Do you need improved laboratory informatics systems?
Systems such as LIMS, ELN, LES, SDMS and CDS can contribute significantly to increasing efficiency in the lab, releasing time for core science activities and enabling a wider audience to utilise valuable scientific data.
These systems, of course, come in a variety of formats suited for different industries and processes, from the earliest stages of cutting-edge research to the defined workflows in QC laboratories.
There is a myriad of drivers for adding or upgrading such systems however these drivers are nearly always linked to delivering faster decisions, that are more accurate and that are made with increased confidence.
Where should we invest next?
With a plethora of informatics systems all competing for your organisation’s attention, it can be complex to decide your next move. The existing systems landscape within a laboratory adds to this conundrum, as few labs are greenfield these days. Decisions on information systems made several years ago contribute to systems entanglement that influences todays’ direction.
Developing a laboratory information system strategy that defines the desired target state of systems can vastly assist in taking decisions in the short and medium term that deliver real impact without tying your hands in the longer term.
A great example of long-term goals effecting current decisions is a project we worked on twenty years ago. We worked with a Fast-Moving Consumer Goods (FMCG) company to implement a LIMS, configured to manage the day to day activities of new formulation research. A key requirement was to output the formulation candidate results to what would have been called a data warehouse back in the day. This ‘pool’ of successful and unsuccessful formulation data was to be used by statistics applications to predict interesting formulation areas. The future state being that this data analysis would reduce the number of formulations tested to produce a new product. Crucial in such a competitive space, this would ultimately reduce time to market. Interestingly, over the yearsthe LIMS used by this global company has changed several times, but the project to predict formulations is still a keystone of their information systems strategy.
This example was not chosen randomly, this challenge of balancing the provision of correct tools to support ‘bench science’ and enabling repurposing data for ‘desk-based science’ is of great significance to the life sciences industry.
Laboratory Information Systems Strategies
Information system strategies start by clearly defining what laboratory objectives are required in order to deliver the organisation’s overall business plan. Investigation workshops can then be structured with a cross section of laboratory personnel centred on both the laboratory objectives and the requirements of current and potential systems. Systems currently in place should also be evaluated typically assessing their Strengths, Weakness, Opportunities and Threats (SWOT).
The information gathered in the discovery phase can then be used to document the current state, develop the future state and importantly create a prioritised blueprint of how to move to the future state.
The diagram shows a typical laboratory information systems landscape.
The diagram is of course generic and simplistic, some systems will be relevant to some organisations and not to others. Even when you have a well-defined systems high level plan, there are still many details to resolve. Questions such as which processes / data do we include in ELN vs LIMS? Is one vendor for multiple systems better than multiple best of breed vendors? How master data are created and shared can derail the strategy if they are not approached with care.
Keeping the IS strategy alive and aligned to the organisation’s plans is critical to achieving long term benefits.
As the picture of the new landscape starts to become clearer, now is the time to consider the governance and maintenance of the IS strategy.
In addition to ongoing governance, it is important to keep a watchful brief on new technology. I recently heard an industry insider decry the future of ELN and LES, ‘they will wane in popularity and disappear’. While I don’t think this will happen, I can imagine a future where ELNs and LES are driven by voice commands and VR tools, such as Microsoft HoloLens, which could be used to replace existing keyboard, mouse and monitor interfaces.
Another good example is the use of vendor neutral instrument data formats. These have been touted as the future of archive and data reuse for a considerable number of years. However, with the ever-increasing emphasis on ‘desk-based science’ and the growing interest in AI and ML, this could be ‘vendor neutral data format’s’ time in the spotlight.
IS strategies develop a structured approach for IS projects and focus your budget on achievable business objectives and promise a step change in utility for scientists.
But until more companies start to adopt best practice approaches to IS strategy, they will struggle to get the most out of their investments, not to mention the knowledge, data and resources trapped in their organisations.