From machine learning to deep learning: progress in machine intelligence for rational drug discovery
Highlights•Six commonly used machine learning methods in QSAR models are
summarized.•Newly developed combinatorial QSAR and hybrid QSAR methods are …
summarized.•Newly developed combinatorial QSAR and hybrid QSAR methods are …
[HTML][HTML] In vitro and ex vivo models in inhalation biopharmaceutical research—advances, challenges and future perspectives
Oral inhalation results in pulmonary drug targeting and thereby reduces systemic side
effects, making it the preferred means of drug delivery for the treatment of respiratory …
effects, making it the preferred means of drug delivery for the treatment of respiratory …
A boiled‐egg to predict gastrointestinal absorption and brain penetration of small molecules
A Daina, V Zoete - ChemMedChem, 2016 - Wiley Online Library
Apart from efficacy and toxicity, many drug development failures are imputable to poor
pharmacokinetics and bioavailability. Gastrointestinal absorption and brain access are two …
pharmacokinetics and bioavailability. Gastrointestinal absorption and brain access are two …
[HTML][HTML] Real-time release testing of dissolution based on surrogate models developed by machine learning algorithms using NIR spectra, compression force and …
In this work spectroscopic measurements, process data and Critical Material Attributes
(CMAs) are used to predict the in vitro dissolution profile of sustained-release tablets with …
(CMAs) are used to predict the in vitro dissolution profile of sustained-release tablets with …
High throughput read-across for screening a large inventory of related structures by balancing artificial intelligence/machine learning and human knowledge
C Yang, JF Rathman, A Mostrag… - Chemical Research …, 2023 - ACS Publications
Read-across is an in silico method applied in chemical risk assessment for data-poor
chemicals. The read-across outcomes for repeated-dose toxicity end points include the no …
chemicals. The read-across outcomes for repeated-dose toxicity end points include the no …
[PDF][PDF] Archive of SID. ir
We [1, 2] and others [3- 5] have been interested in designing and making new molecules
that have biological activities, medicinal uses, coordination behaviors [6- 8] and studying …
that have biological activities, medicinal uses, coordination behaviors [6- 8] and studying …
Use of big data in drug development for precision medicine: an update
Introduction: Big-data-driven drug development resources and methodologies have been
evolving with ever-expanding data from large-scale biological experiments, clinical trials …
evolving with ever-expanding data from large-scale biological experiments, clinical trials …
The trends and future prospective of in silico models from the viewpoint of ADME evaluation in drug discovery
H Komura, R Watanabe, K Mizuguchi - Pharmaceutics, 2023 - mdpi.com
Drug discovery and development are aimed at identifying new chemical molecular entities
(NCEs) with desirable pharmacokinetic profiles for high therapeutic efficacy. The plasma …
(NCEs) with desirable pharmacokinetic profiles for high therapeutic efficacy. The plasma …
Simulation models for prediction of bioavailability of medicinal drugs—the interface between experiment and computation
The oral drug bioavailability (BA) problems have remained inevitable over the years,
impairing drug efficacy and indirectly leading to eventual human morbidity and mortality …
impairing drug efficacy and indirectly leading to eventual human morbidity and mortality …
[HTML][HTML] In silico molecular docking: Evaluation of coumarin based derivatives against SARS-CoV-2
Background The unique anthropological coronavirus which has been titled as SARS-CoV-2
was originally arisen in late 2019 in Wuhan, China affecting respiratory infection named as …
was originally arisen in late 2019 in Wuhan, China affecting respiratory infection named as …