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Title:Higher incidence of common polymorphisms in the genes of folate and methionine cycles in children with orofacial clefs and congenital heart defects compared to their unaffected siblings
Authors:ID Karas Kuželički, Nataša (Author)
ID Šmid, Alenka (Author)
ID Vidmar, Maša (Author)
ID Kek, Tina (Author)
ID Eberlinc, Andreja (Author)
ID Geršak, Borut (Author)
ID Mazić, Uroš (Author)
ID Mlinarič-Raščan, Irena (Author)
ID Geršak, Ksenija (Author)
Files:.pdf PDF - Presentation file, download (1,23 MB)
MD5: ED451CA1260907925914A2231AEF16E6
 
URL URL - Source URL, visit https://onlinelibrary.wiley.com/doi/10.1002/bdr2.2408
 
Language:English
Typology:1.01 - Original Scientific Article
Organization:Logo UKC LJ - Ljubljana University Medical Centre
Abstract:Background: Bioequivalence risk assessment as an extension of quality risk management lacks examples of quantitative approaches to risk assessment at an early stage of generic drug development. The aim of our study was to develop a model-based approach for bioequivalence risk assessment that uses pharmacokinetic and physicochemical characteristics of drugs as predictors and would standardize the first step of risk assessment. Methods: The Sandoz in-house bioequivalence database of 128 bioequivalence studies with poorly soluble drugs (23.5% non-bioequivalent) was used to train and validate the model. Four different modeling approaches, random forest, XGBoost, logistic regression and naïve Bayes, were compared. Results: Among the best performing machine learning models, random forest was selected and optimized for the number of features, resulting in an accuracy of 84% on the test data set. The most important features for prediction were those related to solubility (dose number, acid dissociation constant), absorption and elimination rate, effective permeability, variability of pharmacokinetic endpoints, and absolute bioavailability. All features had a conceivable influence on the model predictions. Conclusion: The model was used to develop a bioequivalence risk assessment approach to categorize drugs in early development into high, medium or low risk classes.
Keywords:congenital heart disease, folate metabolism, FPGS, genetics, orofacial clefts, polymorphisms, sibling pairs
Publication status:Published
Publication version:Version of Record
Year of publishing:2024
Number of pages:11 str.
Numbering:Vol. 116, iss. 11
PID:20.500.12556/DiRROS-29737 New window
UDC:575:616.12-039
ISSN on article:2472-1727
DOI:10.1002/bdr2.2408 New window
COBISS.SI-ID:213546755 New window
Note:Št. članka: e2408;
Publication date in DiRROS:04.06.2026
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Downloads:88
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Record is a part of a journal

Title:Birth defects research
Shortened title:Birth defects res.
Publisher:John Wiley & Sons, Inc.
ISSN:2472-1727
COBISS.SI-ID:530027289 New window

Document is financed by a project

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:J3-8207-2017
Name:Novi izzivi folatne terapije v porodništvu in ginekologiji

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:J3-5507-2013
Name:ANALIZA BIOLOŠKIH OZNAČEVALCEV PRESNOVE FOLATOV PRI UGOTAVLJANJU TVEGANJA ZA NASTANEK NAPAK NEVRALNE CEVI

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P3-0124-2020
Name:Metabolni in prirojeni dejavniki reproduktivnega zdravja, porod III

Funder:ARIS - Slovenian Research and Innovation Agency
Project number:P1-0208-2022
Name:Farmacevtska kemija: načrtovanje, sinteza in vrednotenje učinkovin

Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.

Secondary language

Language:Slovenian
Keywords:prirojena srčna napaka, metabolizem folatov, FPGS, orofacialne razjede, polimorfizmi, bratje in sestre pari


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