AIMC Topic: Drug Delivery Systems

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Drug Release Nanoparticle System Design: Data Set Compilation and Machine Learning Modeling.

ACS applied materials & interfaces
Magnetic nanoparticles (NPs) are gaining significant interest in the field of biomedical functional nanomaterials because of their distinctive chemical and physical characteristics, particularly in drug delivery and magnetic hyperthermia applications...

'Applications of machine learning in liposomal formulation and development'.

Pharmaceutical development and technology
Machine learning (ML) has emerged as a transformative tool in drug delivery, particularly in the design and optimization of liposomal formulations. This review focuses on the intersection of ML and liposomal technology, highlighting how advanced algo...

Machine Learning-Driven Prediction, Preparation, and Evaluation of Functional Nanomedicines Via Drug-Drug Self-Assembly.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Small molecules as nanomedicine carriers offer advantages in drug loading and preparation. Selecting effective small molecules for stable nanomedicines is challenging. This study used artificial intelligence (AI) to screen drug combinations for self-...

Toward Resolving Heterogeneous Mixtures of Nanocarriers in Drug Delivery Systems through Light Scattering and Machine Learning.

ACS nano
Nanocarriers (NCs) have emerged as a revolutionary approach in targeted drug delivery, promising to enhance drug efficacy and reduce toxicity through precise targeting and controlled release mechanisms. Despite their potential, the clinical adoption ...

Intelligence analysis of drug nanoparticles delivery efficiency to cancer tumor sites using machine learning models.

Scientific reports
This study focuses on the use of machine learning (ML) models to predict the biodistribution of nanoparticles in various organs, using a dataset derived from research on nanoparticle behavior for cancer treatment. The dataset includes both categorica...

Preparation and optimisation of solid lipid nanoparticles of rivaroxaban using artificial neural networks and response surface method.

Journal of microencapsulation
AIMS: This study aimed to improve rivaroxaban delivery by optimising solid lipid nanoparticles (SLN) for minimal mean diameter and maximal entrapment efficiency (EE), enhancing solubility, bioavailability, and the ability to cross the blood-brain bar...

Deep Learning for the Accurate Prediction of Triggered Drug Delivery.

IEEE transactions on nanobioscience
The need to mitigate the adverse effects of chemotherapy has driven the exploration of innovative drug delivery approaches. One emerging trend in cancer treatment is the utilization of Drug Delivery Systems (DDSs), facilitated by nanotechnology. Nano...

Sub-millimeter fiberscopic robot with integrated maneuvering, imaging, and biomedical operation abilities.

Nature communications
Small-scale continuum robots hold promise for interventional diagnosis and treatment, yet existing models struggle to achieve small size, precise steering, and visualized functional treatment simultaneously, termed an "impossible trinity". This study...

Breaking Through Physiological Barriers: Nanorobotic Strategies for Active Drug Delivery.

Bioconjugate chemistry
Self-propelled micro/nanomotors (MNMs) represent a groundbreaking advancement in precision drug delivery, offering potential solutions to persistent challenges such as systemic toxicity, limited bioavailability, and nonspecific distribution. By trans...

Cubosomes as Delivery System to Repositioning Nitrofurantoin in Breast Cancer Management.

Drug design, development and therapy
PURPOSE: Nitrofurantoin (NITRO), a long-standing antibiotic to treat urinary tract infections, is activated by Nitro reductases. This activation mechanism has led to its exploration for repositioning applications in controlling and treating breast ca...