happening at all. Critically, data that is locked in paper notebooks or a spreadsheet on a researcher’s computer is neither sharable nor searchable. ‘Many food and drink research organisations are now contemplating or already going through the process of updating their practices from pen and paper to an electronic system that allows the easy archival and retrieval of information,’ said Vaschetto.
Dotmatics Studies ELN provides full traceability of samples throughout the testing process
product brand – you need to marshal your information and resources to improve performance around five common objectives: governance and compliance, internal and external communication, efficient document access, recall management, and auditable and defensible information. Te internal and external communication
of research and results can bring their own set of difficulties. Mariana Vaschetto, VP for marketing at Dotmatics, a global informatics solution and service provider, said the problem lies in the fact that data is oſten being exchanged via email, Excel spreadsheets and shared drives – or, in some cases, it is not
Case study
René Blok, head of the analytical laboratory at IOI Loders Croklaan Europe, describes his laboratory’s informatics set-up
IOI Loders Croklaan Europe implemented its first laboratory information management system (LIMS) in 1990, and introduced Seimen’s Simatic IT Unilab, a multi-lab, multi-language enterprise LIMS for QC, service and R&D labs, in 1999. The main goal was to implement a system that could host the huge quantities of complex analytical data generated during the production processes, and at the same time offer the possibility to connect the analytical instrumentation. The LIMS handles the storage and availability of analytical data produced during the operations, the supply chains, and R&D activities – as well as the control samples for the regulation of the analytical process. This has the added advantage of making life easier for the analysts, and more pleasant by reducing manual data handling (both tedious and error- prone) with the advantage of creating a high level of traceability.
The data volumes resulting from all analyses
are considerable: approximately 100,000 samples per year, with an average of seven parameters per sample. Samples are taken in every phase
of the process (raw material and in-process samples, through to the finished product delivery samples), and analyses from the R&D department are included. All resulting analytical data is then aggregated in Unilab. If an out-of-specification result is registered during the analysis, Unilab feeds that information back to both the MES (manufacturing execution system) and SAP (systems application programing). When the SAP was first introduced, the IT landscape could be largely defined as follows: SAP as the system for master data, and Unilab LIMS as the system for analytical data. The SAP also contains customer information, specifications and analysis plans, while reporting and data collation is done via the LIMS. To keep track of the large amount of data the system works with, group keys give access to the right data in the database, based on the choice of the operator (period, location, type of sample, etc.). Reports can be generated in a flexible and ad-hoc manner with the reporting server (based on business objects). The automatic time- or event- based generation and dispatch of reports is also something that is scheduled and defined upfront, which means it can be done by the system at night, without further human involvement.
The LIMS is also used for the generation of worksheets. These tools provide barcode labels
for further processing, and instructions on what analysis needs to be carried out. For the sake of traceability equipment is connected as much as possible, and everything and everyone involved in the analysis is barcode-scanned (the analyst, the instrument, the production station, the type of analysis, and the sample). This not only offers a multi-faceted view of the analytical data, it makes the system easy to use and promotes its adoption.
Analytical processes are automated where possible. Some analytical processes are generated by robotic systems, according to the analysis plans, and are based on official standard operating procedures. Since no human intervention is required, this can run at night without the need for a lab technician. Results will be automatically transferred to the LIMS, after which people in the lab and the plant can access and drill the data at any time. Looking to the future, it will become
increasingly important to have an IT landscape in place that can accommodate changes without major customisations that clog the system and stand in the way of future flexibility. With this in mind, Loders is considering the deployment of a full web interface, which will have the added advantage of providing overseas plants with the ability to access the LIMS.
Optimising the lab Given the complexity involved in food and drink laboratories, companies like Accelrys have created scientific maturity models that are designed to help organisations understand how to optimise their workflows and best distribute their people, processes, tools and technology. Deployed on the Accelrys website 12 months ago, the tool begins by presenting people with a 12-question assessment to determine how well their companies perform in each of the four areas, and how they compare to industry peers. Gaps are then quickly identified. By effectively managing the entire scientific
lifecycle, companies are able to demonstrate a continuous thread of tracking and traceability based on the scientific decision process. Ted
Pawela, senior director of materials science and engineering solutions at Accelrys, explained: ‘People will not only be able to know precisely what is in each product, but can understand the basis on which decisions were made regarding its composition. In an electronically enabled way they are able to track back from the manufacturing process to the testing of samples, research and
COMPANIES ARE ABLE TO DEMONSTRATE A CONTINUOUS THREAD OF TRACKING AND TRACEABILITY BASED ON THE SCIENTIFIC DECISION PROCESS
development, and experimentation.’ Te use of electronic signatures also ensures that accountability is recorded at each stage of the process. Waters is another company focused on
removing the need for user intervention or transcription. Launched in 2012, the company’s informatics suite, NuGenesis 8,
10 SCIENTIFIC COMPUTING WORLD
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