INFORMATION TECHNOLOGY
Role of Artificial Intelligence and Machine Learning in Nanosafety Medical applications of nanomaterials span drug, protein and vaccine delivery, diagnostics, theranostics. There is a need for a ‘safe-by-design’ paradigm for nanomaterials, and machine learning is increasingly used to predict their properties. I briefly review nanomaterials machine learning modelling and provide examples where model predictions have been validated by experiments. David Winkler Professor of Biochemistry & Chemistry at La Trobe University, Professor of Pharmacy at the University of Nottingham, and Professor of Medicinal Chemistry at Monash University.
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anomaterials have been one of the most exciting scientific and technical innovations of the past few decades. Due to their very high surface to volume ratios, they exhibit properties that can differ dramatically from those for the same material in bulk. This, and their ability to be designed and synthesized with multiple surface functionalities, has seen them used for a myriad of bespoke applications in industry and medicine. Their medical applications span delivery systems for drugs, proteins and DNA/RNA to diagnostics, targeted cancer treatments, to theranostics. They have been used very successfully
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P H AR M A F O C U S E U R O PE
ISSUE 01 - 2022
