LIFE SCIENCES INDUSTRY CHALLENGES TODAY
Life Sciences organizations need to bring new high-quality therapeutics to market fast to respond to patient needs specific to different diseases and geographies. But development time and costs for new therapeutics are gigantic with an average accrual of $2.6B and 12 years from ideation to market. Reasons for the struggle include (1) the long “time to fail” in new target identification, (2) increasing global and regional regulations and scrutiny, and (3) the major efforts required to ensure that therapeutics are safe, efficacious and compliant with specifications. Personalized Medicine and Patient Centricity add complexity to Development and Manufacturing. Testing is required to confirm therapeutic characteristics discovered during Research, to identify and optimize formulations for production and scale-up, and to release active ingredients and products.
With long product development times, Life Sciences organizations must accelerate the pace and quality of innovation for long-term success. As a result, they are re-evaluating the entire product lifecycle from research through development to manufacturing and are adopting advanced information technology (IT) systems capable of supporting today’s dynamic business ecosystem. As products move from discovery and development to manufacturing and commercial operations, Life Sciences organizations are investing in the latest tools and technology to improve insight, accelerate innovation, reduce costs, and speed time to market. Faster innovation is a direct result of greater productivity with digital solutions in the lab, as researchers spend less time on documentation and leverage existing experimental data to make better decisions faster.
MOVING TOWARDS THE DIGITAL LAB
Laboratory organizations need an environment that facilitates and optimizes collaboration, experiment execution, documentation and data management in the different labs from R&D through manufacturing to commercialization. But today many laboratories are still working on paper or have a legacy system of some kind that digitally stores experimental data. This can be a database that includes anything from scanned PDF documents to word documents to spreadsheets. It can also be a commercial solution that is not fully leveraged because of usability or implementation issues. Many organizations that adopted early commercial ELNs now find themselves missing needed features with a system that is difficult to upgrade or has not been widely embraced by laboratory staff. The deployment of different (legacy) solutions in different areas or working fully or partially with paper often results in workflow inefficiencies, errors due to manual work, high total cost of ownership and difficult collaboration.