AI-powered therapeutic target discovery
Disease modeling and target identification are the most crucial initial steps in drug
discovery, and influence the probability of success at every step of drug development …
discovery, and influence the probability of success at every step of drug development …
Artificial intelligence in COVID-19 drug repurposing
Drug repurposing or repositioning is a technique whereby existing drugs are used to treat
emerging and challenging diseases, including COVID-19. Drug repurposing has become a …
emerging and challenging diseases, including COVID-19. Drug repurposing has become a …
A small-molecule TNIK inhibitor targets fibrosis in preclinical and clinical models
Idiopathic pulmonary fibrosis (IPF) is an aggressive interstitial lung disease with a high
mortality rate. Putative drug targets in IPF have failed to translate into effective therapies at …
mortality rate. Putative drug targets in IPF have failed to translate into effective therapies at …
A roadmap for multi-omics data integration using deep learning
High-throughput next-generation sequencing now makes it possible to generate a vast
amount of multi-omics data for various applications. These data have revolutionized …
amount of multi-omics data for various applications. These data have revolutionized …
Rethinking drug design in the artificial intelligence era
P Schneider, WP Walters, AT Plowright… - Nature reviews drug …, 2020 - nature.com
Artificial intelligence (AI) tools are increasingly being applied in drug discovery. While some
protagonists point to vast opportunities potentially offered by such tools, others remain …
protagonists point to vast opportunities potentially offered by such tools, others remain …
A review of computational drug repositioning: strategies, approaches, opportunities, challenges, and directions
Drug repositioning is the process of identifying novel therapeutic potentials for existing drugs
and discovering therapies for untreated diseases. Drug repositioning, therefore, plays an …
and discovering therapies for untreated diseases. Drug repositioning, therefore, plays an …
AI in medical imaging informatics: current challenges and future directions
This paper reviews state-of-the-art research solutions across the spectrum of medical
imaging informatics, discusses clinical translation, and provides future directions for …
imaging informatics, discusses clinical translation, and provides future directions for …
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 …
[HTML][HTML] The rise of deep learning in drug discovery
Highlights•Deep learning technology has gained remarkable success.•We highlight the
recent applications of deep learning in drug discovery research.•Some popular deep …
recent applications of deep learning in drug discovery research.•Some popular deep …