search.noResults

search.searching

note.createNoteMessage

search.noResults

search.searching

orderForm.title

orderForm.productCode
orderForm.description
orderForm.quantity
orderForm.itemPrice
orderForm.price
orderForm.totalPrice
orderForm.deliveryDetails.billingAddress
orderForm.deliveryDetails.deliveryAddress
orderForm.noItems
laboratory informatics


incidences of data integrity-related cGMP violations.’ While discussions around data integrity are


oſten tethered to the pharmaceutical industry, the imperative to maintain the integrity of data is just as relevant to other sectors, including the food, environmental, chemicals, contract research and manufacturing industries,’ Jansen notes. From the perspective of the regulators and


industry itself, data integrity is ultimately about protecting public health and safety, whether you are talking about a new drug, or a child’s toy. ‘To be sure that products are safe, we need to have test data that fulfil that integrity definition of complete, consistent and accurate, and that are secure and traceable with no possibility of manipulation, whether that manipulation involves accidental or intentional modification, falsification or deletion.’


Locked into product life cycle Data integrity should also be tied to data quality, Jansen adds: ‘Te two go hand in hand; being able to verify data integrity means little if your data lacks quality or accuracy to start with. Tat quality will, to a large extent, depend on your instruments and the personnel who are operating them. You need to make sure that instruments are correctly maintained, calibrated and fit for purpose, that your experiments have been designed to generate the right type of data and that your personnel have been trained properly to execute the experiments. ‘Tracking this supporting information and


ensuring that they correctly represent the real- world to which they refer is just as important as the analytical data that you are looking to derive.’


Trickier management Managing and maintaining such huge amounts of data and its integrity becomes


trickier when you want to collate data from multiple and disparate sources in a single environment, Jansen admits: ‘Te scientific sector organisations need to consider open platforms that will meet data security and validation requirements, but which will interface directly with the data sources


SOME ORGANISATIONS


MAY HAVE TO SHOULDER THE EXPENSE OF UPGRADING ANALYTICAL INSTRUMENTATION BECAUSE LEGACY EQUIPMENT SIMPLY CAN’T BE INTERFACED WITH DATA MANAGEMENT PLATFORMS


and the data-consuming applications from multiple vendors, without the need to create a separate gigantic data warehouse. On top of this they should be able to handle and manage contextually disparate data formats that are generated across multiple disciplines.’


Opportunities for error In an ideal world, raw data will be captured from every piece of instrumentation and transferred directly into a secure electronic system, from where it can be reported in appropriate formats or shuttled between systems for further analysis, without any manual input, notes Graham Langrish, sales manager for life sciences at LabWare: ‘In reality, however, pen and paper still feature fairly heavily in many laboratories, including those that work with electronic laboratory notebooks (ELN) and laboratory information management systems (LIMS). From the


regulatory perspective, if you weigh a reagent on a balance, note the balance reading on a piece of paper and then go back to your bench and transfer that information into a LIMS or ELN, or even into an Excel spreadsheet, then the raw data isn’t what you put into your electronic system, but what you wrote down on your paper. ‘Tat gives two opportunities for error –


writing down an incorrect reading in the first instance, and putting an incorrect reading into the LIMS/ELN, even if you’ve written it down correctly.’ Te regulators are pushing for industry to


capture all its data electronically and transfer that data directly into data management platforms, in parallel the industry is pushing the informatics vendors to provide the soſtware that can achieve this, Langrish continues: ‘LabWare LIMS and ELN have been developed to integrate with a wide range of instrumentation and other informatics platforms. Some organisations may have to shoulder the expense of upgrading analytical instrumentation because legacy equipment simply can’t be interfaced with data management platforms.’ While it is obviously vital to maintain


the integrity of top-line data that come out of analytical instrumentation, it is just as important to maintain the integrity of data that will underpin any aspect of decision making, adds John Gabathuler, director, industrial and environmental at LabWare: ‘An informatics platform, such as LabWare LIMS/ELN, can help to do this by reducing the requirement to put pen to paper, and also by installing safeguards that will flag up a caution if any data that is added either manually – or automatically – is not within prescribed limits. Te LIMS/ELN has a lot of functionality within it to try to ensure that overall data integrity is maintained, by helping people manually to enter information accurately, and in the right format.’


Scientist using the latest LabWare software www.scientific-computing.com l @scwmagazine


Extensive data trails In the scientific field in particular, the development of ever more sensitive chemical and biological analyses, and advances in genomic and proteomic techniques, is increasing the depth and breadth of data that is generated, Langrish points out. In parallel, the amount of data that may be associated with even simple tasks, such as taking a pH reading of a chemical solution, for example, can be significant: ‘An extensive trail of data will oſten be required to demonstrate the integrity of a simple pH reading. All this data has to be backed by instrumentation maintenance and calibration, to verify the


JUNE/JULY 2016 23





Labware


Page 1  |  Page 2  |  Page 3  |  Page 4  |  Page 5  |  Page 6  |  Page 7  |  Page 8  |  Page 9  |  Page 10  |  Page 11  |  Page 12  |  Page 13  |  Page 14  |  Page 15  |  Page 16  |  Page 17  |  Page 18  |  Page 19  |  Page 20  |  Page 21  |  Page 22  |  Page 23  |  Page 24  |  Page 25  |  Page 26  |  Page 27  |  Page 28  |  Page 29  |  Page 30  |  Page 31  |  Page 32  |  Page 33  |  Page 34  |  Page 35  |  Page 36  |  Page 37  |  Page 38  |  Page 39  |  Page 40  |  Page 41  |  Page 42  |  Page 43  |  Page 44