Lab automation and digital workflows are transforming R&D

Let us talk about automation and R&D workflows in pharmaceutical and biotech R&D and Innovation.

While many companies have invested a lot of thoughts, energy, and money in the topic, most of pharmaceutical and biotech R&D labs remain short of the advanced automation, miniaturization, and integration that can enable them to push the boundaries of scientific knowledge.

Nowadays, a convergence of breakthroughs and advancements, increasing integration and compatibility of technologies, and supported by digitization have made exploring automation options more imperative for successful pharmaceutical and biotech R&D. Since automation can only be effective if adopted and integrated into scientific processes, the experience and needs of the scientists involved should guide stakeholders’ decision making. Critical breakthroughs in R&D and Innovation orchestration, robotics, and liquid-handling technologies are now considered as a strategic priority for a majority of big corporations in the industry following many smaller size organizations.

Indeed, labs automation is not a silver bullet or a one-size-fits-all fix, however (full or partial) automation can bring several paybacks labs. More precisely, it could effectively contribute to improvements across all major laboratory KPIs, including but not limited to i) shorter cycle times, ii) higher throughput, iii) better reproducibility and iv) More predictability.

One should nevertheless keep in mind how to handle and organize the large flow of data lab automation will generate. Indeed, with the tremendous rise of data, R&D workflows have become more complex with big data playing a key role in driving scientific discovery. Scientists must manage the increased volume and the variety of data flowing from different instruments, sensors, systems, research teams, and partners. Therefore, the utilization of a comprehensive R&D digital platform seems mandatory.

A laboratory workflow can be defined as the sequence of tasks or steps to meet all the requirements for the completion of a process or work. A typical lab workflow commences with data collection from an instrument, then the data is transferred to an IT application, cleaned, and harmonized into an format enabling the use of artificial intelligence tools to generate deeper and faster insights. One of the key benefits of automated scientific workflows softwares, is that R&D and Innovation teams can spend less time on manual tasks and focus more on higher-value work allowing to move faster in face of the industry's top challenges.?