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 …
In vitro models and systems for evaluating the dynamics of drug delivery to the healthy and diseased brain
HP Modarres, M Janmaleki, M Novin, J Saliba… - Journal of Controlled …, 2018 - Elsevier
The blood-brain barrier (BBB) plays a crucial role in maintaining brain homeostasis and
transport of drugs to the brain. The conventional animal and Transwell BBB models along …
transport of drugs to the brain. The conventional animal and Transwell BBB models along …
Explaining blood–brain barrier permeability of small molecules by integrated analysis of different transport mechanisms
FMG Cornelissen, G Markert, G Deutsch… - Journal of Medicinal …, 2023 - ACS Publications
The blood–brain barrier (BBB) represents a major obstacle to delivering drugs to the central
nervous system (CNS), resulting in the lack of effective treatment for many CNS diseases …
nervous system (CNS), resulting in the lack of effective treatment for many CNS diseases …
Improving grasshopper optimization algorithm for hyperparameters estimation and feature selection in support vector regression
High-dimensionality is one of the major problems which affect the quality of the classification
and prediction modeling. Support vector regression has been applied in several real …
and prediction modeling. Support vector regression has been applied in several real …
High-dimensional QSAR/QSPR classification modeling based on improving pigeon optimization algorithm
High-dimensionality is one of the major problems which affect the quality of the quantitative
structure-activity (property) relationship (QSAR/QSPR) classification methods in …
structure-activity (property) relationship (QSAR/QSPR) classification methods in …
Quantitative structure–activity relationship model for prediction study of corrosion inhibition efficiency using two‐stage sparse multiple linear regression
A new quantitative structure–activity relationship (QSAR) of the inhibition of mild steel
corrosion in 1 M hydrochloric acid using furan derivatives was developed by proposing two …
corrosion in 1 M hydrochloric acid using furan derivatives was developed by proposing two …
Assessment and reproducibility of quantitative structure–activity relationship models by the nonexpert
M Patel, ML Chilton, A Sartini, L Gibson… - Journal of Chemical …, 2018 - ACS Publications
Model reliability is generally assessed and reported as an intrinsic component of
quantitative structure–activity relationship (QSAR) publications; it can be evaluated using …
quantitative structure–activity relationship (QSAR) publications; it can be evaluated using …
High‐dimensional QSAR classification model for anti‐hepatitis C virus activity of thiourea derivatives based on the sparse logistic regression model with a bridge …
This study addresses the problem of the high‐dimensionality of quantitative structure‐activity
relationship (QSAR) classification modeling. A new selection of descriptors that truly affect …
relationship (QSAR) classification modeling. A new selection of descriptors that truly affect …
A new adaptive L1-norm for optimal descriptor selection of high-dimensional QSAR classification model for anti-hepatitis C virus activity of thiourea derivatives
ZY Algamal, MH Lee - SAR and QSAR in Environmental Research, 2017 - Taylor & Francis
A high-dimensional quantitative structure–activity relationship (QSAR) classification model
typically contains a large number of irrelevant and redundant descriptors. In this paper, a …
typically contains a large number of irrelevant and redundant descriptors. In this paper, a …
QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm
High-dimensionality is one of the major problems which affect the quality of the quantitative
structure–activity relationship (QSAR) modelling. Obtaining a reliable QSAR model with few …
structure–activity relationship (QSAR) modelling. Obtaining a reliable QSAR model with few …