Microfluidic technologies are rapidly becoming the method of choice for micro- and nanoparticle production across a number of sectors, from cell biology research to drug development. This approach offers a number of advantages over traditional batch methods, including precise process control, enhanced reliability, and the ability to easily scale up production.

The exceptional reproducibility and tunability of microfluidic particle generation provides new opportunities to streamline development workflows, using artificial intelligence (AI) to perform in silico predictions prior to laboratory testing. Dr Safa A Damiati from the Department of Pharmaceutics at King Abdulaziz University in Jeddah, Saudi Arabia, explained: “AI, and machine learning in particular, are now widely used for numerous applications in pharmaceutical development. These technologies help to accelerate research and reduce costs by, for example, predicting the experimental parameters or compounds most likely to give a particular outcome, without the need for extensive trial and error. However, AI approaches can only be used where results are predictable and reproducible, and sufficient quantities of carefullycurated data are available. Microfluidics brings this level of precision to particle generation, and has allowed us to develop a machine learning model that can successfully predict the experimental parameters required to generate size-tunable particles with specific characteristics.”

“Working with multiple data sets provided by Dolomite, we used a supervised learning approach to train an artificial neural network (ANN)to interpret the non-linear relationships between various experimental parameters – flow rates, polymer concentrations, etc. – on the resulting particles. Once we had trained, tested and validated the ANN model, we used an external data set containing previously unseen data to assess its capability to predict experimental outcomes, with accurate and promising results.* This initial proof-of-concept study showed that AI could be combined with microfluidic systems to accelerate research, and the aim now is to expand this approach to provide researchers with a novel tool to accelerate particle development for a variety of applications.”

Reference

* Damiati SA, et al. Artificial intelligence application for rapid fabrication of size-tunable PLGA microparticles in microfluidics. Sci Rep, 2020, 10, 19517

About Dolomite Microfluidics
 
Established in 2005, Dolomite Microfluidics has grown to be the world leader in the design and manufacture of high quality innovative microfluidic products.
 
The company offers a range of microfluidic systems, components and specialist chemicals – including pumps, chips, connectors, temperature controllers, sensors, accessories and custom-made components – as well as software for analysis or automation.
 
Modularity, ease of use, innovation and scalability are common to all Dolomite Microfluidics products, which are used across a broad range of applications in biology, drug discovery, chemistry, food, cosmetics and academia.
 
Dolomite is a part of the Blacktrace group of companies, a world leader in Productizing Science®, and has offices in the USA, Japan, India, Brazil and Hanoi as well as a worldwide network of distributors.

more news from Dolomite Microfluidics