Revolutionizing drug formulation development: the increasing impact of machine learning

Z Bao, J Bufton, RJ Hickman, A Aspuru-Guzik… - Advanced Drug Delivery …, 2023 - Elsevier
Over the past few years, the adoption of machine learning (ML) techniques has rapidly
expanded across many fields of research including formulation science. At the same time …

Application of machine learning in polymer additive manufacturing: A review

T Nasrin, F Pourkamali‐Anaraki… - Journal of Polymer …, 2024 - Wiley Online Library
Additive manufacturing (AM) is a revolutionary technology that enables production of
intricate structures while minimizing material waste. However, its full potential has yet to be …

Application of ensemble machine learning approach to assess the factors affecting size and polydispersity index of liposomal nanoparticles

B Hoseini, MR Jaafari, A Golabpour… - Scientific Reports, 2023 - nature.com
Liposome nanoparticles have emerged as promising drug delivery systems due to their
unique properties. Assessing particle size and polydispersity index (PDI) is critical for …

[HTML][HTML] Energy consumption and carbon footprint of 3D printing in pharmaceutical manufacture

M Elbadawi, AW Basit, S Gaisford - International Journal of Pharmaceutics, 2023 - Elsevier
Achieving carbon neutrality is seen as an important goal in order to mitigate the effects of
climate change, as carbon dioxide is a major greenhouse gas that contributes to global …

[HTML][HTML] The role of artificial intelligence in generating original scientific research

M Elbadawi, H Li, AW Basit, S Gaisford - International Journal of …, 2024 - Elsevier
Artificial intelligence (AI) is a revolutionary technology that is finding wide application across
numerous sectors. Large language models (LLMs) are an emerging subset technology of AI …

3D printing technology: A new approach for the fabrication of personalized and customized pharmaceuticals

M Ullah, A Wahab, SU Khan, M Naeem… - European Polymer …, 2023 - Elsevier
Abstract 3DP is a computer-aided designing with the interesting innovation of prototyping
layer-by-layer, creating 3D articles as digital blueprints to accomplish unequaled …

Progress and opportunities for machine learning in materials and processes of additive manufacturing

WL Ng, GL Goh, GD Goh, JSJ Ten… - Advanced …, 2024 - Wiley Online Library
In recent years, there has been widespread adoption of machine learning (ML) technologies
to unravel intricate relationships among diverse parameters in various additive …

Optimizing nanoliposomal formulations: Assessing factors affecting entrapment efficiency of curcumin-loaded liposomes using machine learning

B Hoseini, MR Jaafari, A Golabpour… - International Journal of …, 2023 - Elsevier
Background Curcumin faces challenges in clinical applications due to its low bioavailability
and poor water solubility. Liposomes have emerged as a promising delivery system for …

[HTML][HTML] Smart laser Sintering: Deep Learning-Powered powder bed fusion 3D printing in precision medicine

Y Abdalla, M Ferianc, A Awad, J Kim… - International Journal of …, 2024 - Elsevier
Medicines remain ineffective for over 50% of patients due to conventional mass production
methods with fixed drug dosages. Three-dimensional (3D) printing, specifically selective …

Electroactive Polymers for On‐Demand Drug Release

ME Alkahtani, M Elbadawi… - Advanced …, 2024 - Wiley Online Library
Conductive materials have played a significant role in advancing society into the digital era.
Such materials are able to harness the power of electricity and are used to control many …