Data: Instrumentation Building a Smart Laboratory 2015 Where there is an option, the choice of
dedicated computer-instrument combinations vs. multi-user, multi-instrument packages is worth careful consideration. Te most common example is chromatography, which has options from both instrument vendors and third- party suppliers. One of the major differences is data access
and management. In a dedicated format, each computer’s data system is independent and has to be managed individually, including backups to servers. It also means that searching for data may be more difficult. With multi-user/ instrument systems there is only one database that needs to be searched and managed. If you are considering connecting
the systems to a LIMS or ELN, make the connections as simple as possible. If an instrument supported by the soſtware needs to be replaced, changing the connection will be simpler. Licence costs are also a factor. Dedicated
formats require a licence for each system. Shared-access systems have more flexible licensing considerations. Some have a cost per user and connected instrument; others have a cost per active user/instrument schedules. In the latter case, there are eight instruments and four analysts, of which only half may be simultaneously active, licenses for only four instruments and two users are needed. Tere can be significant cost savings. One factor that needs attention is the
education of laboratory staff in the use of computer-instrument systems. While instrument soſtware systems are capable of doing a great deal, their ability to function is oſten governed by user-defined parameters that affect, at least in chromatography, baseline- corrections, area allocation for unresolved peaks, etc. Carefully adjusted and tuned parameters will yield good results, but problems can occur if they are not managed and checked for each run.
Instrument data management
Te issue of instrument data management is a significant one and requires considerable planning. Connecting instruments to a LIMS or ELN is a common practice, though oſten not an easy one if the informatics vendor hasn’t provided a mechanism for interfacing equipment. Depending on how things are set up, only a portion of the information in the instrument data system is transferred to the informatics system. If the transfer is the result of a worklist execution of a quantitative
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analysis, only the final result may be transferred – the reference data still resides on the instrument system. Te result is a distributed data structure. In regulated environments, this means that links to the backup information have to be maintained within the LIMS or ELN so that it can be traced back to the original analysis.
“ The issue of instrument data management is a significant one and requires considerable planning”
Te situation becomes more interesting
when instrument data systems change or are retired. Access still has to be maintained to the data those systems hold. One approach is virtualising the instrument data system so that the operating system, instrument support soſtware, and the data are archived together on a server. (Virtualisation is, in part, a process of making a copy of everything on a computer so that it can be stored on a server as a file or ‘virtual container’ and then executed on the server without the need for the original hardware. It can be backed up or archived, so that it is protected from loss.) In the smart laboratory, system management is a significant function – one that may be new to many facilities. Te benefits of doing it smartly are significant.
Computer-controlled experiments and sample processing
Adding intelligence to lab operations isn’t limited to processing instrument data, it extends to an earlier phase of the analysis: sample preparation. Robotic systems take samples from the form in which they were submitted to that needed by the instrument. Tey changed substantially. Robotic arms – still appropriate for many applications – have been replaced with components more suitable to the task, particularly where liquid handling is the dominant activity, as in life science applications. Success in automating sample preparation
depends heavily on thoroughly analysing the process in question and determining: • Whether or not the process is well documented and understood (no undocumented short-cuts or workarounds that are critical to success), and whether improvements or changes can be made without adversely impacting
the underlying science;
• Suitability for automation: whether or not there are any significant barriers (equipment, etc.) to automation and whether they can be resolved;
• Tat the return in investment is acceptable and that automation is superior to other alternatives such as outsourcing, particularly for shorter-term applications; and
• Tat the people implementing the project have the technical and project management skills appropriate for the work. Te tools available for successfully
implementing a process are clearly superior to what was available in the past. Rather than having a robot adapt to equipment that was made for people to work with, equipment has been designed for automation – a major advance. In the life sciences, the adoption of the microplate as a standard format multi- sample holder (typically 96 wells, but can have 384 or 1,536 wells – denser forms have been manufactured) has fostered the commercial availability of readers, shakers, washers, handlers, stackers, and liquid additions systems, which makes the design of preparation and analysis systems easier. Rather than processing samples one at a time, as was done in early technologies, parallel processing of multiple samples is performed to increase productivity. Te world is a bigger place than life sciences,
and other equipment has been developed to support analytical work. Te basic auto-sampler used to inject samples into instruments has been upgraded to address internally standard additions: heating, stirring, dissolution, derivitisation, chilling stations, headspace analysis, and barcode readers. Another area of development is the ability
to centralise sample preparation and then distribute the samples to instrumentation outside the sample prep area through pneumatic tubes. Tis technology offers increased efficiency by putting the preparation phase in one place so that solvents and preparation equipment can be easily managed, with analysis taking place elsewhere. Tis is particularly useful if safety is an issue. Te sample vials can be returned to a centralised disposal area. Across the landscape of laboratory types
and industries, the application of sample preparation robotics is patchy at best. Success and commercial interest have favoured areas where standardisation in sample formats has taken place. Te development of microplate sample
formats, including variations such as tape systems that maintain the same sample cell
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