Artificial intelligence to deep learning: machine intelligence approach for drug discovery
Drug designing and development is an important area of research for pharmaceutical
companies and chemical scientists. However, low efficacy, off-target delivery, time …
companies and chemical scientists. However, low efficacy, off-target delivery, time …
Toward better drug discovery with knowledge graph
Drug discovery is the process of new drug identification. This process is driven by the
increasing data from existing chemical libraries and data banks. The knowledge graph is …
increasing data from existing chemical libraries and data banks. The knowledge graph is …
Artificial intelligence in drug development: present status and future prospects
KK Mak, MR Pichika - Drug discovery today, 2019 - Elsevier
Highlights•Advances in artificial intelligence (AI) are modernising several aspects of our
lives.•The pharma industry is facing challenges to overcome the high attrition rates in drug …
lives.•The pharma industry is facing challenges to overcome the high attrition rates in drug …
Artificial intelligence and machine learning‐aided drug discovery in central nervous system diseases: State‐of‐the‐arts and future directions
Neurological disorders significantly outnumber diseases in other therapeutic areas.
However, developing drugs for central nervous system (CNS) disorders remains the most …
However, developing drugs for central nervous system (CNS) disorders remains the most …
Artificial intelligence in the prediction of protein–ligand interactions: recent advances and future directions
New drug production, from target identification to marketing approval, takes over 12 years
and can cost around $2.6 billion. Furthermore, the COVID-19 pandemic has unveiled the …
and can cost around $2.6 billion. Furthermore, the COVID-19 pandemic has unveiled the …
[HTML][HTML] Recent advances in metabolomics analysis for early drug development
JC Alarcon-Barrera, S Kostidis, A Ondo-Mendez… - Drug discovery today, 2022 - Elsevier
Highlights•Metabolomics has become a widely applied tool in drug development.•
Metabolomics plays a key role for the identification of physiological response markers.• …
Metabolomics plays a key role for the identification of physiological response markers.• …
Application of Artificial Intelligence in COVID-19 drug repurposing
Background and aim COVID-19 outbreak has created havoc and a quick cure for the
disease will be a therapeutic medicine that has usage history in patients to resolve the …
disease will be a therapeutic medicine that has usage history in patients to resolve the …
Nanotoxicology and nanosafety: Safety-by-design and testing at a glance
A Zielińska, B Costa, MV Ferreira, D Miguéis… - International Journal of …, 2020 - mdpi.com
This review offers a systematic discussion about nanotoxicology and nanosafety associated
with nanomaterials during manufacture and further biomedical applications. A detailed …
with nanomaterials during manufacture and further biomedical applications. A detailed …
Artificial intelligence and machine learning approaches for drug design: challenges and opportunities for the pharmaceutical industries
C Selvaraj, I Chandra, SK Singh - Molecular diversity, 2021 - Springer
The global spread of COVID-19 has raised the importance of pharmaceutical drug
development as intractable and hot research. Developing new drug molecules to overcome …
development as intractable and hot research. Developing new drug molecules to overcome …
hERG toxicity assessment: Useful guidelines for drug design
A Garrido, A Lepailleur, SM Mignani… - European journal of …, 2020 - Elsevier
All along the drug development process, one of the most frequent adverse side effects,
leading to the failure of drugs, is the cardiac arrhythmias. Such failure is mostly related to the …
leading to the failure of drugs, is the cardiac arrhythmias. Such failure is mostly related to the …