Machine learning predicts 3D printing performance of over 900 drug delivery systems

September 02, 2021 | Featured

Researchers at FabRx, the UCL School of Pharmacy, Universidade de Santiago de Compostela Departamento de Farmacología and University of A Coruña Department of Computer Science recently published a research article describing the use of machine learning to predict the 3D printing performance of 968 drug delivery systems. Data from 114 articles were collected and used to develop AI driven machine learning algorithms to predict 3D printing parameters and printed formulation characteristics.


Using machine learning as a predictive tool for 3D printing


Developing 3D-printable formulations can be a long and complex process, sometimes requiring extensive time and resources. Predictive tools, such as the one described, have the ability to reduce this drastically, speeding up the formulation development process and pushing the pharmaceutical 3D printing field further.

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