2022
DOI: 10.3390/molecules27175676
|View full text |Cite
|
Sign up to set email alerts
|

Development of GBRT Model as a Novel and Robust Mathematical Model to Predict and Optimize the Solubility of Decitabine as an Anti-Cancer Drug

Abstract: The efficient production of solid-dosage oral formulations using eco-friendly supercritical solvents is known as a breakthrough technology towards developing cost-effective therapeutic drugs. Drug solubility is a significant parameter which must be measured before designing the process. Decitabine belongs to the antimetabolite class of chemotherapy agents applied for the treatment of patients with myelodysplastic syndrome (MDS). In recent years, the prediction of drug solubility by applying mathematical models… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
5
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
7

Relationship

0
7

Authors

Journals

citations
Cited by 7 publications
(5 citation statements)
references
References 36 publications
0
5
0
Order By: Relevance
“…Consequently, in numerous studies, researchers have resorted to utilizing classical ML algorithms to address tasks related to SCF-based pharmaceutical formulation preparation. Remarkably, these approaches have yielded commendable predictive results [65][66][67][68]. Conversely, employing models with a high number of parameters may lead to overfitting of the data, resulting in less-than-ideal predictive outcomes.…”
Section: Ai Modelsmentioning
confidence: 99%
See 2 more Smart Citations
“…Consequently, in numerous studies, researchers have resorted to utilizing classical ML algorithms to address tasks related to SCF-based pharmaceutical formulation preparation. Remarkably, these approaches have yielded commendable predictive results [65][66][67][68]. Conversely, employing models with a high number of parameters may lead to overfitting of the data, resulting in less-than-ideal predictive outcomes.…”
Section: Ai Modelsmentioning
confidence: 99%
“…[21,65,68,69] Extra Trees In the context of decision tree-based ensemble algorithms, a random feature is chosen during node splitting. [63,66] Table 6. Cont.…”
Section: Decision Tree Regressionmentioning
confidence: 99%
See 1 more Smart Citation
“…Machine learning (ML) techniques have shown great potential in the field of drug development by enabling accurate forecasting of drug solubility and density (Abdelbasset et al, 2022;Almehizia et al, 2023). These techniques have the capability to evaluate large amounts of data and extract meaningful patterns and relationships that can be utilized for predictions (Jovel and Greiner, 2021).…”
Section: Introductionmentioning
confidence: 99%
“…Estimating pharmaceutical solubility in supercritical solvents such as CO 2 has been reported by different methods such as thermodynamics and data-driven models 3 . The main inputs for the modeling have been considered to be pressure and temperature as these factors showed the most important effects on the drug solubility change 2 , 4 7 . It is a crucial step to measure and correlate drug solubility to prepare drugs with nanosized and better bioavailability.…”
Section: Introductionmentioning
confidence: 99%