TY  - JOUR
AU  - Erić, Slavica
AU  - Kalinić, Marko
AU  - Popović, Aleksandar
AU  - Zloh, Mire
AU  - Kuzmanovski, Igor
PY  - 2012
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/1644
AB  - In this work, we present a novel approach for the development of models for prediction of aqueous solubility, based on the implementation of an algorithm for the automatic adjustment of descriptor's relative importance (AARI) in counter-propagation artificial neural networks (CPANN). Using this approach, the interpretability of the models based on artificial neural networks, which are traditionally considered as "black box" models, was significantly improved. For the development of the model, a data set consisting of 374 diverse drug-like molecules, divided into training (n = 280) and test (n = 94) sets using self-organizing maps, was used. Heuristic method was applied in preselecting a small number of the most significant descriptors to serve as inputs for CPANN training. The performances of the final model based on 7 descriptors for prediction of solubility were satisfactory for both training (RMSEPtrain = 0.668) and test set (RMSEPtest = 0.679). The model was found to be a highly interpretable in terms of solubility, as well as rationalizing structural features that could have an impact on the solubility of the compounds investigated. Therefore, the proposed approach can significantly enhance model usability by giving guidance for structural modifications of compounds with the aim of improving solubility in the early phase of drug discovery.
PB  - Elsevier Science BV, Amsterdam
T2  - International Journal of Pharmaceutics
T1  - Prediction of aqueous solubility of drug-like molecules using a novel algorithm for automatic adjustment of relative importance of descriptors implemented in counter-propagation artificial neural networks
VL  - 437
IS  - 1-2
SP  - 232
EP  - 241
DO  - 10.1016/j.ijpharm.2012.08.022
ER  - 

@article{
author = "Erić, Slavica and Kalinić, Marko and Popović, Aleksandar and Zloh, Mire and Kuzmanovski, Igor",
year = "2012",
abstract = "In this work, we present a novel approach for the development of models for prediction of aqueous solubility, based on the implementation of an algorithm for the automatic adjustment of descriptor's relative importance (AARI) in counter-propagation artificial neural networks (CPANN). Using this approach, the interpretability of the models based on artificial neural networks, which are traditionally considered as "black box" models, was significantly improved. For the development of the model, a data set consisting of 374 diverse drug-like molecules, divided into training (n = 280) and test (n = 94) sets using self-organizing maps, was used. Heuristic method was applied in preselecting a small number of the most significant descriptors to serve as inputs for CPANN training. The performances of the final model based on 7 descriptors for prediction of solubility were satisfactory for both training (RMSEPtrain = 0.668) and test set (RMSEPtest = 0.679). The model was found to be a highly interpretable in terms of solubility, as well as rationalizing structural features that could have an impact on the solubility of the compounds investigated. Therefore, the proposed approach can significantly enhance model usability by giving guidance for structural modifications of compounds with the aim of improving solubility in the early phase of drug discovery.",
publisher = "Elsevier Science BV, Amsterdam",
journal = "International Journal of Pharmaceutics",
title = "Prediction of aqueous solubility of drug-like molecules using a novel algorithm for automatic adjustment of relative importance of descriptors implemented in counter-propagation artificial neural networks",
volume = "437",
number = "1-2",
pages = "232-241",
doi = "10.1016/j.ijpharm.2012.08.022"
}

Erić, S., Kalinić, M., Popović, A., Zloh, M.,& Kuzmanovski, I.. (2012). Prediction of aqueous solubility of drug-like molecules using a novel algorithm for automatic adjustment of relative importance of descriptors implemented in counter-propagation artificial neural networks. in International Journal of Pharmaceutics
Elsevier Science BV, Amsterdam., 437(1-2), 232-241.
https://doi.org/10.1016/j.ijpharm.2012.08.022

Erić S, Kalinić M, Popović A, Zloh M, Kuzmanovski I. Prediction of aqueous solubility of drug-like molecules using a novel algorithm for automatic adjustment of relative importance of descriptors implemented in counter-propagation artificial neural networks. in International Journal of Pharmaceutics. 2012;437(1-2):232-241.
doi:10.1016/j.ijpharm.2012.08.022 .

Erić, Slavica, Kalinić, Marko, Popović, Aleksandar, Zloh, Mire, Kuzmanovski, Igor, "Prediction of aqueous solubility of drug-like molecules using a novel algorithm for automatic adjustment of relative importance of descriptors implemented in counter-propagation artificial neural networks" in International Journal of Pharmaceutics, 437, no. 1-2 (2012):232-241,
https://doi.org/10.1016/j.ijpharm.2012.08.022 . .

TY  - JOUR
AU  - Erić, Slavica
AU  - Kalinić, Marko
AU  - Popović, Aleksandar
PY  - 2010
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/1446
AB  - Aqueous solubility of a drug is a factor which can significantly influence its oral bioavailability, and can also affect the drug distribution in the body. Consideration of aqueous solubility in early stages of drug discovery and development is vital in reducing the incidence of late-stage drug development failures. The application of computational models for solubility prediction could provide the screening of combinatorial libraries, helping single-out potentially problematic and eliminate compounds with inadequate solubility. In addition to the prediction of solubility from chemical structure, the interpretation of such models can give an insight into structure-solubility relationships and can guide the optimization of structures in order to provide better solubility whilst retaining the activity of the investigated drugs. Development of such models is a complex process that requires consideration of numerous factors which can impact the final model's performance. Different solubility modeling approaches are discussed in this article. Despite intensive research on model development, prediction of the solubility of diverse drugs remains a challenging task. The quality of available experimental data used for modeling of solubility is increasingly recognized as one of the main causes for the limited reliability of many of the proposed models. Therefore, the full potential of the developed modeling methods will only be achieved by greater availability of reliable data obtained by same experimental methodology.
AB  - Rastvorljivost leka u vodi je faktor koji može značajno da utiče na bioraspoloživost peroralno primenjenog leka, kao i na njegovu raspodelu u organizmu. Razmatranjem rastvorljivosti u ranim fazama otkrića i razvoja leka smanjuje se mogućnost neuspeha u daljem razvoju leka. Računarske metode za predviđanje rastvorljivosti lekova omogućavaju analizu kombinatornih baza podataka, identifikaciju potencijalno problematičnih jedinjenja i isključivanje onih čija je rastvorljivost neadekvatna. Pored predviđanja rastvorljivosti na osnovu hemijske strukture, analizom ovih modela moguće je detaljnije razjasniti odnose hemijske strukture i rastvorljivosti ispitivanih lekova i optimizovati strukture u cilju poboljšanja rastvorljivosti, pri čemu bi njihova aktivnost ostala nepromenjena. Razvoj ovakvih modela je kompleksan proces koji zahteva razmatranje velikog broja faktora koji mogu uticati na uspešnost predviđanja konačnog modela. U ovom radu su prikazani različiti pristupi koji se koriste u razvoju računarskih modela za predviđanje rastvorljivosti. I pored intenzivnog rada na razvoju ovih modela tokom protekle decenije, pouzdanost predviđanja rastvorljivosti lekova različitih struktura još uvek ostaje veliki izazov. Kvalitet dostupnih eksperimentalnih podataka koji se koriste u modelovanju rastvorljivosti se u sve većoj meri prepoznaje kao jedan od glavnih uzroka ograničene pouzdanosti većine do sada predloženih modela. Iskorišćenje punog potencijala razvijenih pristupa modelovanja rastvorljivosti uslovljeno je širom dostupnošću pouzdanih podataka za rastvorljivost određenih pod identičnim eksperimentalnim uslovima.
PB  - Savez farmaceutskih udruženja Srbije, Beograd
T2  - Arhiv za farmaciju
T1  - Computational models for the prediction of drug solubility
T1  - Računarski modeli za predviđanje rastvorljivosti lekova
VL  - 60
IS  - 4
SP  - 373
EP  - 390
UR  - https://hdl.handle.net/21.15107/rcub_farfar_1446
ER  - 

@article{
author = "Erić, Slavica and Kalinić, Marko and Popović, Aleksandar",
year = "2010",
abstract = "Aqueous solubility of a drug is a factor which can significantly influence its oral bioavailability, and can also affect the drug distribution in the body. Consideration of aqueous solubility in early stages of drug discovery and development is vital in reducing the incidence of late-stage drug development failures. The application of computational models for solubility prediction could provide the screening of combinatorial libraries, helping single-out potentially problematic and eliminate compounds with inadequate solubility. In addition to the prediction of solubility from chemical structure, the interpretation of such models can give an insight into structure-solubility relationships and can guide the optimization of structures in order to provide better solubility whilst retaining the activity of the investigated drugs. Development of such models is a complex process that requires consideration of numerous factors which can impact the final model's performance. Different solubility modeling approaches are discussed in this article. Despite intensive research on model development, prediction of the solubility of diverse drugs remains a challenging task. The quality of available experimental data used for modeling of solubility is increasingly recognized as one of the main causes for the limited reliability of many of the proposed models. Therefore, the full potential of the developed modeling methods will only be achieved by greater availability of reliable data obtained by same experimental methodology., Rastvorljivost leka u vodi je faktor koji može značajno da utiče na bioraspoloživost peroralno primenjenog leka, kao i na njegovu raspodelu u organizmu. Razmatranjem rastvorljivosti u ranim fazama otkrića i razvoja leka smanjuje se mogućnost neuspeha u daljem razvoju leka. Računarske metode za predviđanje rastvorljivosti lekova omogućavaju analizu kombinatornih baza podataka, identifikaciju potencijalno problematičnih jedinjenja i isključivanje onih čija je rastvorljivost neadekvatna. Pored predviđanja rastvorljivosti na osnovu hemijske strukture, analizom ovih modela moguće je detaljnije razjasniti odnose hemijske strukture i rastvorljivosti ispitivanih lekova i optimizovati strukture u cilju poboljšanja rastvorljivosti, pri čemu bi njihova aktivnost ostala nepromenjena. Razvoj ovakvih modela je kompleksan proces koji zahteva razmatranje velikog broja faktora koji mogu uticati na uspešnost predviđanja konačnog modela. U ovom radu su prikazani različiti pristupi koji se koriste u razvoju računarskih modela za predviđanje rastvorljivosti. I pored intenzivnog rada na razvoju ovih modela tokom protekle decenije, pouzdanost predviđanja rastvorljivosti lekova različitih struktura još uvek ostaje veliki izazov. Kvalitet dostupnih eksperimentalnih podataka koji se koriste u modelovanju rastvorljivosti se u sve većoj meri prepoznaje kao jedan od glavnih uzroka ograničene pouzdanosti većine do sada predloženih modela. Iskorišćenje punog potencijala razvijenih pristupa modelovanja rastvorljivosti uslovljeno je širom dostupnošću pouzdanih podataka za rastvorljivost određenih pod identičnim eksperimentalnim uslovima.",
publisher = "Savez farmaceutskih udruženja Srbije, Beograd",
journal = "Arhiv za farmaciju",
title = "Computational models for the prediction of drug solubility, Računarski modeli za predviđanje rastvorljivosti lekova",
volume = "60",
number = "4",
pages = "373-390",
url = "https://hdl.handle.net/21.15107/rcub_farfar_1446"
}

Erić, S., Kalinić, M.,& Popović, A.. (2010). Computational models for the prediction of drug solubility. in Arhiv za farmaciju
Savez farmaceutskih udruženja Srbije, Beograd., 60(4), 373-390.
https://hdl.handle.net/21.15107/rcub_farfar_1446

Erić S, Kalinić M, Popović A. Computational models for the prediction of drug solubility. in Arhiv za farmaciju. 2010;60(4):373-390.
https://hdl.handle.net/21.15107/rcub_farfar_1446 .

Erić, Slavica, Kalinić, Marko, Popović, Aleksandar, "Computational models for the prediction of drug solubility" in Arhiv za farmaciju, 60, no. 4 (2010):373-390,
https://hdl.handle.net/21.15107/rcub_farfar_1446 .

TY  - JOUR
AU  - Erić, Slavica
AU  - Kalinić, Marko
AU  - Popović, Aleksandar
AU  - Makić, Halid
AU  - Civić, Elvisa
AU  - Bektašević, Mejra
PY  - 2010
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/1425
AB  - Aqueous solubility is an important factor influencing several aspects of the pharmacokinetic profile of a drug. Numerous publications present different methodologies for the development of reliable computational models for the prediction of solubility from structure. The quality of such models can be significantly affected by the accuracy of the employed experimental solubility data. In this work, the importance of the accuracy of the experimental solubility data used for model training was investigated. Three data sets were used as training sets - data set 1, containing solubility data collected from various literature sources using a few criteria (n = 319), data set 2, created by substituting 28 values from data set 1 with uniformly determined experimental data from one laboratory (n = 319), and data set 3, created by including 56 additional components, for which the solubility was also determined under uniform conditions in the same laboratory, in the data set 2 (n = 375). The selection of the most significant descriptors was performed by the heuristic method, using one-parameter and multi-parameter analysis. The correlations between the most significant descriptors and solubility were established using multi-linear regression analysis (MLR) for all three investigated data sets. Notable differences were observed between the equations corresponding to different data sets, suggesting that models updated with new experimental data need to be additionally optimized. It was successfully shown that the inclusion of uniform experimental data consistently leads to an improvement in the correlation coefficients. These findings contribute to an emerging consensus that improving the reliability of solubility prediction requires the inclusion of many diverse compounds for which solubility was measured under standardized conditions in the data set.
AB  - Rastvorljivost leka u vodi je značajan faktor koji utiče na više aspekata njegovog farmakokinetičkog profila. Brojne publikacije prezentuju različite metodologije za razvoj pouzdanih kompjuterskih modela za predviđanje rastvorljivosti na osnovu strukture jedinjenja. Kvalitet modela za predviđanje rastvorljivosti bitno zavisi od tačnosti eksperimentalnih vrednosti za rastvorljivost koje su korišćene za treniranje modela. U ovom radu proučavan je značaj primene eksperimentalnih podataka dobijenih pod standardizovanim, uniformnim uslovima za treniranje modela za predviđanje rastvorljivosti. Korišćena su tri seta podataka - ispitivani set 1 koji je dobijen odabirom eksperimentalnih vrednosti za rastvorljivost pod određenim kriterijumima iz različitih literaturnih izvora (n = 319), zatim ispitivani set 2 koji je dobijen zamenom 28 vrednosti za rastvorljivost iz ispitivanog seta 1 vrednostima za rastvorljivost dobijenim standardizovanom eksperimentalnom metodom u jednoj laboratoriji (n = 319) i ispitivani set 3 koji je dobijen dodatkom još 56 komponenata u ispitivani set 2, za koje su vrednosti rastvorljivisti takođe određene pod standardizovanim uslovima u istoj laboratoriji (n = 375). Zatim je primenjena heuristička metoda za selekciju najznačajnijih deskriptora, korišćenjem jednoparametarskih i višeparametarskih analiza. Postavljene su korelacije između najznačajnijih deskriptora i rastvorljivosti korišćenjem multilinearne regresione analize za sva tri ispitivana seta podataka. Uočena je značajna razlika između jednačina koje su dobijene korišćenjem različitih setova podataka, što ukazuje na to da je nakon uvođenja novih eksperimentalnih podataka neophodno dodatno optimizovati postojeće modele. Pokazano je da korišćenje uniformnih eksperimentalnih podataka uslovljava poboljšanje koeficijenata korelacije. Ovi rezultati govore u prilog sve zastupljenijem stavu da je za poboljšanje pouzdanosti predviđanja rastvorljivosti potrebno koristiti setove podataka velikog broja različitih jedinjenja čija je rastvorljivost merena pod standardizovanim uslovima.
PB  - Srpsko hemijsko društvo, Beograd
T2  - Journal of the Serbian Chemical Society
T1  - The importance of the accuracy of the experimental data for the prediction of solubility
T1  - Važnost preciznosti eksperimentalnih podataka za procenu rastvorljivosti
VL  - 75
IS  - 4
SP  - 483
EP  - 495
DO  - 10.2298/JSC090809022E
ER  - 

@article{
author = "Erić, Slavica and Kalinić, Marko and Popović, Aleksandar and Makić, Halid and Civić, Elvisa and Bektašević, Mejra",
year = "2010",
abstract = "Aqueous solubility is an important factor influencing several aspects of the pharmacokinetic profile of a drug. Numerous publications present different methodologies for the development of reliable computational models for the prediction of solubility from structure. The quality of such models can be significantly affected by the accuracy of the employed experimental solubility data. In this work, the importance of the accuracy of the experimental solubility data used for model training was investigated. Three data sets were used as training sets - data set 1, containing solubility data collected from various literature sources using a few criteria (n = 319), data set 2, created by substituting 28 values from data set 1 with uniformly determined experimental data from one laboratory (n = 319), and data set 3, created by including 56 additional components, for which the solubility was also determined under uniform conditions in the same laboratory, in the data set 2 (n = 375). The selection of the most significant descriptors was performed by the heuristic method, using one-parameter and multi-parameter analysis. The correlations between the most significant descriptors and solubility were established using multi-linear regression analysis (MLR) for all three investigated data sets. Notable differences were observed between the equations corresponding to different data sets, suggesting that models updated with new experimental data need to be additionally optimized. It was successfully shown that the inclusion of uniform experimental data consistently leads to an improvement in the correlation coefficients. These findings contribute to an emerging consensus that improving the reliability of solubility prediction requires the inclusion of many diverse compounds for which solubility was measured under standardized conditions in the data set., Rastvorljivost leka u vodi je značajan faktor koji utiče na više aspekata njegovog farmakokinetičkog profila. Brojne publikacije prezentuju različite metodologije za razvoj pouzdanih kompjuterskih modela za predviđanje rastvorljivosti na osnovu strukture jedinjenja. Kvalitet modela za predviđanje rastvorljivosti bitno zavisi od tačnosti eksperimentalnih vrednosti za rastvorljivost koje su korišćene za treniranje modela. U ovom radu proučavan je značaj primene eksperimentalnih podataka dobijenih pod standardizovanim, uniformnim uslovima za treniranje modela za predviđanje rastvorljivosti. Korišćena su tri seta podataka - ispitivani set 1 koji je dobijen odabirom eksperimentalnih vrednosti za rastvorljivost pod određenim kriterijumima iz različitih literaturnih izvora (n = 319), zatim ispitivani set 2 koji je dobijen zamenom 28 vrednosti za rastvorljivost iz ispitivanog seta 1 vrednostima za rastvorljivost dobijenim standardizovanom eksperimentalnom metodom u jednoj laboratoriji (n = 319) i ispitivani set 3 koji je dobijen dodatkom još 56 komponenata u ispitivani set 2, za koje su vrednosti rastvorljivisti takođe određene pod standardizovanim uslovima u istoj laboratoriji (n = 375). Zatim je primenjena heuristička metoda za selekciju najznačajnijih deskriptora, korišćenjem jednoparametarskih i višeparametarskih analiza. Postavljene su korelacije između najznačajnijih deskriptora i rastvorljivosti korišćenjem multilinearne regresione analize za sva tri ispitivana seta podataka. Uočena je značajna razlika između jednačina koje su dobijene korišćenjem različitih setova podataka, što ukazuje na to da je nakon uvođenja novih eksperimentalnih podataka neophodno dodatno optimizovati postojeće modele. Pokazano je da korišćenje uniformnih eksperimentalnih podataka uslovljava poboljšanje koeficijenata korelacije. Ovi rezultati govore u prilog sve zastupljenijem stavu da je za poboljšanje pouzdanosti predviđanja rastvorljivosti potrebno koristiti setove podataka velikog broja različitih jedinjenja čija je rastvorljivost merena pod standardizovanim uslovima.",
publisher = "Srpsko hemijsko društvo, Beograd",
journal = "Journal of the Serbian Chemical Society",
title = "The importance of the accuracy of the experimental data for the prediction of solubility, Važnost preciznosti eksperimentalnih podataka za procenu rastvorljivosti",
volume = "75",
number = "4",
pages = "483-495",
doi = "10.2298/JSC090809022E"
}

Erić, S., Kalinić, M., Popović, A., Makić, H., Civić, E.,& Bektašević, M.. (2010). The importance of the accuracy of the experimental data for the prediction of solubility. in Journal of the Serbian Chemical Society
Srpsko hemijsko društvo, Beograd., 75(4), 483-495.
https://doi.org/10.2298/JSC090809022E

Erić S, Kalinić M, Popović A, Makić H, Civić E, Bektašević M. The importance of the accuracy of the experimental data for the prediction of solubility. in Journal of the Serbian Chemical Society. 2010;75(4):483-495.
doi:10.2298/JSC090809022E .

Erić, Slavica, Kalinić, Marko, Popović, Aleksandar, Makić, Halid, Civić, Elvisa, Bektašević, Mejra, "The importance of the accuracy of the experimental data for the prediction of solubility" in Journal of the Serbian Chemical Society, 75, no. 4 (2010):483-495,
https://doi.org/10.2298/JSC090809022E . .

TY  - JOUR
AU  - Ražić, Slavica
AU  - Đogo, Svetlana
AU  - Slavković, Latinka
AU  - Popović, Aleksandar
PY  - 2005
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/662
AB  - Elemental profiles of the total analyte content of major, minor and trace elements (Cu, Zn, Mn, Fe, K, Ca, Mg, Al, Ba and B) in 8 herbal drugs, originating from medicinal plants of the family Lamiacae, were determined. Flame atomic absorption/ emission spectroscopy (FAAS/FAES), inductively coupled plasma atomic emission spectroscopy (ICP-AES) and energy dispersive X-ray fluorescence (EDXRF) were applied, and the advantages and limitations of these techniques are also discussed. The whole procedure, from sample preparation via dissolution to the actual measurements, was validated by using CRM (NIST 1573a - Tomato leaves). The recovery values obtained were in the range 90.64 - 101.58 %. A high degree of similarity in their elemental profiles was noticed from the results of qualitative analysis, while quantitative analysis shows significant diversity due to the variety of the influencing sources. The medicinal plants investigated in this work contained Cu (5.92- 14.79 mg kg-1), Zn (15.0 - 43.0 mg kg-1), Mn (25 - 111 mg kg-1), Fe (74 - 546 mg kg-1), K (1.80 - 6.24 %), Ca (0.90 - 1.43 %), Mg (0.17 - 0.67 %), Al (49 - 378 mg kg-1), Ba (15.53 - 69.84 mg kg-1) and B (34.7 - 56.5 mg kg-1).
AB  - Određeni su profili elemenata, izraženi kao ukupan sadržaj glavnih komponenti i tragova (Cu, Zn,Mn, Fe,K,Ca, Mg,Al, Ba i B) u 8 biljnih droga, dobijenih iz biljaka familije Lamiacae. U analizi su primenjene metode: plamena atomska apsorpciona/ emisiona spektroskopija, atomska emisiona spektroskopija sa induktivno spregnutom plazmom i fluorescentna rendgenska analiza sa disperzijom energije. Diskutovane su prednosti i ograničenja primenjenih metoda analize. Metodološki postupak od pripreme uzoraka, do merenja proveren je i potvrđen primenom sertifikovanog standardnog materijala (NIST 1573a - Tomato leaves). Statističkom obradom rezultata dobijeni su procenti prinosa u opsegu 90.64 - 101.58 %. Rezultati kvalitativne analize ukazuju na veliki stepen sličnosti u sastavu neorganskih analita. Kvantitativnom analizom određen je sadržaj 10 elemenata i uočena različitost koncentracionih profila. Analizirane biljne droge sadrže: Cu (5.92 - 14.79 mg kg-1), Zn (15.0 - 43.0mg kg-1), Mn (25 - 111 mg kg-1), Fe (74 - 546 mg kg-1), K (1.80 - 6.24 %), Ca (0.90 - 1.43 %), Mg (0.17 - 0.67 %), Al (49 - 378 mg kg-1), Ba (15.53 - 69.84 mg kg-1) and B (34.7 - 56.5mg kg -1).
PB  - Srpsko hemijsko društvo, Beograd
T2  - Journal of the Serbian Chemical Society
T1  - Inorganic analysis of herbal drugs, Part I: Metal determination in herbal drugs originating from medicinal plants of the family Lamiacae
T1  - Neorganska analiza biljnih droga, I deo - određivanje metala u biljnim drogama dobijenih iz biljaka familije Lamiacae
VL  - 70
IS  - 11
SP  - 1347
EP  - 1355
DO  - 10.2298/JSC0511347R
ER  - 

@article{
author = "Ražić, Slavica and Đogo, Svetlana and Slavković, Latinka and Popović, Aleksandar",
year = "2005",
abstract = "Elemental profiles of the total analyte content of major, minor and trace elements (Cu, Zn, Mn, Fe, K, Ca, Mg, Al, Ba and B) in 8 herbal drugs, originating from medicinal plants of the family Lamiacae, were determined. Flame atomic absorption/ emission spectroscopy (FAAS/FAES), inductively coupled plasma atomic emission spectroscopy (ICP-AES) and energy dispersive X-ray fluorescence (EDXRF) were applied, and the advantages and limitations of these techniques are also discussed. The whole procedure, from sample preparation via dissolution to the actual measurements, was validated by using CRM (NIST 1573a - Tomato leaves). The recovery values obtained were in the range 90.64 - 101.58 %. A high degree of similarity in their elemental profiles was noticed from the results of qualitative analysis, while quantitative analysis shows significant diversity due to the variety of the influencing sources. The medicinal plants investigated in this work contained Cu (5.92- 14.79 mg kg-1), Zn (15.0 - 43.0 mg kg-1), Mn (25 - 111 mg kg-1), Fe (74 - 546 mg kg-1), K (1.80 - 6.24 %), Ca (0.90 - 1.43 %), Mg (0.17 - 0.67 %), Al (49 - 378 mg kg-1), Ba (15.53 - 69.84 mg kg-1) and B (34.7 - 56.5 mg kg-1)., Određeni su profili elemenata, izraženi kao ukupan sadržaj glavnih komponenti i tragova (Cu, Zn,Mn, Fe,K,Ca, Mg,Al, Ba i B) u 8 biljnih droga, dobijenih iz biljaka familije Lamiacae. U analizi su primenjene metode: plamena atomska apsorpciona/ emisiona spektroskopija, atomska emisiona spektroskopija sa induktivno spregnutom plazmom i fluorescentna rendgenska analiza sa disperzijom energije. Diskutovane su prednosti i ograničenja primenjenih metoda analize. Metodološki postupak od pripreme uzoraka, do merenja proveren je i potvrđen primenom sertifikovanog standardnog materijala (NIST 1573a - Tomato leaves). Statističkom obradom rezultata dobijeni su procenti prinosa u opsegu 90.64 - 101.58 %. Rezultati kvalitativne analize ukazuju na veliki stepen sličnosti u sastavu neorganskih analita. Kvantitativnom analizom određen je sadržaj 10 elemenata i uočena različitost koncentracionih profila. Analizirane biljne droge sadrže: Cu (5.92 - 14.79 mg kg-1), Zn (15.0 - 43.0mg kg-1), Mn (25 - 111 mg kg-1), Fe (74 - 546 mg kg-1), K (1.80 - 6.24 %), Ca (0.90 - 1.43 %), Mg (0.17 - 0.67 %), Al (49 - 378 mg kg-1), Ba (15.53 - 69.84 mg kg-1) and B (34.7 - 56.5mg kg -1).",
publisher = "Srpsko hemijsko društvo, Beograd",
journal = "Journal of the Serbian Chemical Society",
title = "Inorganic analysis of herbal drugs, Part I: Metal determination in herbal drugs originating from medicinal plants of the family Lamiacae, Neorganska analiza biljnih droga, I deo - određivanje metala u biljnim drogama dobijenih iz biljaka familije Lamiacae",
volume = "70",
number = "11",
pages = "1347-1355",
doi = "10.2298/JSC0511347R"
}

Ražić, S., Đogo, S., Slavković, L.,& Popović, A.. (2005). Inorganic analysis of herbal drugs, Part I: Metal determination in herbal drugs originating from medicinal plants of the family Lamiacae. in Journal of the Serbian Chemical Society
Srpsko hemijsko društvo, Beograd., 70(11), 1347-1355.
https://doi.org/10.2298/JSC0511347R

Ražić S, Đogo S, Slavković L, Popović A. Inorganic analysis of herbal drugs, Part I: Metal determination in herbal drugs originating from medicinal plants of the family Lamiacae. in Journal of the Serbian Chemical Society. 2005;70(11):1347-1355.
doi:10.2298/JSC0511347R .

Ražić, Slavica, Đogo, Svetlana, Slavković, Latinka, Popović, Aleksandar, "Inorganic analysis of herbal drugs, Part I: Metal determination in herbal drugs originating from medicinal plants of the family Lamiacae" in Journal of the Serbian Chemical Society, 70, no. 11 (2005):1347-1355,
https://doi.org/10.2298/JSC0511347R . .

TY  - JOUR
AU  - Ražić, Slavica
AU  - Onjia, Antonije
AU  - Đogo-Mračević, Svetlana
AU  - Slavković, Latinka
AU  - Popović, Aleksandar
PY  - 2005
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/577
AB  - The concentrations of Cu, Zn, Mn, Fe, K, Ca, Mg, Al, Ba and B in 26 herbal drugs of special importance in phytopharmacywere studied. Flame atomic absorption and emission spectrometry (FAAS, FAES), as well as inductively coupled plasma atomic emission spectrometry (ICP-AES), were applied in this work. The whole procedure, from sample preparation, via dissolution, to measurements, was validated by using CRM (NIST 1573a-tomato leaves), and the obtained recovery values are in the range from 91 to 102%. Drug samples originated from medicinal plants cultivated in Serbia contained Cu (4.47-14.08 mg kg(-1)), Zn (8.4-54.5 mg kg(-1)), Mn (9-155 mg kg(-1)), Fe (47-546 mg kg(-1)), K (0.20-6.24%), Ca (0.18-1.84%), Mg (0.13-1.09%), Al (16-416 mg kg(-1)), Ba (11.70-84.83 mg kg(-1)) and B (5.1-118.7 mg kg(-1)). In order to get a better insight into the elemental patterns, a common chemometric approach to data evaluation was used. Four significant factors identified by principal component analysis (PCA) were attributed partly to the significant influential sources and high mobility of some elements thus referring to potential anthropogenic contamination as well.
PB  - Elsevier Science BV, Amsterdam
T2  - Talanta
T1  - Determination of metal content in some herbal drugs - Empirical and chemometric approach
VL  - 67
IS  - 1
SP  - 233
EP  - 239
DO  - 10.1016/j.talanta.2005.03.023
ER  - 

@article{
author = "Ražić, Slavica and Onjia, Antonije and Đogo-Mračević, Svetlana and Slavković, Latinka and Popović, Aleksandar",
year = "2005",
abstract = "The concentrations of Cu, Zn, Mn, Fe, K, Ca, Mg, Al, Ba and B in 26 herbal drugs of special importance in phytopharmacywere studied. Flame atomic absorption and emission spectrometry (FAAS, FAES), as well as inductively coupled plasma atomic emission spectrometry (ICP-AES), were applied in this work. The whole procedure, from sample preparation, via dissolution, to measurements, was validated by using CRM (NIST 1573a-tomato leaves), and the obtained recovery values are in the range from 91 to 102%. Drug samples originated from medicinal plants cultivated in Serbia contained Cu (4.47-14.08 mg kg(-1)), Zn (8.4-54.5 mg kg(-1)), Mn (9-155 mg kg(-1)), Fe (47-546 mg kg(-1)), K (0.20-6.24%), Ca (0.18-1.84%), Mg (0.13-1.09%), Al (16-416 mg kg(-1)), Ba (11.70-84.83 mg kg(-1)) and B (5.1-118.7 mg kg(-1)). In order to get a better insight into the elemental patterns, a common chemometric approach to data evaluation was used. Four significant factors identified by principal component analysis (PCA) were attributed partly to the significant influential sources and high mobility of some elements thus referring to potential anthropogenic contamination as well.",
publisher = "Elsevier Science BV, Amsterdam",
journal = "Talanta",
title = "Determination of metal content in some herbal drugs - Empirical and chemometric approach",
volume = "67",
number = "1",
pages = "233-239",
doi = "10.1016/j.talanta.2005.03.023"
}

Ražić, S., Onjia, A., Đogo-Mračević, S., Slavković, L.,& Popović, A.. (2005). Determination of metal content in some herbal drugs - Empirical and chemometric approach. in Talanta
Elsevier Science BV, Amsterdam., 67(1), 233-239.
https://doi.org/10.1016/j.talanta.2005.03.023

Ražić S, Onjia A, Đogo-Mračević S, Slavković L, Popović A. Determination of metal content in some herbal drugs - Empirical and chemometric approach. in Talanta. 2005;67(1):233-239.
doi:10.1016/j.talanta.2005.03.023 .

Ražić, Slavica, Onjia, Antonije, Đogo-Mračević, Svetlana, Slavković, Latinka, Popović, Aleksandar, "Determination of metal content in some herbal drugs - Empirical and chemometric approach" in Talanta, 67, no. 1 (2005):233-239,
https://doi.org/10.1016/j.talanta.2005.03.023 . .