Machine learning in drug discovery: a review
This review provides the feasible literature on drug discovery through ML tools and
techniques that are enforced in every phase of drug development to accelerate the research …
techniques that are enforced in every phase of drug development to accelerate the research …
Applications of machine learning in drug discovery and development
J Vamathevan, D Clark, P Czodrowski… - Nature reviews Drug …, 2019 - nature.com
Drug discovery and development pipelines are long, complex and depend on numerous
factors. Machine learning (ML) approaches provide a set of tools that can improve discovery …
factors. Machine learning (ML) approaches provide a set of tools that can improve discovery …
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 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 …
Translational precision medicine: an industry perspective
In the era of precision medicine, digital technologies and artificial intelligence, drug
discovery and development face unprecedented opportunities for product and business …
discovery and development face unprecedented opportunities for product and business …
Artificial intelligence: Machine learning approach for screening large database and drug discovery
PP Parvatikar, S Patil, K Khaparkhuntikar, S Patil… - Antiviral Research, 2023 - Elsevier
Recent research in drug discovery dealing with many faces difficulties, including
development of new drugs during disease outbreak and drug resistance due to rapidly …
development of new drugs during disease outbreak and drug resistance due to rapidly …
Machine learning applications in drug development
Due to the huge amount of biological and medical data available today, along with well-
established machine learning algorithms, the design of largely automated drug development …
established machine learning algorithms, the design of largely automated drug development …
Artificial intelligence in drug discovery: a comprehensive review of data-driven and machine learning approaches
As expenditure on drug development increases exponentially, the overall drug discovery
process requires a sustainable revolution. Since artificial intelligence (AI) is leading the …
process requires a sustainable revolution. Since artificial intelligence (AI) is leading the …
[HTML][HTML] In-silico predicting as a tool to develop plant-based biomedicines and nanoparticles: Lycium shawii metabolites
Introduction and purpose In silico approach helps develop biomedicines and is useful for
exploring the pharmacology of potential therapeutics using computer-simulated models. In …
exploring the pharmacology of potential therapeutics using computer-simulated models. In …