TY  - CHAP
AU  - Krmar, Jovana
AU  - Svrkota, Bojana
AU  - Đajić, Nevena
AU  - Stojanović, Jevrem
AU  - Protić, Ana
AU  - Otašević, Biljana
PY  - 2023
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/4907
AB  - One-factor-at-a-time experimentation was used for a long time as gold-standard
optimization for liquid chromatographic (LC) method development. This approach
has two downsides as it requires a needlessly great number of experimental runs and it
is unable to identify possible factor interactions. At the end of the last century,
however, this problem could be solved with the introduction of new chemometric
strategies. This chapter aims at presenting quantitative structure–retention relationship
(QSRR) models with structuring possibilities, from the point of feature selection
through various machine learning algorithms that can be used in model building, for
internal and external validation of the proposed models. The presented strategies of
QSRR model can be a good starting point for analysts to use and adopt them as a good
practice for their applications. QSRR models can be used in predicting the retention
behavior of compounds, to point out the molecular features governing the retention,
and consequently to gain insight into the retention mechanisms. In terms of these
applications, special attention was drawn to modified chromatographic systems,
characterized by mobile or stationary phase modifications. Although chromatographic
methods are applied in a wide variety of fields, the greatest attention has been devoted
to the analysis of pharmaceuticals.
PB  - IntechOpen
T2  - Novel Aspects of Gas Chromatography and Chemometrics
T1  - QSRR Approach: Application to Retention Mechanism in Liquid Chromatography
SP  - 113
EP  - 141
DO  - 10.5772/intechopen.106245
ER  - 

@inbook{
author = "Krmar, Jovana and Svrkota, Bojana and Đajić, Nevena and Stojanović, Jevrem and Protić, Ana and Otašević, Biljana",
year = "2023",
abstract = "One-factor-at-a-time experimentation was used for a long time as gold-standard
optimization for liquid chromatographic (LC) method development. This approach
has two downsides as it requires a needlessly great number of experimental runs and it
is unable to identify possible factor interactions. At the end of the last century,
however, this problem could be solved with the introduction of new chemometric
strategies. This chapter aims at presenting quantitative structure–retention relationship
(QSRR) models with structuring possibilities, from the point of feature selection
through various machine learning algorithms that can be used in model building, for
internal and external validation of the proposed models. The presented strategies of
QSRR model can be a good starting point for analysts to use and adopt them as a good
practice for their applications. QSRR models can be used in predicting the retention
behavior of compounds, to point out the molecular features governing the retention,
and consequently to gain insight into the retention mechanisms. In terms of these
applications, special attention was drawn to modified chromatographic systems,
characterized by mobile or stationary phase modifications. Although chromatographic
methods are applied in a wide variety of fields, the greatest attention has been devoted
to the analysis of pharmaceuticals.",
publisher = "IntechOpen",
journal = "Novel Aspects of Gas Chromatography and Chemometrics",
booktitle = "QSRR Approach: Application to Retention Mechanism in Liquid Chromatography",
pages = "113-141",
doi = "10.5772/intechopen.106245"
}

Krmar, J., Svrkota, B., Đajić, N., Stojanović, J., Protić, A.,& Otašević, B.. (2023). QSRR Approach: Application to Retention Mechanism in Liquid Chromatography. in Novel Aspects of Gas Chromatography and Chemometrics
IntechOpen., 113-141.
https://doi.org/10.5772/intechopen.106245

Krmar J, Svrkota B, Đajić N, Stojanović J, Protić A, Otašević B. QSRR Approach: Application to Retention Mechanism in Liquid Chromatography. in Novel Aspects of Gas Chromatography and Chemometrics. 2023;:113-141.
doi:10.5772/intechopen.106245 .

Krmar, Jovana, Svrkota, Bojana, Đajić, Nevena, Stojanović, Jevrem, Protić, Ana, Otašević, Biljana, "QSRR Approach: Application to Retention Mechanism in Liquid Chromatography" in Novel Aspects of Gas Chromatography and Chemometrics (2023):113-141,
https://doi.org/10.5772/intechopen.106245 . .

TY  - JOUR
AU  - Walther, Rasmus
AU  - Krmar, Jovana
AU  - Leistner, Adrian
AU  - Svrkota, Bojana
AU  - Otašević, Biljana
AU  - Malenović, Anđelija
AU  - Holzgrabe, Ulrike
AU  - Protić, Ana
PY  - 2023
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/4698
AB  - An alternative to the time-consuming and error-prone pharmacopoeial gas chromatography method for the analysis of fatty acids (FAs) is urgently needed. The objective was therefore to propose a robust liquid chromatography method with charged aerosol detection for the analysis of polysorbate 80 (PS80) and magnesium stearate. FAs with different numbers of carbon atoms in the chain necessitated the use of a gradient method with a Hypersil Gold C18 column and acetonitrile as organic modifier. The risk-based Analytical Quality by Design approach was applied to define the Method Operable Design Region (MODR). Formic acid concentration, initial and final percentages of acetonitrile, gradient elution time, column temperature, and mobile phase flow rate were identified as critical method parameters (CMPs). The initial and final percentages of acetonitrile were fixed while the remaining CMPs were fine-tuned using response surface methodology. Critical method attributes included the baseline separation of adjacent peaks (α-linolenic and myristic acid, and oleic and petroselinic acid) and the retention factor of the last compound eluted, stearic acid. The MODR was calculated by Monte Carlo simulations with a probability equal or greater than 90%. Finally, the column temperature was set at 33 °C, the flow rate was 0.575 mL/min, and acetonitrile linearly increased from 70 to 80% (v/v) within 14.2 min.
PB  - MDPI
T2  - Pharmaceuticals
T1  - Analytical Quality by Design: Achieving Robustness of an LC-CAD Method for the Analysis of Non-Volatile Fatty Acids
VL  - 16
IS  - 4
DO  - 10.3390/ph16040478
ER  - 

@article{
author = "Walther, Rasmus and Krmar, Jovana and Leistner, Adrian and Svrkota, Bojana and Otašević, Biljana and Malenović, Anđelija and Holzgrabe, Ulrike and Protić, Ana",
year = "2023",
abstract = "An alternative to the time-consuming and error-prone pharmacopoeial gas chromatography method for the analysis of fatty acids (FAs) is urgently needed. The objective was therefore to propose a robust liquid chromatography method with charged aerosol detection for the analysis of polysorbate 80 (PS80) and magnesium stearate. FAs with different numbers of carbon atoms in the chain necessitated the use of a gradient method with a Hypersil Gold C18 column and acetonitrile as organic modifier. The risk-based Analytical Quality by Design approach was applied to define the Method Operable Design Region (MODR). Formic acid concentration, initial and final percentages of acetonitrile, gradient elution time, column temperature, and mobile phase flow rate were identified as critical method parameters (CMPs). The initial and final percentages of acetonitrile were fixed while the remaining CMPs were fine-tuned using response surface methodology. Critical method attributes included the baseline separation of adjacent peaks (α-linolenic and myristic acid, and oleic and petroselinic acid) and the retention factor of the last compound eluted, stearic acid. The MODR was calculated by Monte Carlo simulations with a probability equal or greater than 90%. Finally, the column temperature was set at 33 °C, the flow rate was 0.575 mL/min, and acetonitrile linearly increased from 70 to 80% (v/v) within 14.2 min.",
publisher = "MDPI",
journal = "Pharmaceuticals",
title = "Analytical Quality by Design: Achieving Robustness of an LC-CAD Method for the Analysis of Non-Volatile Fatty Acids",
volume = "16",
number = "4",
doi = "10.3390/ph16040478"
}

Walther, R., Krmar, J., Leistner, A., Svrkota, B., Otašević, B., Malenović, A., Holzgrabe, U.,& Protić, A.. (2023). Analytical Quality by Design: Achieving Robustness of an LC-CAD Method for the Analysis of Non-Volatile Fatty Acids. in Pharmaceuticals
MDPI., 16(4).
https://doi.org/10.3390/ph16040478

Walther R, Krmar J, Leistner A, Svrkota B, Otašević B, Malenović A, Holzgrabe U, Protić A. Analytical Quality by Design: Achieving Robustness of an LC-CAD Method for the Analysis of Non-Volatile Fatty Acids. in Pharmaceuticals. 2023;16(4).
doi:10.3390/ph16040478 .

Walther, Rasmus, Krmar, Jovana, Leistner, Adrian, Svrkota, Bojana, Otašević, Biljana, Malenović, Anđelija, Holzgrabe, Ulrike, Protić, Ana, "Analytical Quality by Design: Achieving Robustness of an LC-CAD Method for the Analysis of Non-Volatile Fatty Acids" in Pharmaceuticals, 16, no. 4 (2023),
https://doi.org/10.3390/ph16040478 . .

TY  - JOUR
AU  - Svrkota, Bojana
AU  - Krmar, Jovana
AU  - Protić, Ana
AU  - Otašević, Biljana
PY  - 2023
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/4414
AB  - Resolving complex sample mixtures by liquid chromatography in a single run is challenging. The so-called mixed-mode liquid chromatography (MMLC) which combines several retention mechanisms within a single column, can provide resource-efficient separation of solutes of diverse nature. The Acclaim Mixed-Mode WCX-1 column, encompassing hydrophobic and weak cation exchange interactions, was employed for the analysis of small drug molecules. The stationary phase's interaction abilities were assessed by analysing molecules of different ionisation potentials. Mixed Quantitative Structure-Retention Relationship (QSRR) models were developed for revealing significant experimental parameters (EPs) and molecular features governing molecular retention. According to the plan of Face-Centred Central Composite Design, EPs (column temperature, acetonitrile content, pH and buffer concentration of aqueous mobile phase) variations were included in QSRR modelling. QSRRs were developed upon the whole data set (global model) and upon discrete parts, related to similarly ionized analytes (local models) by applying gradient boosted trees as a regression tool. Root mean squared errors of prediction for global and local QSRR models for cations, anions and neutrals were respectively 0.131; 0.105; 0.102 and 0.042 with the coefficient of determination 0.947; 0.872; 0.954 and 0.996, indicating satisfactory performances of all models, with slightly better accuracy of local ones. The research showed that influences of EPs were dependant on the molecule's ionisation potential. The molecular descriptors highlighted by models pointed out that electrostatic and hydrophobic interactions and hydrogen bonds participate in the retention process. The molecule's conformation significance was evaluated along with the topological relationship between the interaction centres, explicitly determined for each molecular species through local models. All models showed good molecular retention predictability thus showing potential for facilitating the method development.
PB  - Elsevier B.V.
T2  - Journal of Chromatography A
T1  - The secret of reversed-phase/weak cation exchange retention mechanisms in mixed-mode liquid chromatography applied for small drug molecule analysis
VL  - 1690
DO  - 10.1016/j.chroma.2023.463776
ER  - 

@article{
author = "Svrkota, Bojana and Krmar, Jovana and Protić, Ana and Otašević, Biljana",
year = "2023",
abstract = "Resolving complex sample mixtures by liquid chromatography in a single run is challenging. The so-called mixed-mode liquid chromatography (MMLC) which combines several retention mechanisms within a single column, can provide resource-efficient separation of solutes of diverse nature. The Acclaim Mixed-Mode WCX-1 column, encompassing hydrophobic and weak cation exchange interactions, was employed for the analysis of small drug molecules. The stationary phase's interaction abilities were assessed by analysing molecules of different ionisation potentials. Mixed Quantitative Structure-Retention Relationship (QSRR) models were developed for revealing significant experimental parameters (EPs) and molecular features governing molecular retention. According to the plan of Face-Centred Central Composite Design, EPs (column temperature, acetonitrile content, pH and buffer concentration of aqueous mobile phase) variations were included in QSRR modelling. QSRRs were developed upon the whole data set (global model) and upon discrete parts, related to similarly ionized analytes (local models) by applying gradient boosted trees as a regression tool. Root mean squared errors of prediction for global and local QSRR models for cations, anions and neutrals were respectively 0.131; 0.105; 0.102 and 0.042 with the coefficient of determination 0.947; 0.872; 0.954 and 0.996, indicating satisfactory performances of all models, with slightly better accuracy of local ones. The research showed that influences of EPs were dependant on the molecule's ionisation potential. The molecular descriptors highlighted by models pointed out that electrostatic and hydrophobic interactions and hydrogen bonds participate in the retention process. The molecule's conformation significance was evaluated along with the topological relationship between the interaction centres, explicitly determined for each molecular species through local models. All models showed good molecular retention predictability thus showing potential for facilitating the method development.",
publisher = "Elsevier B.V.",
journal = "Journal of Chromatography A",
title = "The secret of reversed-phase/weak cation exchange retention mechanisms in mixed-mode liquid chromatography applied for small drug molecule analysis",
volume = "1690",
doi = "10.1016/j.chroma.2023.463776"
}

Svrkota, B., Krmar, J., Protić, A.,& Otašević, B.. (2023). The secret of reversed-phase/weak cation exchange retention mechanisms in mixed-mode liquid chromatography applied for small drug molecule analysis. in Journal of Chromatography A
Elsevier B.V.., 1690.
https://doi.org/10.1016/j.chroma.2023.463776

Svrkota B, Krmar J, Protić A, Otašević B. The secret of reversed-phase/weak cation exchange retention mechanisms in mixed-mode liquid chromatography applied for small drug molecule analysis. in Journal of Chromatography A. 2023;1690.
doi:10.1016/j.chroma.2023.463776 .

Svrkota, Bojana, Krmar, Jovana, Protić, Ana, Otašević, Biljana, "The secret of reversed-phase/weak cation exchange retention mechanisms in mixed-mode liquid chromatography applied for small drug molecule analysis" in Journal of Chromatography A, 1690 (2023),
https://doi.org/10.1016/j.chroma.2023.463776 . .

TY  - CONF
AU  - Svrkota, Bojana
AU  - Krmar, Jovana
AU  - Đajić, Nevena
AU  - Protić, Ana
AU  - Otašević, Biljana
PY  - 2022
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/4692
AB  - Introduction: Active pharmaceutical ingredients
(APIs) are often used in salt form, which is why the
inclusion of weak cation exchange (WCX), in
addition to reverse-phased (RP) hydrophobic
interactions, could improve APIs’ separation (1).
Due to the limited knowledge about the RP/WCX
bimodal system, the aim was to elucidate the
experimental factors’ influence on the retention of
diverse ionized APIs, and provide efficient method
optimization.
Materials and Methods: Acidic (ibuprofen (IB),
aceclofenac (AC)) and basic (escitalopram (ES),
aripiprazole (AR), atomoxetine (AT)) analytes were
tested. Chromatography experiments were
performed on Thermo Acclaim Mixed Mode WCX-
1 (5 μm, 3x10 mm) column. Mobile phase
consisted of ACN (30-50% (v/v)) and acetic buffer
(pH 3.8 - 5.6; ionic strength (I) 20-40 mM).
Temperature (T) was varied in range 30–38 °C.
Variations of these factors were conducted
according to Full Factorial Design 24. Optimization
phase was executed by using face-centered
Central Composite Design (Design-Expert 7.0.0).
Results: Screening results showed that %ACN
had the greatest impact on analytes’ retention
factors (k), so increasing in %ACN caused a
decrease in k. T had the same effect, but much less
pronounced. Changes in mobile phase pH affected
k, with the opposite effect on anionic and cationic species. This is attributed to greater ionization of
stationary phases’ carboxylic groups at higher pH.
As consequence, repulsive interactions with
anionic and attractive interactions with the cationic
analytes, are enhanced, vice versa (2). Ionic
strength had much more influence on cationic
analytes than on anionic ones. Due to all the
above, all of four factors were included during
optimization phase. Optimization goals were set so
that k values were in range 1–10 (k(AR)<10,
k(AC)>10, k(IB) in range) and selectivity of critical
peak pair α(AT/ES)>1.3. All derived mathematical
models were statistically estimated (R2, adj. R2,
pred. R2>0.95). Set of optimal conditions which is
47% (v/v) ACN, acetic buffer (40 mМ, pH 3.8) and
temperature 30 °C was determined using
Derringer’s desirability function.
Conclusions: Experimental parameters with
significant influence on retention in bimodal
RP/WCX system were evaluated, and upon that
method was successfully optimized.
PB  - Ankara University Faculty of Pharmacy
C3  - 13th International Symposium on Pharmaceutical Sciences (ISOPS), June 22-25, 2021, Ankara, Turkey
T1  - Chemometrically supported optimization of RP/WCX-HPLC method
SP  - 228
EP  - 229
UR  - https://hdl.handle.net/21.15107/rcub_farfar_4692
ER  - 

@conference{
author = "Svrkota, Bojana and Krmar, Jovana and Đajić, Nevena and Protić, Ana and Otašević, Biljana",
year = "2022",
abstract = "Introduction: Active pharmaceutical ingredients
(APIs) are often used in salt form, which is why the
inclusion of weak cation exchange (WCX), in
addition to reverse-phased (RP) hydrophobic
interactions, could improve APIs’ separation (1).
Due to the limited knowledge about the RP/WCX
bimodal system, the aim was to elucidate the
experimental factors’ influence on the retention of
diverse ionized APIs, and provide efficient method
optimization.
Materials and Methods: Acidic (ibuprofen (IB),
aceclofenac (AC)) and basic (escitalopram (ES),
aripiprazole (AR), atomoxetine (AT)) analytes were
tested. Chromatography experiments were
performed on Thermo Acclaim Mixed Mode WCX-
1 (5 μm, 3x10 mm) column. Mobile phase
consisted of ACN (30-50% (v/v)) and acetic buffer
(pH 3.8 - 5.6; ionic strength (I) 20-40 mM).
Temperature (T) was varied in range 30–38 °C.
Variations of these factors were conducted
according to Full Factorial Design 24. Optimization
phase was executed by using face-centered
Central Composite Design (Design-Expert 7.0.0).
Results: Screening results showed that %ACN
had the greatest impact on analytes’ retention
factors (k), so increasing in %ACN caused a
decrease in k. T had the same effect, but much less
pronounced. Changes in mobile phase pH affected
k, with the opposite effect on anionic and cationic species. This is attributed to greater ionization of
stationary phases’ carboxylic groups at higher pH.
As consequence, repulsive interactions with
anionic and attractive interactions with the cationic
analytes, are enhanced, vice versa (2). Ionic
strength had much more influence on cationic
analytes than on anionic ones. Due to all the
above, all of four factors were included during
optimization phase. Optimization goals were set so
that k values were in range 1–10 (k(AR)<10,
k(AC)>10, k(IB) in range) and selectivity of critical
peak pair α(AT/ES)>1.3. All derived mathematical
models were statistically estimated (R2, adj. R2,
pred. R2>0.95). Set of optimal conditions which is
47% (v/v) ACN, acetic buffer (40 mМ, pH 3.8) and
temperature 30 °C was determined using
Derringer’s desirability function.
Conclusions: Experimental parameters with
significant influence on retention in bimodal
RP/WCX system were evaluated, and upon that
method was successfully optimized.",
publisher = "Ankara University Faculty of Pharmacy",
journal = "13th International Symposium on Pharmaceutical Sciences (ISOPS), June 22-25, 2021, Ankara, Turkey",
title = "Chemometrically supported optimization of RP/WCX-HPLC method",
pages = "228-229",
url = "https://hdl.handle.net/21.15107/rcub_farfar_4692"
}

Svrkota, B., Krmar, J., Đajić, N., Protić, A.,& Otašević, B.. (2022). Chemometrically supported optimization of RP/WCX-HPLC method. in 13th International Symposium on Pharmaceutical Sciences (ISOPS), June 22-25, 2021, Ankara, Turkey
Ankara University Faculty of Pharmacy., 228-229.
https://hdl.handle.net/21.15107/rcub_farfar_4692

Svrkota B, Krmar J, Đajić N, Protić A, Otašević B. Chemometrically supported optimization of RP/WCX-HPLC method. in 13th International Symposium on Pharmaceutical Sciences (ISOPS), June 22-25, 2021, Ankara, Turkey. 2022;:228-229.
https://hdl.handle.net/21.15107/rcub_farfar_4692 .

Svrkota, Bojana, Krmar, Jovana, Đajić, Nevena, Protić, Ana, Otašević, Biljana, "Chemometrically supported optimization of RP/WCX-HPLC method" in 13th International Symposium on Pharmaceutical Sciences (ISOPS), June 22-25, 2021, Ankara, Turkey (2022):228-229,
https://hdl.handle.net/21.15107/rcub_farfar_4692 .

TY  - CONF
AU  - Otašević, Biljana
AU  - Svrkota, Bojana
AU  - Krmar, Jovana
AU  - Protić, Ana
AU  - Zečević, Mira
PY  - 2022
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/4688
AB  - Liquid chromatography which implies that an analyte interacts through several
separation mechanisms (modes) with a stationary phase packed in a single chromatographic
column is called multimodal or mixed-mode chromatography (MMC). Based on the combined
modes, MMC is seen as bimodal (RP/HILIC, RP/IEX, HILIC/IEX) or trimodal (different
RP/HILIC/IEXcombinations) system. Consequently, compounds that encompass wide
spectra of properties (nonpolar, polar, organic, inorganic, ionized and/or non-ionized) can
be chromatographed in a single chromatographic run. The main practical achievement of this
is the reduction of the number of required analyses needed per one complex sample
compared to unimodal chromatographic systems. Therefore, the popularity of MMC grows
rapidly in recent years together with the number of its applications (1). Beside common
quality control issues that include active pharmaceutical ingredients and related substances
analysis and impurity profiling, the range of different analytes which MMC successfully
handles extends to the analyses of drugs in environmental and biological samples, peptides
and proteins. Since nearly half of recently FDA approved pharmaceutical substances are in
the form of a salt, the focus of MMC turned to pharmaceutical counterions analyses as well
(2). However, separations are governed by numerous intermolecular interactions resulting
from specific analyteʼs properties (size, charge, polarity) and mobile phase composition
(aqueous phase ionic strength and pH value, organic solvent content) while the quality of
separation can also be affected by column temperature and mobile phase flow rate.
Eventually, analytical method development is challenging and demands the assistance of
multifactorial optimization strategies such as the design of experiments.
AB  - Tečna hromatografija koja podrazumeva da analit interaguje putem nekoliko
mehanizama razdvajanja (modova) sa stacionarnom fazom upakovanom u jednu istu
hromatografsku kolonu naziva se multimodalna hromatografija (MMC). Na osnovu
kombinovanih modova, MMC se posmatra kao bimodalni (RP/HILIC, RP/IEX, HILIC/IEX) ili
trimodalni (različite RP/HILIC/IEX kombinacije) sistem. Ovo za posledicu ima da jedinjenja
širokog spektra svojstava (nepolarna, polarna, organska, neorganska, jonizovana i/ili
nejonizovana) mogu se hromatografisati u jednom ciklusu hromatografije. Glavni praktični
doprinos ovoga je smanjenje broja potrebnih analiza po jednom složenom uzorku u
poređenju sa unimodalnim hromatografskim sistemima. Zbog toga, popularnost MMC naglo
raste poslednjih godina zajedno sa brojem njenih aplikacija (1). Pored uobičajenih pitanja
kontrole kvaliteta koja uključuju analizu aktivnih farmaceutskih sastojaka i srodnih
supstanci i profilisanje nečistoća, opseg različitih analita sa kojima MMC uspešno pokriva
proširen je analitikom lekova iz prirodnog okruženja i bioloških uzoraka, peptidima i
proteinima. Pošto je skoro polovina farmaceutskih supstanci koje je nedavno FDA odobrila u
obliku soli, fokus MMC je orjentisan i ka analizi farmaceutskih kontrajona (2). Međutim,
hromatografsko razdvajanje je vođeno brojnim intermolekularnim interakcijima koje su
rezultat specifičnih svojstava analita (veličina, naelektrisanje, polaritet) i mobilne faze
(jonska jačina i pH vrednost vodene faze, sadržaj organskog rastvarača), dok na kvalitet
razdvajanja može uticati i temperatura kolone i brzina protoka mobilne faze. Na kraju, razvoj
analitičkih metoda predstavlja izazov i zahteva podršku u strategijama multifaktorske
optimizacije kao što je dizajn eksperimenata.
PB  - Savez farmaceutskih udruženja Srbije (SFUS)
C3  - Arhiv za farmaciju
T1  - The use of multimodal chromatography in the control of pharmaceutical products: New possibilities and new challenges
T1  - Primena multimodalne hromatografije u kontroli farmaceutskih proizvoda: Nove mogućnosti i novi izazovi
VL  - 72
IS  - suppl. 4
SP  - 57
EP  - 58
UR  - https://hdl.handle.net/21.15107/rcub_farfar_4688
ER  - 

@conference{
author = "Otašević, Biljana and Svrkota, Bojana and Krmar, Jovana and Protić, Ana and Zečević, Mira",
year = "2022",
abstract = "Liquid chromatography which implies that an analyte interacts through several
separation mechanisms (modes) with a stationary phase packed in a single chromatographic
column is called multimodal or mixed-mode chromatography (MMC). Based on the combined
modes, MMC is seen as bimodal (RP/HILIC, RP/IEX, HILIC/IEX) or trimodal (different
RP/HILIC/IEXcombinations) system. Consequently, compounds that encompass wide
spectra of properties (nonpolar, polar, organic, inorganic, ionized and/or non-ionized) can
be chromatographed in a single chromatographic run. The main practical achievement of this
is the reduction of the number of required analyses needed per one complex sample
compared to unimodal chromatographic systems. Therefore, the popularity of MMC grows
rapidly in recent years together with the number of its applications (1). Beside common
quality control issues that include active pharmaceutical ingredients and related substances
analysis and impurity profiling, the range of different analytes which MMC successfully
handles extends to the analyses of drugs in environmental and biological samples, peptides
and proteins. Since nearly half of recently FDA approved pharmaceutical substances are in
the form of a salt, the focus of MMC turned to pharmaceutical counterions analyses as well
(2). However, separations are governed by numerous intermolecular interactions resulting
from specific analyteʼs properties (size, charge, polarity) and mobile phase composition
(aqueous phase ionic strength and pH value, organic solvent content) while the quality of
separation can also be affected by column temperature and mobile phase flow rate.
Eventually, analytical method development is challenging and demands the assistance of
multifactorial optimization strategies such as the design of experiments., Tečna hromatografija koja podrazumeva da analit interaguje putem nekoliko
mehanizama razdvajanja (modova) sa stacionarnom fazom upakovanom u jednu istu
hromatografsku kolonu naziva se multimodalna hromatografija (MMC). Na osnovu
kombinovanih modova, MMC se posmatra kao bimodalni (RP/HILIC, RP/IEX, HILIC/IEX) ili
trimodalni (različite RP/HILIC/IEX kombinacije) sistem. Ovo za posledicu ima da jedinjenja
širokog spektra svojstava (nepolarna, polarna, organska, neorganska, jonizovana i/ili
nejonizovana) mogu se hromatografisati u jednom ciklusu hromatografije. Glavni praktični
doprinos ovoga je smanjenje broja potrebnih analiza po jednom složenom uzorku u
poređenju sa unimodalnim hromatografskim sistemima. Zbog toga, popularnost MMC naglo
raste poslednjih godina zajedno sa brojem njenih aplikacija (1). Pored uobičajenih pitanja
kontrole kvaliteta koja uključuju analizu aktivnih farmaceutskih sastojaka i srodnih
supstanci i profilisanje nečistoća, opseg različitih analita sa kojima MMC uspešno pokriva
proširen je analitikom lekova iz prirodnog okruženja i bioloških uzoraka, peptidima i
proteinima. Pošto je skoro polovina farmaceutskih supstanci koje je nedavno FDA odobrila u
obliku soli, fokus MMC je orjentisan i ka analizi farmaceutskih kontrajona (2). Međutim,
hromatografsko razdvajanje je vođeno brojnim intermolekularnim interakcijima koje su
rezultat specifičnih svojstava analita (veličina, naelektrisanje, polaritet) i mobilne faze
(jonska jačina i pH vrednost vodene faze, sadržaj organskog rastvarača), dok na kvalitet
razdvajanja može uticati i temperatura kolone i brzina protoka mobilne faze. Na kraju, razvoj
analitičkih metoda predstavlja izazov i zahteva podršku u strategijama multifaktorske
optimizacije kao što je dizajn eksperimenata.",
publisher = "Savez farmaceutskih udruženja Srbije (SFUS)",
journal = "Arhiv za farmaciju",
title = "The use of multimodal chromatography in the control of pharmaceutical products: New possibilities and new challenges, Primena multimodalne hromatografije u kontroli farmaceutskih proizvoda: Nove mogućnosti i novi izazovi",
volume = "72",
number = "suppl. 4",
pages = "57-58",
url = "https://hdl.handle.net/21.15107/rcub_farfar_4688"
}

Otašević, B., Svrkota, B., Krmar, J., Protić, A.,& Zečević, M.. (2022). The use of multimodal chromatography in the control of pharmaceutical products: New possibilities and new challenges. in Arhiv za farmaciju
Savez farmaceutskih udruženja Srbije (SFUS)., 72(suppl. 4), 57-58.
https://hdl.handle.net/21.15107/rcub_farfar_4688

Otašević B, Svrkota B, Krmar J, Protić A, Zečević M. The use of multimodal chromatography in the control of pharmaceutical products: New possibilities and new challenges. in Arhiv za farmaciju. 2022;72(suppl. 4):57-58.
https://hdl.handle.net/21.15107/rcub_farfar_4688 .

Otašević, Biljana, Svrkota, Bojana, Krmar, Jovana, Protić, Ana, Zečević, Mira, "The use of multimodal chromatography in the control of pharmaceutical products: New possibilities and new challenges" in Arhiv za farmaciju, 72, no. suppl. 4 (2022):57-58,
https://hdl.handle.net/21.15107/rcub_farfar_4688 .

TY  - JOUR
AU  - Svrkota, Bojana
AU  - Krmar, Jovana
AU  - Protić, Ana
AU  - Zečević, Mira
AU  - Otašević, Biljana
PY  - 2022
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/4330
AB  - A new optimization strategy based on the mixed quantitative struc- ture–retention relationship (QSRR) model is proposed for improving the RP- HPLC separation of aripiprazole and its impurities (IMP A-E). Firstly, experi- mental parameters (EPs), namely mobile phase composition and flow rate, were varied according to Box–Behnken design and thereafter, an artificial neural network (ANN) as a QSRR model was built correlating EPs and sel- ected molecular descriptors (ovality, torsion energy and non-1,4-van der Waals energy) with the log-transformed retention times of the analytes. Values of the root mean square error (RMSE) were used for an estimation of the quality of the ANNs (0.0227, 0.0191 and 0.0230 for the training, verification and test set, respectively). The separations of critical peak pairs on chromatogram (IMP A- B and IMP D-C) were optimized using ANNs for which the EPs served as inputs and the log-transformed separation criteria s as the outputs. They were validated by application of leave-one-out cross-validation (RMSE values 0.065 and 0.056, respectively). The obtained ANNs were used for plotting response surfaces upon which the analyses chromatographic conditions resulting in optimal analytes retention behaviour and the optimal values of the separation criteria s were defined. The optimal conditions were 54 % of methanol at the beginning and 79 % of methanol at the end of gradient elution programme with a mobile phase flow rate of 460 μL min-1
AB  - Нова оптимизациона стратегија заснована на грађењу мешовитих модела за кван- тификовање односа структуре и ретенционог понашања (QSRR) предложена је за уна- пређење RP-HPLC раздвајања арипипразола и његових нечистоћа (IMP А-Е). Експери- ментални параметри (EP), састав мобилне фазе и брзина протока, варирани су најпре у складу са Box–Behnken дизајном, а затим је награђена вештачка неуронска мрежа као QSRR модел који повезује ЕP и одабране молекуларне дескрипторе (овалност, торзиона енергија и не-1,4-ван дер Валсова енергија) са логаритамски трансформисаним ретен- ционим временом аналита. Вредности средње квадратне грешке (RMSE) коришћене су за процену квалитета мреже (0,0227, 0,0191 и 0,0230 за тренинг, верификацију и тест сет, редом). Раздвајање критичних парова пикова на хроматограму (IMP А-B и IMP D-C) оптимизовано је коришћењем мрежа за које су ЕP послужили као улази, а логаритамски трансформисани критеријуми сепарације s као излази. Ове мреже су валидиране при- меном унакрсне валидације изостанка (RMSE вредности, редом, 0,065 и 0,056). На основу награђених мрежа, конструисани су дијаграми површина одговора чијом ана- лизом су дефинисани услови при којима се постиже оптимална ретенција аналита, односно вредности критеријума сепарације s, а који су подразумевали 54 % метанола на почетку и 79 % на крају програма градијентног елуирања са брзином протока мобилне фазе од 460 mL min -1
PB  - Serbian Chemical Society
T2  - Journal of the Serbian Chemical Society
T1  - Optimization of chromatographic separation of aripiprazole and impurities: Quantitative structure-retention relationship approach
T1  - Оптимизација хроматографског раздвајања арипипразола и нечистоћа: приступ квантификовања односа структуре и ретенционог понашања
VL  - 87
IS  - 5
SP  - 615
EP  - 628
DO  - 10.2298/JSC210709092S
ER  - 

@article{
author = "Svrkota, Bojana and Krmar, Jovana and Protić, Ana and Zečević, Mira and Otašević, Biljana",
year = "2022",
abstract = "A new optimization strategy based on the mixed quantitative struc- ture–retention relationship (QSRR) model is proposed for improving the RP- HPLC separation of aripiprazole and its impurities (IMP A-E). Firstly, experi- mental parameters (EPs), namely mobile phase composition and flow rate, were varied according to Box–Behnken design and thereafter, an artificial neural network (ANN) as a QSRR model was built correlating EPs and sel- ected molecular descriptors (ovality, torsion energy and non-1,4-van der Waals energy) with the log-transformed retention times of the analytes. Values of the root mean square error (RMSE) were used for an estimation of the quality of the ANNs (0.0227, 0.0191 and 0.0230 for the training, verification and test set, respectively). The separations of critical peak pairs on chromatogram (IMP A- B and IMP D-C) were optimized using ANNs for which the EPs served as inputs and the log-transformed separation criteria s as the outputs. They were validated by application of leave-one-out cross-validation (RMSE values 0.065 and 0.056, respectively). The obtained ANNs were used for plotting response surfaces upon which the analyses chromatographic conditions resulting in optimal analytes retention behaviour and the optimal values of the separation criteria s were defined. The optimal conditions were 54 % of methanol at the beginning and 79 % of methanol at the end of gradient elution programme with a mobile phase flow rate of 460 μL min-1, Нова оптимизациона стратегија заснована на грађењу мешовитих модела за кван- тификовање односа структуре и ретенционог понашања (QSRR) предложена је за уна- пређење RP-HPLC раздвајања арипипразола и његових нечистоћа (IMP А-Е). Експери- ментални параметри (EP), састав мобилне фазе и брзина протока, варирани су најпре у складу са Box–Behnken дизајном, а затим је награђена вештачка неуронска мрежа као QSRR модел који повезује ЕP и одабране молекуларне дескрипторе (овалност, торзиона енергија и не-1,4-ван дер Валсова енергија) са логаритамски трансформисаним ретен- ционим временом аналита. Вредности средње квадратне грешке (RMSE) коришћене су за процену квалитета мреже (0,0227, 0,0191 и 0,0230 за тренинг, верификацију и тест сет, редом). Раздвајање критичних парова пикова на хроматограму (IMP А-B и IMP D-C) оптимизовано је коришћењем мрежа за које су ЕP послужили као улази, а логаритамски трансформисани критеријуми сепарације s као излази. Ове мреже су валидиране при- меном унакрсне валидације изостанка (RMSE вредности, редом, 0,065 и 0,056). На основу награђених мрежа, конструисани су дијаграми површина одговора чијом ана- лизом су дефинисани услови при којима се постиже оптимална ретенција аналита, односно вредности критеријума сепарације s, а који су подразумевали 54 % метанола на почетку и 79 % на крају програма градијентног елуирања са брзином протока мобилне фазе од 460 mL min -1",
publisher = "Serbian Chemical Society",
journal = "Journal of the Serbian Chemical Society",
title = "Optimization of chromatographic separation of aripiprazole and impurities: Quantitative structure-retention relationship approach, Оптимизација хроматографског раздвајања арипипразола и нечистоћа: приступ квантификовања односа структуре и ретенционог понашања",
volume = "87",
number = "5",
pages = "615-628",
doi = "10.2298/JSC210709092S"
}

Svrkota, B., Krmar, J., Protić, A., Zečević, M.,& Otašević, B.. (2022). Optimization of chromatographic separation of aripiprazole and impurities: Quantitative structure-retention relationship approach. in Journal of the Serbian Chemical Society
Serbian Chemical Society., 87(5), 615-628.
https://doi.org/10.2298/JSC210709092S

Svrkota B, Krmar J, Protić A, Zečević M, Otašević B. Optimization of chromatographic separation of aripiprazole and impurities: Quantitative structure-retention relationship approach. in Journal of the Serbian Chemical Society. 2022;87(5):615-628.
doi:10.2298/JSC210709092S .

Svrkota, Bojana, Krmar, Jovana, Protić, Ana, Zečević, Mira, Otašević, Biljana, "Optimization of chromatographic separation of aripiprazole and impurities: Quantitative structure-retention relationship approach" in Journal of the Serbian Chemical Society, 87, no. 5 (2022):615-628,
https://doi.org/10.2298/JSC210709092S . .

TY  - JOUR
AU  - Stojanović, Jevrem
AU  - Krmar, Jovana
AU  - Protić, Ana
AU  - Svrkota, Bojana
AU  - Đajić, Nevena
AU  - Otašević, Biljana
PY  - 2021
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/3951
AB  - Design of Experiments (DoE) is an indispensable tool in contemporary drug analysis as it
simultaneously balances a number of chromatographic parameters to ensure optimal separation
in High Pressure Liquid Chromatography (HPLC). This manuscript briefly outlines the theoretical
background of the DoE and provides step-by-step instruction for its implementation in HPLC
pharmaceutical practice. It particularly discusses the classification of various design types and
their possibilities to rationalize the different stages of HPLC method development workflow, such
as the selection of the most influential factors, factors optimization and assessment of the method
robustness. Additionally, the application of the DoE-based Analytical Quality by Design (AQbD)
concept in the LC method development has been summarized. Recent achievements in the use of
DoE in the development of stability-indicating LC and hyphenated LC-MS methods have also
been briefly reported. Performing of Quantitative structure retention relationship (QSRR) study
enhanced with DoE-based data collection was recomended as a future perspective in description
of retention in HPLC system.
AB  - Dizajn eksperimenata (DoE) je nezaobilazan alat u savremenoj analizi lekova budući da istovremeno balansira niz hromatografskih parametara kako bi se osiguralo optimalno razdvajanje u tečnoj hromatografiji pod visokim pritiskom (HPLC). Prikazana je teorijska osnova DOE i data su detaljna uputstva za njegovu primenu u HPLC ispitivanjima u farmaciji. Naročito se govori o klasifikaciji brojnih tipova dizajna i njihovim mogućnostima za racionalizaciju različitih faza tokom procesa razvoja HPLC metode, kao što su izbor najuticajnijih faktora, optimizacija faktora i procena robusnosti metode. Dodatno, sumirana je primena DOE kao sastavnog dela koncepta ugradnje kvaliteta u proizvod u domenu razvoja analitičkih metoda (AQbD) zasnovanih na HPLC tehnici. Takođe su prikazana i nedavna dostignuća u primeni DOE u razvoju LC metoda koje su pogodne za ispitivanje stabilnosti lekova, kao i LC-MS metoda. U budućoj perspektivi, preporučeno je izvođenje ispitivanja kvantitativnog odnosa između strukture i retencionog ponašanja (QSRR) analita u HPLC sistemu na osnovu podataka dobijenih primenom DOE.
PB  - Beograd : Savez farmaceutskih udruženja Srbije
T2  - Arhiv za farmaciju
T1  - Experimental design in HPLC separation of pharmaceuticals
T1  - Primena eksperimentalnog dizajna za razdvajanje lekova HPLC metodom
VL  - 71
IS  - 4
SP  - 279
EP  - 301
DO  - 10.5937/arhfarm71-32480
ER  - 

@article{
author = "Stojanović, Jevrem and Krmar, Jovana and Protić, Ana and Svrkota, Bojana and Đajić, Nevena and Otašević, Biljana",
year = "2021",
abstract = "Design of Experiments (DoE) is an indispensable tool in contemporary drug analysis as it
simultaneously balances a number of chromatographic parameters to ensure optimal separation
in High Pressure Liquid Chromatography (HPLC). This manuscript briefly outlines the theoretical
background of the DoE and provides step-by-step instruction for its implementation in HPLC
pharmaceutical practice. It particularly discusses the classification of various design types and
their possibilities to rationalize the different stages of HPLC method development workflow, such
as the selection of the most influential factors, factors optimization and assessment of the method
robustness. Additionally, the application of the DoE-based Analytical Quality by Design (AQbD)
concept in the LC method development has been summarized. Recent achievements in the use of
DoE in the development of stability-indicating LC and hyphenated LC-MS methods have also
been briefly reported. Performing of Quantitative structure retention relationship (QSRR) study
enhanced with DoE-based data collection was recomended as a future perspective in description
of retention in HPLC system., Dizajn eksperimenata (DoE) je nezaobilazan alat u savremenoj analizi lekova budući da istovremeno balansira niz hromatografskih parametara kako bi se osiguralo optimalno razdvajanje u tečnoj hromatografiji pod visokim pritiskom (HPLC). Prikazana je teorijska osnova DOE i data su detaljna uputstva za njegovu primenu u HPLC ispitivanjima u farmaciji. Naročito se govori o klasifikaciji brojnih tipova dizajna i njihovim mogućnostima za racionalizaciju različitih faza tokom procesa razvoja HPLC metode, kao što su izbor najuticajnijih faktora, optimizacija faktora i procena robusnosti metode. Dodatno, sumirana je primena DOE kao sastavnog dela koncepta ugradnje kvaliteta u proizvod u domenu razvoja analitičkih metoda (AQbD) zasnovanih na HPLC tehnici. Takođe su prikazana i nedavna dostignuća u primeni DOE u razvoju LC metoda koje su pogodne za ispitivanje stabilnosti lekova, kao i LC-MS metoda. U budućoj perspektivi, preporučeno je izvođenje ispitivanja kvantitativnog odnosa između strukture i retencionog ponašanja (QSRR) analita u HPLC sistemu na osnovu podataka dobijenih primenom DOE.",
publisher = "Beograd : Savez farmaceutskih udruženja Srbije",
journal = "Arhiv za farmaciju",
title = "Experimental design in HPLC separation of pharmaceuticals, Primena eksperimentalnog dizajna za razdvajanje lekova HPLC metodom",
volume = "71",
number = "4",
pages = "279-301",
doi = "10.5937/arhfarm71-32480"
}

Stojanović, J., Krmar, J., Protić, A., Svrkota, B., Đajić, N.,& Otašević, B.. (2021). Experimental design in HPLC separation of pharmaceuticals. in Arhiv za farmaciju
Beograd : Savez farmaceutskih udruženja Srbije., 71(4), 279-301.
https://doi.org/10.5937/arhfarm71-32480

Stojanović J, Krmar J, Protić A, Svrkota B, Đajić N, Otašević B. Experimental design in HPLC separation of pharmaceuticals. in Arhiv za farmaciju. 2021;71(4):279-301.
doi:10.5937/arhfarm71-32480 .

Stojanović, Jevrem, Krmar, Jovana, Protić, Ana, Svrkota, Bojana, Đajić, Nevena, Otašević, Biljana, "Experimental design in HPLC separation of pharmaceuticals" in Arhiv za farmaciju, 71, no. 4 (2021):279-301,
https://doi.org/10.5937/arhfarm71-32480 . .

TY  - CONF
AU  - Otašević, Biljana
AU  - Svrkota, Bojana
AU  - Krmar, Jovana
AU  - Protić, Ana
AU  - Zečević, Mira
PY  - 2021
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/4693
AB  - Liquid chromatography system in which several separation mechanisms are integrated in the
composition of a single column is called multimodal or mixed-mode chromatography (MMC). MMC
systems are classified based on combined separation mechanisms as bimodal (RP/HILIC, RP/IEX,
HILIC/IEX) and trimodal (different combinations of RP/HILIC/IEX). The main benefit of MMC lies
in widening the spectra of properties of analytes that can be simultaneously chromatographed
(nonpolar, polar, organic, inorganic, ionized and / or non-ionized analytes). In this way, it is possible
to reduce the number of required analyses for one complex sample compared to unimodal
chromatographic systems. For that reason, the popularity of MMC has been growing fast in recent
years. However, in line with this achievement, MMC is characterized by large number of
intermolecular interactions governing separations which are related to the properties of the analyte
(charge and polarity) and chromatographic conditions (ionic strength and the pH of the aqueous phase
and the content of the organic solvent) [1]. In order to get insight into relative contribution of
aforementioned factors to retention of selected group of analytes, preferred chemometric approach is
Quantitative Structure Retention Relationship (QSRR) study. The QSRR models relate the physicalchemical
properties of analytes reflected by assigned molecular descriptors with their retention
behaviour in predefined experimental space described by the range of chromatographic conditions
(instrumental and mobile phase composition related factors). Apart from its general purpose to assist
in the characterization of observed chromatographic system, the reliable predictions of retention
behaviour of so-called system blind analytes (analytes of known chemical structure but not subjected
to experimentations) can also be derived from a QSRR model. In such way, the development of MMC
based analytical method can be rationalized by saving time and other resources [2].
This research demonstrates the QSRR study performed on 31 pharmaceuticals covering wide range
of polarities, acid-base properties and divergent retention in RP/WCX system (Thermo Acclaim
Mixed Mode WCX-1 3 μm, 2.1x150 mm column). This system was subjected to variations of the
mobile phase composition (30-50% (v/v) of acetonitrile; 3.8-5.6 pH value and 20-40 mM ionic
strength of acetic buffer) and column temperature (30–38 °C) according to the plan of central
composite design of experiments. The machine learning algorithm based on Artificial Neural
Network was used for relating these independent variables to cube root transformed retention factors
of analytes as observed responses. The network comprising of 11-7-1 topology was trained through
1200 cycles with learning rate set at 0.3 and momentum set at 0.5. Cross validation and external
validation were used to prove good statistical performances of built model (Root Mean Square Error
values 0.131 and 0.147 and Squared Correlation vales 0.963 and 0.944, respectively). According to
the weighting scheme used, volume fraction of acetonitrile, pH of aqueous phase and descriptors
related to hydrophobicity and molecule size demonstrated the greatest impact towards retention in
MMC.
PB  - Aristotle University of Thessaloniki
PB  - National Technical University of Athens
C3  - 12th International Conference on Instrumental Methods of Analysis, Modern Trends and Applications, 20-23 September 2021, Virtual event
T1  - QSRR driven insight into retention in multimodal chromatography
SP  - 50
EP  - 50
UR  - https://hdl.handle.net/21.15107/rcub_farfar_4693
ER  - 

@conference{
author = "Otašević, Biljana and Svrkota, Bojana and Krmar, Jovana and Protić, Ana and Zečević, Mira",
year = "2021",
abstract = "Liquid chromatography system in which several separation mechanisms are integrated in the
composition of a single column is called multimodal or mixed-mode chromatography (MMC). MMC
systems are classified based on combined separation mechanisms as bimodal (RP/HILIC, RP/IEX,
HILIC/IEX) and trimodal (different combinations of RP/HILIC/IEX). The main benefit of MMC lies
in widening the spectra of properties of analytes that can be simultaneously chromatographed
(nonpolar, polar, organic, inorganic, ionized and / or non-ionized analytes). In this way, it is possible
to reduce the number of required analyses for one complex sample compared to unimodal
chromatographic systems. For that reason, the popularity of MMC has been growing fast in recent
years. However, in line with this achievement, MMC is characterized by large number of
intermolecular interactions governing separations which are related to the properties of the analyte
(charge and polarity) and chromatographic conditions (ionic strength and the pH of the aqueous phase
and the content of the organic solvent) [1]. In order to get insight into relative contribution of
aforementioned factors to retention of selected group of analytes, preferred chemometric approach is
Quantitative Structure Retention Relationship (QSRR) study. The QSRR models relate the physicalchemical
properties of analytes reflected by assigned molecular descriptors with their retention
behaviour in predefined experimental space described by the range of chromatographic conditions
(instrumental and mobile phase composition related factors). Apart from its general purpose to assist
in the characterization of observed chromatographic system, the reliable predictions of retention
behaviour of so-called system blind analytes (analytes of known chemical structure but not subjected
to experimentations) can also be derived from a QSRR model. In such way, the development of MMC
based analytical method can be rationalized by saving time and other resources [2].
This research demonstrates the QSRR study performed on 31 pharmaceuticals covering wide range
of polarities, acid-base properties and divergent retention in RP/WCX system (Thermo Acclaim
Mixed Mode WCX-1 3 μm, 2.1x150 mm column). This system was subjected to variations of the
mobile phase composition (30-50% (v/v) of acetonitrile; 3.8-5.6 pH value and 20-40 mM ionic
strength of acetic buffer) and column temperature (30–38 °C) according to the plan of central
composite design of experiments. The machine learning algorithm based on Artificial Neural
Network was used for relating these independent variables to cube root transformed retention factors
of analytes as observed responses. The network comprising of 11-7-1 topology was trained through
1200 cycles with learning rate set at 0.3 and momentum set at 0.5. Cross validation and external
validation were used to prove good statistical performances of built model (Root Mean Square Error
values 0.131 and 0.147 and Squared Correlation vales 0.963 and 0.944, respectively). According to
the weighting scheme used, volume fraction of acetonitrile, pH of aqueous phase and descriptors
related to hydrophobicity and molecule size demonstrated the greatest impact towards retention in
MMC.",
publisher = "Aristotle University of Thessaloniki, National Technical University of Athens",
journal = "12th International Conference on Instrumental Methods of Analysis, Modern Trends and Applications, 20-23 September 2021, Virtual event",
title = "QSRR driven insight into retention in multimodal chromatography",
pages = "50-50",
url = "https://hdl.handle.net/21.15107/rcub_farfar_4693"
}

Otašević, B., Svrkota, B., Krmar, J., Protić, A.,& Zečević, M.. (2021). QSRR driven insight into retention in multimodal chromatography. in 12th International Conference on Instrumental Methods of Analysis, Modern Trends and Applications, 20-23 September 2021, Virtual event
Aristotle University of Thessaloniki., 50-50.
https://hdl.handle.net/21.15107/rcub_farfar_4693

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