Unleashing the Power of Machine Learning in Nanomedicine Formulation Development
A random forest machine learning model is able to make predictions on nanoparticle attributes of different nanomedicines (i.e. lipid nanoparticles, liposomes, or PLGA nanoparticles) based on microfluidic formulation parameters. Machine learning models are based on a database of nanoparticle formulations, and models are able to generate unique solutions
Thomas L. Moore +7 more
wiley +1 more source
Influence of Nozzle Speed on the Crystallinity and Solubility of Polyvinyl Alcohol in Material Extrusion. [PDF]
Lee JE, Son Y, Park SJ.
europepmc +1 more source
Multiscale Structuring of Hydroxyapatite via Two‐Photon Lithography of Nanocomposites
Hydroxyapatite scaffolds are of great interest in bone tissue engineering applications, ranging from 3D cell culture to regenerative medicine. Using two‐photon lithography of a transparent nanocomposite, hydroxyapatite microstructures with features ranging from submicron to centimeter‐scale are fabricated. This allows to mimic the natural bone geometry,
Leonhard Hambitzer +6 more
wiley +1 more source
Book Review: Pharmaceutical Dissolution Testing
openaire +1 more source
Sustainable mechanochemical activation of rock phosphate with oxalic acid for high-efficiency phosphorus fertilizers. [PDF]
Dabare S, Munaweera I, Diyabalanage S.
europepmc +1 more source
A Bubble-Driven Drug Delivery System Enhances Oral Absorption and Antipyretic Efficacy of Poorly Water-Soluble Andrographolide. [PDF]
Zhou J +7 more
europepmc +1 more source
Acid Dissolution-Induced Damage Mechanisms in Concrete-Rock Composites: Experimental and Particle Flow Simulation. [PDF]
Chen H, Du B, Shen M, Wang J, Li Y.
europepmc +1 more source
Dual-source CT for medical dissolution of uric acid stones: a retrospective derivation and prospective validation study. [PDF]
Li W +6 more
europepmc +1 more source

