laboratory informatics ➤

data accuracy and its integrity, as well as operator competence. LabWare LIMS/ELN has been developed to store and manage all these data points, and overlay that data with records of standard operating procedures, personnel training, instrumentation calibration and maintenance records, which can all be transferred directly into the LIMS/ ELN platform to support the final analytical data.’ It’s all heading towards the paperless lab,

and we are making good progress, Gabathuler suggests: ‘Sometimes it’s not possible to capture or transmit every piece of data electronically, and some data entry will have to be done manually. Te key is to ensure that data management systems that are in place help to ensure that mistakes are not made, that irregularities are at least flagged up for further investigation, and that once captured, data is secure and fully traceable.’

Limit the risks of manipulation In most cases companies put systems in place to try to ensure that they can comply with data integrity guidelines and mandates, and that they are confident of their own data integrity. Relying on data that has been generated by a CRO is a different matter, points out Paul Denny-Gouldson, vice president of strategic solutions at IDBS, citing the Semler case: ‘Whether samples or data are manipulated intentionally or unintentionally is a question that needs to be answered, but there are IT approaches that can be implemented by the sponsor and the CRO that will limit significantly the risks of either intentional or unintentional data manipulation.’ In parallel with sample management and tracking, organisations can also implement

a study master data management practice, to define all of the other sources of metadata around a study and make that data available to all other applications used in the collection and analysis of study data. ‘Tis can then be used by secondary applications to check at run time if samples and data are associated with the given study, alerting the user if they are not,’ Denny-Gouldson explains.

Error by exception Error by exception is a third IT element that can cross check samples against study data, alerting operators when there may be a problem. Error by exception applications will flag up out-of-scope data automatically to the user at the time of entry. ‘For example, a simple correlation of sample ID against subject ID against project ID can properly qualify whether a particular sample belongs to a particular study.’ Tis highlights another area of master data tracking around study and subjects – essentially the study design and



subject. ‘Tese errors by exception can also be automatically flagged to a QA/QC official for witnessing and handling. And when an error by exception has been flagged, process control applications can direct the user to help explain the cause of the error and what the corrective action should be.’ Te obvious extension to these elements

Inputting data on secure monitored platforms can protect data integrity.

is to remove as much human interference in the process as possible, Denny-Gouldson notes. ‘Full lab automation of bioanalytical laboratories is not as farfetched as it might first seem – various organisations have developed near 100 per cent automation environments for processing bioanalytical lab samples and analysis. Tis step requires all the above elements to be in place, but it does reduce significantly the risk of bad data getting into the value chain – and it also significantly improves sample throughput.’

The right environment Te final option in the CRO space is either to push the validated data collection and execution environment that the sponsor organisation wants to use to the CRO itself – or to integrate elements of the master data management and exception handling elements into the CRO’s systems, Denny-Gouldson suggests. ‘Te advent of secure, validated cloud-based collaboration environments that are designed to support this type of detailed and process-centric workflow makes it easily possible to give the CRO access to the validated data collection and execution environment. Te alternative option, of integrating

Laboratory informatics software helps assure data integrity 24 SCIENTIFIC COMPUTING WORLD

application services and master data management services between multiple organisations is perhaps another few years away yet – but it is something that is an active area of development now. It may never be possible to claim a zero risk of losing data integrity, but if multiple risk reduction elements are brought together, then the risk of using the wrong sample, creating data that is associated with the wrong sample, or reporting the wrong data to a study report, can be significantly reduced.’l

@scwmagazine l



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