AI Medical Compendium Journal:
Journal of drug targeting

Showing 1 to 10 of 10 articles

The biomedical applications of artificial intelligence: an overview of decades of research.

Journal of drug targeting
A significant area of computer science called artificial intelligence (AI) is successfully applied to the analysis of intricate biological data and the extraction of substantial associations from datasets for a variety of biomedical uses. AI has attr...

Artificial intelligence-based molecular property prediction of photosensitising effects of drugs.

Journal of drug targeting
Drug-induced photosensitivity is a potential adverse event of many drugs and chemicals used across a wide range of specialties in clinical medicine. In the present study, we investigated the feasibility of predicting the photosensitising effects of d...

Integrating machine learning and multitargeted drug design to combat antimicrobial resistance: a systematic review.

Journal of drug targeting
Antimicrobial resistance (AMR) is a critical global health challenge, undermining the efficacy of antimicrobial drugs against microorganisms like bacteria, fungi and viruses. Multidrug resistance (MDR) arises when microorganisms become resistant to m...

Artificial intelligence in nanotechnology for treatment of diseases.

Journal of drug targeting
Nano-based drug delivery systems (DDSs) have demonstrated the ability to address challenges posed by therapeutic agents, enhancing drug efficiency and reducing side effects. Various nanoparticles (NPs) are utilised as DDSs with unique characteristics...

Harnessing machine learning potential for personalised drug design and overcoming drug resistance.

Journal of drug targeting
Drug resistance in cancer treatment presents a significant challenge, necessitating innovative approaches to improve therapeutic efficacy. Integrating machine learning (ML) in cancer research is promising as ML algorithms outrival in analysing comple...

An extensive review on lung cancer therapeutics using machine learning techniques: state-of-the-art and perspectives.

Journal of drug targeting
There are over 100 types of human cancer, accounting for millions of deaths every year. Lung cancer alone claims over 1.8 million lives per year and is expected to surpass 3.2 million by 2050, which underscores the urgent need for rapid drug developm...

Artificial intelligence for skin permeability prediction: deep learning.

Journal of drug targeting
BACKGROUND AND OBJECTIVE: Researchers have put in significant laboratory time and effort in measuring the permeability coefficient (Kp) of xenobiotics. To develop alternative approaches to this labour-intensive procedure, predictive models have been ...

The ameliorating approach of nanorobotics in the novel drug delivery systems: a mechanistic review.

Journal of drug targeting
Nanoscale robotics have the ability that it can productively transform multiple energy sources into motion and strength which reflects an expeditiously appearing and captivating area for research of robotics. In today's plethora, biomedical nanorobot...

Machine learning-guided evolution of BMP-2 knuckle Epitope-Derived osteogenic peptides to target BMP receptor II.

Journal of drug targeting
Bone morphogenetic protein-2 (BMP-2) is a key regulator of bone formation, growth and regeneration, which contains a conformational wrist epitope and a linear knuckle epitope that are functionally responsible for the protein by mediating its interact...

Physicochemical property profile for brain permeability: comparative study by different approaches.

Journal of drug targeting
A comparative study of classification models of brain penetration by different approaches was carried out on a training set of 1000 chemicals and drugs, and an external test set of 100 drugs. Ten approaches were applied in this work: seven medicinal ...