHSA;
• standards like ISO 9000 were developed by the International Organization for Standardization (ISO);
• the EPA’s good laboratory practices (GLP) came into existence; and
• the International Society of Pharmaceutical Engineers (ISPE) released the Good Automated Manufacturing Practices (GAMP).

Companies and their laboratories increasingly had to organize and document their work according to external standards, guidelines, and regulations instead of relying on internally defined business practices. These covered more than experimental records; they extended to personnel and their qualifications, equipment maintenance and calibrations, reagent maintenance and testing, and test method documentation and validation. It created a large amount of clerical and administrative work. In addition, the results of that work had to be produced on-demand. Today, regulatory compliance remains one of the primary reasons for adopting a LIMS.

Additionally, the requirements established by regulatory agencies provided the initial thrust for concerns over data governance, including data management, integrity, and utility. When everything was on paper, it was a matter of keeping paper documents well organized. There wasn't much else you could do. Then things changed, bringing with them new responsibilities and opportunities.

The integrity, security, and integration of instrument data is also a concern. Most instruments today either contain computing capabilities or are attached to computer systems with data storage, some temporary (e.g., pH meters and scales) and some long-term (e.g., IDSs). The more instruments we have, the more storage devices that hold laboratory results. In some cases, those results only exist on one storage device as long as a power surge doesn’t disrupt that system. Lab personnel probably know where the data they produce is, but that knowledge walks out the door every night. As such, laboratories need a centralized system to track all the data, information, results, calibrations, schedules, documents, etc., that labs produce. A small lab might be able to get by with a paper-based approach until they discover it no longer works, often when data previously believed to be secure becomes lost. Today, that centralized system is a LIMS.

Table 2 looks at a variety of these technological, regulatory, data governance, and data security issues, comparing what the state of thought was in the 1980s vs. today.

Table 2. Brief comparison of factors affecting laboratory operations in the 1980s vs. today. Factor 1980s Today Computing model Computing was still in the early stages of adoption, and IT support was in its infancy, mostly concerned with corporate issues. Laboratory automation was essentially a few "islands of automation," with little interconnection. Personal computing was also in its infancy, and cloud computing didn't exist. Today, computing is widespread, and IT support can be found in many organizations large and small. Interconnected systems are just part of the landscape inside and outside the laboratory. Personal computing is ubiquitous at work and home, as is wired and wireless networking. Cloud computing is available through a variety of technologies for executing applications, primary data storage, data backup, access to advanced technologies, etc. Regulatory landscape Regulations were in the early stages of development, with the EPA and FDA leading with record retention requirements and guidelines. Enforced regulations were just beginning. Regulations come from a variety of sources, with organizations finding themselves under one or more sets of standards, guidelines, and regulations, including ISO 9000, GAMP, and Clinical Laboratory Improvement Amendments (CLIA). Personnel Lab personnel were readily available. There is a growing shortage of people interested in and available for laboratory work, particularly in the medical realm. Data governance This concept was in its infancy, mostly in the form of records retention requirements. Data governance has become a significant factor in lab operations and management. Computer security This wasn't a serious issue, but evidence of problems was developing. style="background-color:white; padding-left:10px; padding-right:10px;" Computer security is a major consideration in all forms of computing. Computing legal issues There wasn't much different from paper-based operations. Anything needed from the lab for legal reasons was largely printed on paper. Legal issues have grown as material on computers is needed for business efficiency, patent evidence creation, intellectual property protection, regulatory compliance, knowledge management, data governance, and more.