Drug discovery is perhaps one of the most data sensitive processes in the world. From finding the drug target, to identifying potential drugs, sample validation, concept testing and ultimately launch, data has to be repeatedly logged, revised, checked and analysed in the laboratory. Advances in biotech and genomic technology mean this flow of information is no longer linear; instead, stages of this process are occurring simultaneously, creating a massive data mountain.
Laboratory Information Management Systems (LIMS) help automate the pooling and reporting of this data, providing manufacturers and distributors with access to critical scientific data, product information and trial records helping to streamline and accelerate development. LIMS are invaluable in automating, classifying and securing the increasing amounts of data generated by high through put laboratories during lab trials into one primary database. They can also be instrumental in improving workflow, alerting staff to the resources required for stability studies and stipulating when these need to be executed; ensuring data quality by rejecting substandard samples; and, providing analysis and reports to inform future working parties, for instance. Yet LIMS tend to be laboratory specific (typically pharmaceutical) requiring adaptation for other labs, and many of the LIMS in place today are fat client legacy systems making integration with other systems problematic.