How to determine return on investment in lab automation technology
As life science organizations push the boundaries and deal with increasingly varied and complex data types, insights justify that further spend on lab automation software can help lead to a lab of the future environment
For companies to think about achieving a lab of the future environment, investment in lab automation is required to successfully bring disparate systems together and democratize access to data. With a number of pharma companies already owning large volumes of legacy software and maintaining instruments for patent filings, justifying further spend on lab software can be challenging for life science organizations.
In a recently published Pharma IQ report, Breaking down the barriers to the lab of the future, the most prominent investment benefit highlighted was “bringing scientists back to high-value scientific work and away from manual, time-intensive, low-value activity”.
Dr. Rob Brown, Vice-President of Product Marketing at scientific research informatics solutions provider Dotmatics, said, “For certain scientific disciplines, such as in analytical labs, an estimated 80 per cent of the scientists’ time is spent on manual data preparation. That means that they are able to spend 20 per cent of their time on their actual role and 80 per cent of their time doing something that doesn’t really add value.”
While investment in lab automation can help to overcome the time hurdles of manual work, it can also support data management and data transfer when outsourcing to different partners. For biotech organizations working on therapeutic projects and who are likely to outsource in this instance, the report highlights “between 50–70 per cent of work may be completed across multiple [contract research organizations (CROs)]. In these types of systems, being able to make dynamic decisions in relative real-time is crucial to the success of the research project”.
Brown explains, “You can spend one FTE on a CRO and you then have to spend half an FTE in-house to manage the data.” Brown notes that it is contradicting reasons for outsourcing research activity initially. Automation technology is highlighted as the key solution by Brown to create more efficient processes and allow researchers to focus their efforts on strategic activity.
For labs to thrive in today’s competitive marketplace, life science companies are implementing smarter solutions to manage operation processes, otherwise, they risk significant delays in research and loss of resources.
To learn how to employ smarter systems in your lab and improve your team's productivity, stay ahead of the data challenges facing scientists’ today and start planning your investment strategy in the next-generation of precision medicine and biologics. Also, read a round-up of the key insights from SmartLab Digital 2020 to receive data-driven benchmarks and peer-proven best practices from industry experts