The National Center for Advancing Translational Sciences (NCATS) is an institute within the NIH, its mission is to catalyse the next generation of innovative methods and technologies to enhance the speed of development, testing, and implementation of diagnostics and therapeutics.
The main aim is to perform translational research at scale. To achieve this, Pranav Bende, Senior Robotics Engineer at NIH, explained that researchers must identify the bottlenecks in drug discovery and tackle them at the bench level.
Bende described how NCATS develops custom robotic solutions, both hardware and software, to automate and optimise chemical synthesis workflows and address these bottlenecks. The organisation has a small platform called ASPIRE (A Specialised Platform for Innovative Research Exploration) that examines the entire workflow in a chemical synthesis cycle, starting with in silico design, followed by preparation, isolation, purification, and biological testing.
The data obtained from biological testing is fed back into a loop and iterated to refine the designs. The approach involves close collaboration between engineers and scientists, starting with manual setups, gathering user feedback, and iterating prototypes to gradually introduce automation. Bende also touched on the need for collaboration with external vendors for productisation.
Bende presented various in-house innovations, including a custom semi-automated solid-phase extraction setup to replace manual separation methods and a batch evaporator. Both of these technologies were designed and prototyped internally using advanced materials and 3D printing, which led to significantly reduced process times and better efficiency. Bende also commented that software integration is key and his team relies on an IoT-based NCAT Dashboard to remotely control and monitor lab equipment.
Some chemists are hesitant to automate certain processes, but it is time for a change in mindset. Bende concluded with the following message: successful automation requires dedicated teams, infrastructural changes like makerspaces and specialised lab utilities, and overcoming resistance from scientists accustomed to manual processes.
