Оптимизација хроматографског раздвајања арипипразола и нечистоћа: приступ квантификовања односа структуре и ретенционог понашања

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-1Нова 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 -

Izgradnja QSRR modela za razvoj RP/WCX HPLC metode

Reverse-phase high-performance liquid chromatography (RP-HPLC) is most common in pharmaceutical analysis and requires significant consumption of toxic mobile phase. Therefore, more eco-friendly solutions are preferred (1). When it comes to complex samples, RP-HPLC, due to inability to separate highly polar and charged analytes, often requires multiple unimodal or two-dimensional HPLC analyzes. The development of mixed-mode liquid chromatography (MMLC), where multiple separation modalities are incorporated into a single stationary phase, allows the separation of complex samples in a single run. Numerous factors affect MMLC separation, which makes method development demanding and limits their practical application (2). Building predictive mathematical models, such as Quantitative structure-retention relationship (QSRR), could improve method development. QSRR links the molecules’ retention behavior with their physicochemical properties (molecular descriptors (MD)), which allows retention behavior prediction of untested analytes. Including experimental parameter values in the QSRR extends the predictability of the model to entire experimental space (3). For model development purposes, experiments were performed on Thermo’s Acclaim Mixed-Mode WCX-1 (3 μm, 2.1 x 150 mm) column which combines hydrophobic and weak cation exchange (WCX) interactions. Small diameter column agrees with low mobile phase flow rate (400 μl/min). Mobile phase composition (acetonitrile content (30 – 50 % (v/v)), pH (3.8 - 5.6) and ionic strength (20 - 40 mM) of acetic buffer) and column temperature (30 – 38 °C) were varied according to face-centered central composite design. Retention factor of 33 pharmaceuticals of different pharmacological and ionization properties were monitored. MDs were calculated using AlvaDesc software. RapidMiner software was used for obtaining QSRR models. Several machine learning algorithms were considered and the most informative (gradient boosted trees (GBT) and bagging neural network (BNN)) were selected. Models were built upon data of 30 analytes, and the remaining three (anion, cation, neutral) were used as a test set. The most influential MDs for BNN were chosen by forward selection, contrary to GBT which did not require preselection. For internal model evaluation 10-fold cross-validation was applied, while external was performed with a test set. Models were compared based on the relative mean square error (RMSE) of the test set. The BNN (RMSE = 0.104; R2 = 0.976) model outperformed GBT (RMSE = 0.122; R2 = 0.963). The obtained QSRR models showed good potential to predict the retention behavior of molecules of different ionization abilities in the RP/WCX system. This could improve the development of MMLC methods and make them more accessible for practical use.U farmaceutskim analizama najzastupljenija je reverzno-fazna tečna hromatografija visokih performansi (reverse‐phase high‐performance liquid chromatography (RP-HPLC)) koja iziskuje značajnu potrošnju mobilne faze toksične prirode. Iz tog razloga, teži se ekološki prihvatljivijim rešenjima (1). Kada su u pitanju kompleksne smeše uzorka, RP-HPLC zbog nemogućnosti sparacije visoko polarnih i naelektrisanih analita, često zahteva više unimodalnih ili dvodimenzionalne HPLC analize. Razvoj multimodalne tečne hromatografije (mixed‐mode liquid chromatography (MMLC)) koja podrazumeva više separacionih modaliteta inkorporiranih u jednu stacionarnu fazu, omogućava razdvajanje složenih uzorka jedinstvenom analizom. Brojni faktori utiču na MMLC separaciju, što razvoj metoda čini zahtevnim i ograničava im praktičnu primenu (2). Izgradnja prediktivnih matematičkih modela, kao što su modeli kvantitativnog odnos strukture i retencionog ponašanja (Quantitative structure‐retention relationship (QSRR)), može ubrzati razvoj metode. QSRR povezuje fizičko-hemijska svojstva (molekulski deskriptori (MD)) sa retencionim ponašanjem molekula, što omogućava predviđanje retencionog ponašanja neispitanih analita. Uključivanje vrednosti eksperimentalnih parametara u QSRR, proširuje prediktivnost modela na ceo eksperimentalni prostor (3). Podaci o retencionom ponašanju za potrebe razvoja QSRR modela, dobijeni su upotrebom Thermo Acclaim Mixed‐Mode WCX‐1 (3 μm; 2,1x150 mm) kolone koja uključuje hirdrofobne i interakcije slabe katjonske izmene (weak cation exchange (WCX)). Malim prečnikom kolone omoguć en je nizak protok i utrošak mobilne faze (400 μl/min). Sastav mobilne faze (udeo ACN (30 – 50 % (v/v)), pH (3,8 – 5,6) i jonska jačina (20 – 40 mM) acetatnog pufera) i temperatura kolone (30 – 38 °C) menjani su u skladu sa centralnim kompozicionim dizajnom – ka centru orijentisanim. Praćen je retencioni faktor 33 farmaceutska jedinjenja različitih farmakoloških i jonizacionih osobina. MD su računati AlvaDesc softverom. Za izgradnju QSRR modela RapidMiner softverom razmatrana je nekolicina algoritama mašinskog učenja, a odabrani su najinformativniji (gradient boosted trees (GBT) i bagging neural networks (BNN)). Modeli su građeni na osnovu podataka za 30 analita, dok su preostala tri (anjon, katjon, neutralni) odabrani za test set. Selekcijom unapred odabrani su najznačajniji MD za izgradnju BNN, za razliku od GBT koji ne zahteva preselekciju MD. Interna procena modela vršena je desetostrukom unakrsnom validacijom (10‐fold cross‐validation), dok je eksterna vršena test setom podataka. Modeli su upoređeni na osnovu relativne srednje kvadratne greške (RMSE) test seta. BNN (RMSE = 0,104; R 2 = 0,976) se pokazao boljim u poređenju sa GBT (RMSE = 0,112; R 2 = 0,963). Dobijeni QSRR modeli pokazali su dobru sposobnost predviđanja retencionog ponašanja molekula različitih jonizacionih sposobnosti u RP/WCX sistemu. Tako bi mogao da se unapredi razvoj MMLC metoda i učini ih pristupačnijim za praktičnu upotrebu.Drugi naučni simpozijum Saveza farmaceutskih udruženja Srbije sa međunarodnim učešćem, 28. 10. 2021. Beogra

Robustan razvoj metode multimodalne hromatografije primenom principa ugrađivanja kvaliteta kroz dizajn za analizu odabarnih lekova

Mixed-Mode Liquid Chromatography (MMLC) includes several separation mechanisms in a single column, which is why MMLC can analyze compounds in a broad range of polarities and ionization potentials in a single run (1). Acclaim Mixed-Mode WCX-1 column with the ability to expose hydrophobic and weak cation exchange interactions was thus selected to analyse a challenging mixture of neutral and cationic forms: ergotamine, mecloxamine, camylofin, caffeine and propyphenazone, used as a fixed combination. MMLC method was developed in line with Analytical Quality by Design (AQbD) approach implying the scientifically-based understanding of process properties and risk-based management of the method life cycle. AQbD refers to pre-definition of the method’s Analytical Target Profile (ATP) by means of baseline separations within the shortest possible time, as well as definition of Critical Method Attributes (CMAs) as a measure of method quality and Critical Method Parameters (CMPs) affecting CMAs (2). Acetonitrile content, pH and acetate buffer concentration were selected as CMPs since retention mechanism expression in MMLC strongly depends on the mobile phase characteristics. The dependence of CMAs on CMPs was revealed following a face-centred central composition design plan of experiments and accompanying mathematical models, coefficients and standard error values. Design Space in which ATP is achieved with a high level of reliability (π = 90%), was determined by Monte Carlo simulations taking error distribution into account. Its margins pointed out to the working point that assures proper method robustness (pH 5.2, 90 mM acetate buffer solution and 48% (v/v) of acetonitrile).Multimodalna tečna hromatografija (Mixed‐Mode Liquid Chromatography – MMLC) uključuje nekoliko mehanizama razdvajanja u jednoj koloni, zbog čega se ova tehnika može koristiti za simultanu analizu jedinjenja širokog opsega polarnosti i jonizacionog potencijala (1). Acclaim Mixed‐Mode WCX‐1 kolona sa sposobnošću ekspresije hidrofobnih i interakcija slabe katjonske izmene, je odabrana za analizu izazovne smeše neutralnih i katjonskih oblika analita: ergotamina, mekloksamina, kamilofina, kofeina i propifenazona, koji se primenjuju u fiksnoj kombinaciji. MMLC metoda je razvijena u skladu sa pristupom ugradnje kvaliteta kroz dizajn (Analytical Quality by Design – AQbD) koji podrazumeva naučno zasnovano razumevanje svojstava procesa i upravljanje životnim ciklusom metode prema riziku. AQbD se odnosi na unapred definisanje analitičkog ciljanog profila metode (Analytical Target Profile - ATP) odnosno razdvajanje na baznoj liniji za što kraće vreme, kao i na definisanje kritičnih osobina metode (Critical Method Attributes - CMA) kao mere kvaliteta metode i kritičnih parametara metode (Critical Method Parameters - CMP) koji utiču na CMA (2). Sadržaj acetonitrila, pH i koncentracija acetatnog pufera izabrani su kao CMP, pošto ekspresija MMLC retencionih mehanizma zavisi od karakteristika mobilne faze. Zavisnost CMA od CMP definisana je pomoću plana eksperimenata usklađenim sa centralnim kompozicionim dizajnom, ka centru orijentisanim i pratećim matematičkim modelima, koeficijentima i vrednostima standardne greške. Prostor dizajna u kome se ATP postiže sa visokim nivoom pouzdanosti (π = 90%) određen je Monte Karlo simulacijama uzimajuć i u obzir distribuciju grešaka. Njegov okvir ukazuje na radnu tačku koja obezbeđuje odgovarajuć u robusnost metode (pH 5,2, 90 mM rastvor acetatnog pufera i 48% (v/v) acetonitrila).VIII Kongres farmaceuta Srbije sa međunarodnim učešćem, 12-15.10.2022. Beogra

Uticaj parametara detektora naelektirsanja u aerosolu na odgovore odabranih analita u sistemu multimodalne hromatografije

With respect to significant market presence (50%), the analysis of pharmaceuticals containing counterions is a crucial component of the drug development life cycle, quality control and lot release processes (1). Mixed-Mode Chromatography (MMC) offers the ability to simultaneously separate cationic and anionic species within a single run, streamlining the laboratory processes (2). However, the detection of typical counterions leaves analysts little room for maneuver. In recent years, the counterions are efficiently detected with the help of Charged Aerosol Detector (CAD) that generates a signal independent of the chemical structure (3). In this regard, the use of MMC-CAD hyphenated technique rationalizes the number of individual analytical activities required for analyte and counterion testing, causes no resource depletion and ultimately supports the concept of sustainability in contemporary drug analysis. In this paper, the influence of the CAD parameters on the response of diclofenac potassium and tramadol hydrochloride was studied performing systematic variations. The analyses were carried out on Acclaim™ Mixed-mode WCX-1 (2.1 x 150 nm, 3 μm) column that provides both hydrophobic reversed-phase and weak cation-exchange properties. Satisfactory separation of the active pharmaceutical ingredients and their counterions was achieved using a mixture of 90 mM acetate buffer at pH 5 (A) and acetonitrile (B). The isocratic elution (40% B) was performed at a flow rate of 0.4 mL/min. Based on preliminary experiments, the following variables were identified as significant and, thus, tested at the listed values: evaporation temperature (35ºC and 50ºC), filter constant (1 s, 5 s and 10 s) and power function value (0.8, 1.0 and 1.2). The results showed that the evaporation temperature had a positive impact on the signal-to-noise (S/N) ratios. On the other hand, the peak area and the peak height decreased significantly upon raising the temperature. This finding pointed out a strong need for fine tuning of mentioned parameter with respect to the analytes’ volatility. The increase in the value of the filter constant led to a baseline smoothing as well as peak broadening. The filter constant set at 5 s resulted in the largest S/N ratios. The power function value, which directly modified the CAD signal, exhibited an obvious negative effect toward the peak area. In light of the above, optimal CAD detection of diclofenac, tramadol, potassium and chlorine was achieved at the following settings: filter constant 5 s, power function value 0.8 and evaporation temperature 35ºCS obzirom na veliku tržišnu zastupljenost farmaceutskih proizvoda koji sadrže kontra- jone (50%), analiza istih ključna je komponenta procesa razvoja leka, kontrole kvaliteta i puštanje serije leka u promet (1). Multimodalna hromatografija (eng. Mixed‐Mode Chromatography, MMC) nudi moguć nost istovremene separacije katjonskih i anjonskih vrsta na jednoj koloni, pojednostavljujući time laboratorijske procese (2). Međutim, izbor tehnika za detekciju tipičnih kontra-jona veoma je sužen. Poslednjih godina, kontra-joni efikasno se detektuju uz pomoć detektora naelektrisanja u aerosolu (eng. Charged Aerosol Detector, CAD) koji generiše signal nezavisan od hemijske strukture (3). S navedenim u vezi, smatra se da upotreba MMC-CAD tehnike racionalizuje broj pojedinačnih analitičkih aktivnosti potrebnih za kontrolu kvaliteta analita i kontra-jona, smanjuje iscrpljivanje resursa i time podržava koncept održivosti u domenu savremene analitike lekova. U ovom radu proučavan je uticaj sistemskog variranja parametara CAD detektora na odgovor diklofenak-kalijuma i tramadol-hidrohlorida. Hromatografkse analize izvedene su na Acclaim ™ Mixed‐mode WCX‐1 (2,1 x 150 nm, 3 μm) koloni koja kombinuje hidrofobne reverzno-fazne i mehanizme slabe katjonske izmene. Zadovoljavajuće razdvajanje aktivnih farmaceutskih supstanci i njihovih kontra-jona postignuto je upotrebom 90 mM acetatnog pufera pri pH 5 (A) i acetonitrila (B). Korišćeno je izokratsko eluiranje mobilne faze (40% B), pri protoku od 0,4 mL/min. Na osnovu preliminarnih eksperimenata, sledeć i faktori identifikovani su kao značajni, te su testirani pri navedenim vrednostima: temperatura isparavanja (35ºC i 50ºC), konstanta filtera (1 s, 5 s i 10 s) i vrednost stepene funkcije (0,8, 1,0 i 1,2). Rezultati su pokazali da je temperatura isparavanja imala pozitivan efekat na odnos signal/šum (eng. signal‐to‐noise, S/N). S druge strane, visina i površina pika značajno su se smanjili pri poveć anju temperature. Ovaj nalaz ukazao je na snažnu potrebu za finim podešavanjem pomenutog parametra imajući u vidu isparljivost analita. Poveć anje vrednosti konstante filtera dovelo je do boljeg izgleda bazne linije, ali i do širenja pikova. Konstanta filtera postavljena na 5 s rezultirala je najveć im vrednostima odnosa S/N. Vrednost stepene funkcije, koja je direktno modifikovala CAD signal, pokazala je očigledan negativan efekat na površinu pika. U svetlu eksperimentalnih nalaza, optimalna CAD detekcija diklofenaka, tramadola, kalijuma i hlora postignuta je pri postavkama: konstanta filtera 5 s, vrednost funkcije snage 0,8 i temperatura isparavanja 35ºC.Drugi naučni simpozijum Saveza farmaceutskih udruženja Srbije sa međunarodnim učešćem, 28. 10. 2021. Beogra

Primena eksperimentalnog dizajna za razdvajanje lekova HPLC metodom

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

Revealing Retention Mechanisms in Liquid Chromatography: QSRR Approach

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

Efikasnost superkritične fluidne hromatografije u kreiranju ekološki prihvatljivih rešenja u farmaceutskoj analizi

Initially employed primarily at a preparative scale for enantiomer separation of chiral drug candidates, Supercritical Fluid Chromatography (SFC) is nowadays extensively used in the analytical mode. Recent advances in SFC separation science have emphasized its potential for modern and environmentally friendly pharmaceutical analysis. The aim of this review is to provide a deeper insight into the main fundamental and practical aspects of the SFC technique in order to familiarize readers with its versatile nature and efficiency in creating sustainable chromatographic solutions. All considerations are made primarily in the context of the most widely used mode of operation - achiral SFC. In addition, recent applications of this promising technique are presented at the end of the article to further promote its use in pharmaceutical analytical practice.Na početku pretežno korišćena kao preparativna tehnika u enantioseparaciji hiralnih molekula kandidatâ za lek, superkritična fluidna hromatografija (eng. supercritical fluid chromatography, SFC) danas se široko koristi u analitičke svrhe. Noviji naučni napori ukazali su na značaj SFC tehnike u modernoj i ekološki prihvatljivoj farmaceutskoj analizi. Cilj ovog preglednog rada je pružanje dubljeg uvida u najvažnije fundamentalne i praktične aspekte SFC tehnike, kako bi se čitaocima približio njen svestrani karakter, te efikasnost u kreiranju održivih hromatografskih rešenja. Sva razmatranja prevashodno su data u kontekstu najzastupljenijeg režima rada - ahiralne SFC. Takođe, na kraju rada predstavljene su savremene primene ove obećavajuće tehnike kako bi se dodatno ohrabrilo njeno usvajanje u farmaceutsku analitičku praksu

266 Koncept ekološki prihvatljivih hromatografskih metoda: Studija slučaja na primeru razdvajanja dronedaron hidrohlorida i njegovih degradacionih proizvoda

Recently, concern about the environmental impact of drug analysis methods has increased significantly. Reversed-phase high-performance liquid chromatography (RP-HPLC), the predominant technique in drug analysis, relies heavily on organic solvents such as acetonitrile, which is known for its chromatographic efficiency, but also for its toxicity and flammability. To address these concerns, it is essential to minimize the use of toxic organic solvents. The aim of this study is to explore greener RP-HPLC modifications and evaluate their applicability in the pharmaceutical industry. Methods were developed for the separation of dronedarone hydrochloride and its degradation products based on experimental design, including micellar liquid chromatography (MLC), β-cyclodextrin (CD) modified RP-HPLC and ultra-high performance liquid chromatography (UHPLC). The eco-friendliness of these methods was assessed using the analytical eco-scale score, green analytical procedure index (GAPI) and analytical greenness (AGREE). AGREE appears to be the most suitable, as it revealed the greatest differences between the compared methods, as well as insights into critical aspects of the methods. UHPLC and β-CD modified RP-HPLC have been shown to be superior to MLC, and both methods can be a good choice, depending on whether the ease of implementation or energy efficiency is considered to be a more important criterion.U poslednje vreme, zabrinutost za negativan uticaj metoda koje se koriste u analitici lekova na životnu sredinu je u značajnom porastu. Reverzno-fazna tečna hromatografija visokih performansi (RP-HPLC) kao dominantno korišćena tehnika u velikoj meri se oslanja na primenu organskih rastvarača, poput acetonitrila, koji je poznat po hromatografskoj efikasnosti, ali i po toksičnosti i zapaljivosti. Kako bi se ovi problemi rešili i zaštitilo zdravlje ljudi i životna sredina, neophodno je upotrebu toksičnih organskih rastvarača svesti na minimum. Cilj ovog istraživanja bio je da preporuči „zelenije“ modifikacije RP-HPLC metoda. Primenom eksperimentalnog dizajna razvijene su metode za razdvajanje dronedaron-hidrohlorida i njegovih degradacionih proizvoda, uključujući micelarnu tečnu hromatografiju (MLC), RP-HPLC metodu modifikovanu β-ciklodekstrinom (CD) i tečnu hromatografiju ultra visokih performansi (UHPLC). Ekološka prihvatljivost ovih metoda je procenjena korišćenjem analitičke eko-skale, indeksa zelene analitičke procedure (GAPI) i pristupa analitičke zelenosti (AGREE). AGREE se izdvojio kao najpogodniji, jer je pokazao najveće razlike između navedenih metoda, kao i uvid u kritične aspekte metoda. UHPLC i β-CD modifikovana RP-HPLC metoda su se pokazale superiornim u odnosu na MLC. Koja metoda će biti metoda izbora zavisi od toga da li se lakoća implementacije ili energetska efikasnost smatraju važnijim kriterijumom

The secret of reversed-phase/weak cation exchange retention mechanisms in mixed-mode liquid chromatography applied for small drug molecule analysis

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