AI-powered solutions to create an ecosystem of connected Laboratories, says Frost & Sullivan

Maryam Farag   

Industry Manufacturing artificial intelligence automation development digital R&D Research Technology

Frost & Sullivan’s latest article, The Pharmaceutical Research and Development Laboratory of the Future, explores strategies to integrate digital and automated systems in research and development laboratories and their impact. The article also highlights the role of artificial intelligence solutions to enable a smart laboratory ecosystem.

“Connected laboratories have increased access to global scientific experts and highlight the need for pharmaceutical companies to reskill or upskill their own workforces to maximize the value of each resource,” said Dennis Kimmel, Senior Consultant, Healthcare, Frost & Sullivan. “With greater use of AI-powered solutions, laboratories can foster more effective collaboration, increase the number of new candidates entering the pipeline, and offer better flexibility of staffing assignments. This digitalization, in line with Industry 4.0, can enhance transparency, quality, and safety and enable more intelligent approaches to pharmaceutical development and manufacturing.”

“Thermo Fisher is exploring the role AI can play in enabling smarter, connected scientific instruments to close the skilled personnel gap,” said Andreas Huhmer, Senior Director Global Vertical Marketing, Thermo Fisher Scientific. “Building a laboratory ecosystem that connects people, instruments, and software will require the right capabilities and tools. This means enabling scientists to manage their analytical data and workflows, perform analysis on data from multiple instruments within a single system, and maintain data integrity.”

To tap into the “Laboratory of the Future” growth opportunities, market players should:

  • Stay on top of innovation in the market by developing data flow-driven systems to improve efficiency and effectiveness.
  • Form strategic partnerships and nurture collaborations with global laboratories to speed therapeutic development from hypothesis to final-stage clinical studies via digital connections.
  • Invest in digital solutions such as automation and Big Data analytics to reduce operational costs and improve productivity.




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