Evaluating the precipitation behavior and absorption potential of poorly soluble weak bases in the small intestine: a small-scale in
vitro procedure
Leevi Mäkitalo Master’s Thesis
University of Eastern Finland Faculty of Health Sciences School of Pharmacy September 2019
UNIVERSITY OF EASTERN FINLAND, Faculty of Health Sciences School of Pharmacy
Master of Science in Pharmacy program Technology of pharmacy
Mäkitalo Leevi: Evaluating the precipitation behavior and absorption potential of poorly soluble weak bases in the small intestine: a small-scale in vitro procedure
Master’s thesis, 69 p.
Supervisors: PhD Terhi Oja, Associate Professor Ossi Korhonen September 2019
Keywords: Poorly soluble weak bases, BSC class II, supersaturation, precipitation
Orally administered poorly soluble weak bases may have a precipitation risk in the small intestine due to the pH-depended solubility change between the stomach and upper small intestine.
Consequently, drug content may get upon a supersaturated state, which tends to settle to thermodynamically stable equilibrium solubility by precipitation. Poorly soluble weak bases often belong to the BSC class II, ergo substances had poor solubility but good permeability. Permeation through the gut wall may affect the precipitation process, but that phenomenon is often ignored at the early phase of drug development.
Drug precipitation in vivo poses a significant challenge for drug development, which has increased the need of IVIVC predictive in vitro tools -at the present time, many methods with a different complexity have been developed in an attempt to evaluate drug precipitation behavior, and development takes place all the time. In the novel, classification systems have also been made as an attempt to classify drug substances based on precipitation kinetic to the classes I (fast precipitating), II (intermediate) precipitating and III (slow precipitating).
In the Experimental part, an in vitro method was developed for studying the precipitation behavior, supersaturated pseudo-steady state, precipitation kinetic and potential absorption in a fasted state.
The method was developed on Pion Inc,’s microdissolution apparatus with a 2-compartment system (µflux) attached. 6 different compounds were used; albendazole, felodipine, indinavir, dipyridamole and two Orion’s own compound under development. Concentrations to be analyzed were 0.25 mM and 0.5 mM and fasted state intestinal simulating fluid (FaSSIF) was used as a medium.
For the method, enough discriminating power was managed to separate the drug from one another based on their precipitation kinetic. In addition, results were able to fit into recently introduced classification systems. Results indicated that permeation might affect precipitation kinetics of the test substances. In the future, the method could be used to create a drug library and, for example, to apply in formulation development to screen convenient precipitation inhibitors.
ITÄ-SUOMEN YLIOPISTO, terveystieteiden tiedekunta Farmasian laitos
Proviisorin koulutusohjelma Farmasian teknologia
Mäkitalo Leevi: Ohutsuolessa tapahtuvan heikosti emäksisten lääkeaineiden saostumisen ja imeytymispotentiaalin arviointi pienen mittakaavan menetelmällä
Pro gradu -tutkielma, 69 s.
Ohjaajat: FT Terhi Oja, Apulaisprofessori Ossi Korhonen, Syyskuu 2019
______________________________________________________________________________
Avainsanat: Heikosti emäksinen lääkeaine, BSC luokka II, ylikyllästyminen, saostuminen
Suun kautta annosteltavilla heikoilla emäksillä, joilla on pH-riippuvainen liukoisuus, on riski saostua ohutsuolessa, koska ne ovat yleensä hyvin liukenevia vatsan matalassa pH:ssa, mutta ohutsuolessa niiden liukoisuus laskee merkittävästi. Liukoisuuden muutos saattaa johtaa ylikylläiseen liuokseen, joka pyrkii kohti termodynaamista tasapainoa saostumalla, joka saattaa heikentää lääkeaineen biologista hyötyosuutta. Yhdisteen ominaisuuksien mukaan lääkeaineilla on erilaiset taipumukset pysyä ylikylläisessä muodossa ja saostua. Heikot emäkset kuuluvat BSC- luokituksessa luokkaan II, eli niillä on huono liukoisuus, mutta hyvä imeytyminen. Lääkeaineen imeytyminen ohutsuolessa saattaa estää tai pidentää ylikylläistä tilaa, mutta tämän ilmiön tutkiminen ohitetaan usein lääkekehityksen alkuvaiheessa.
Koska yhä useampi uusi lääkeaine kuuluu BCS-luokkaan II, on se nostanut tarvetta uusille in vitro työkaluille, joilla voidaan mallintaa kehitteillä olevien lääkeaineiden supersaturaatio- ja saostumiskäyttäytymistä jo lääkekehityksen alkuvaiheessa. Kirjallisuudesta löytyy useita eri menetelmiä tutkia saostumista in vitro. Menetelmät vaihtelevat yksinkertaisista kuoppalevy- tutkimuksista monimutkaisiin laite- ja koemenettelyihin. Lisäksi on kehitetty menetelmiä, joilla voidaan jaotella lääkeaineet niiden saostuskinetiikan perusteella luokkiin I (nopea saostuminen), II (keskitason saostuminen) ja III (hidas saostuminen).
Opinnäyte tutkielman kokeellisessa osassa kehiteltiin in vitro -menetelmä Pion Inc.:in kehittämälle mikrodissoluutiolaitteistolle, jolla voidaan tutkia lääkeaineiden saostumispotentiaalia ja mahdollista imeytymistä ohutsuolta simuloivissa olosuhteissa. Lisäksi oli tarkoitus tutkia imeytymisen vaikutus lääkeaineen saostumiskinetiikkaan. Tutkimuksessa käytettävät aineet olivat albendatsoni, felodipiini, indinaviiri, dipyridamoli ja kaksi Orionin kehityksen alla olevaa lääkeainetta. Väliaineena käytettiin FaSSIF:ia (ohutsuolen paastotilan nesteitä simuloiva biorelevantti väliaine).
Menetelmällä onnistuttiin erotella lääkeaineet saostuskinetiikan mukaan ja määrittämään niille saostumisluokat. Lisäksi tulokset antoivat viitteitä, että saostumiskinetiikka on hitaampaa, kun imeytyminen keinotekoisen rasvaliukoisen kalvon läpi otetaan huomioon. Jatkossa menetelmää voitaisiin käyttää esimerkiksi lääkeainekirjaston luomiseen ja soveltaa saostumista estävien inhibiittorien seulomiseen.
Acknowledgements
My master’s thesis was completed at the University of Eastern Finland, School of Pharmacy, on the Kuopio campus in cooperation with Orion Oyj. I made the experimental part of this master’s thesis in Orion Oyj, Turku, at analytical chemistry laboratory in the autumn and winter 2018- 2019. I would like to thank my supervisors Terhi Oja and Ossi Korhonen for the guidance and Laura Leimu and Sari Pappinen for valuable comments that I received during this thesis. I would also like to thank Johanna Ylikotila for making this unique opportunity possible. Special thanks also to Jaana Meri and Pirjo Kramsu for the HPLC analysis, guidance and teaching me how to use µdissolution apparatus.
Thanks also to all the Orion’s employee, who were involved in this thesis. You all helped me a lot. Many thanks also to my girlfriend.
Turku, August 2019
Leevi Mäkitalo
Table of Contents
I Literature review ... 8
1.1 Introduction ... 8
1.2 Classification of the drug substances ... 10
1.3 Physiological and anatomical factors of human gastrointestinal tract affecting the behavior of the drug molecules in the gastrointestinal tract. ... 12
1.4 Intestinal fluids ... 12
1.5 pH of the gastrointestinal tract ... 13
1.6 Physio-chemical aspects of precipitation behavior of BCS class II drugs in the small intestine ... 14
1.6.1 Dissolution and supersaturation ... 14
1.6.2 Precipitation ... 15
1.7 Permeation of orally administered drugs ... 18
1.8 Small-scale methods for studying the precipitation behavior in vitro ... 20
1.8.1 Biorelevant media ... 20
1.8.2 Approaches to induce the supersaturation on in vitro procedures ... 21
1.8.3 Small-scale in vitro assays for studying precipitation ... 22
1.9 Small-scale assays for studying precipitation with permeation step added ... 25
1.9.1 One-compartment system ... 25
1.9.2 Multi-compartment systems ... 26
1.10 Summary ... 28
II Experimental part ... 29
2.1 Aim of the study ... 29
2.2 Materials and methods ... 30
2.2.1 Reagents and media ... 30
2.2.2 Solubility studies ... 32
2.3 Experimental settings ... 33
2.3.1 The µdissolution apparatus ... 33
2.3.2 Solvent-shift method ... 34
2.3.3 Initial conditions of experiments ... 35
2.3.4 Determination of linearity using µdissolution apparatus ... 36
2.4 Optimization of test parameters ... 37
2.5 Precipitation studies ... 38
2.6 Precipitation-permeation studies ... 38
2.7 Calculations ... 39
2.4 Results ... 41
2.4.1 Solubility studies ... 41
2.4.2 Optimization of the test conditions ... 42
2.4.3 The precipitation studies ... 44
2.4.3.1 Precipitation behavior ... 44
2.4.3.2 Precipitation induction time ... 46
2.4.3.3 Half-time of precipitation ... 47
2.4.4 Precipitation-permeation studies ... 48
2.4.4.1 Precipitation rate and effect of permeation ... 48
2.4.4.2 Flux of test compounds ... 50
2.4.4.3 Permeability ... 52
2.5 Discussion ... 53
2.5.1 µdissolution apparatus and analysis ... 53
2.5.2 Precipitation risk assessment ... 54
2.5.3 Optimization of the method. ... 55
2.5.4 Tendency of crystallization and classification of test compounds. ... 56
2.5.5 Supersaturation, precipitation and permeation studies ... 59
2.6 Conclusions ... 62
References ... 64
Abbreviations and definitions
API Active pharmaceutical ingredient
ASB Acceptor sink buffer
BA Bioavailability
BCS Biopharmaceutical classification system
CNT Classical nucleation theory
DCS Developability Classification System
DMSO Dimethyl sulfoxide
DS Degree of supersaturation
FaSSIF Fasted state simulated intestinal fluid
FeSSIF Fed state simulated intestinal fluid
GI Gastrointestinal
HPLC High-performance liquid chromatography
IVIVC in vitro-in vivo correlation
Ph. Eur. European Pharmacopoeia
SIF Simulated intestinal fluid
SGF Simulated gastric fluid
USP United States Pharmacopeia
UV Ultraviolet
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I Literature review
1.1 Introduction
An oral administration is the most common route to consume drugs. In order to an oral drug to enter the systematic bloodstream, the drug should be first dissolved in body fluids, after which molecules can be absorbed throughout the intestinal epithelium and affect at their target site (figure 1). On this route, many factors can limit the bioavailability of the drug which can be caused by human body system functions (i.e., enzymatic metabolism and gastric functions) and physicochemical properties of the drug molecules (Sugawara et al. 2005). In addition, the drug absorption occurs mainly at the small intestine due to the large area of the absorption site. A significant part of new drug substances under the development are poorly soluble weak bases that are included in class II of the biopharmaceutical classification system (BCS). The physicochemical properties can prevent the bioavailability by limiting the solubility, dissolution, and/or absorption of the drug (Amidon et al. 1995). Poor solubility of the new drug substance is a common issue in drug development. However, it is not the only problem that early-stage drug development has encountered; some basic BCS class II drugs have a potential precipitation risk in the small intestine.
Drug belonging to the BCS class II has a poor solubility but good permeability.
The precipitation risk is especially essential for substances that have pH-depended solubility because their solubility difference can vary significantly between the stomach and small intestine (Hamed et al. 2016). If solubility decreases acutely when consumed content enters the small intestine from the stomach, drug solution may end up supersaturated. A supersaturated state is thermodynamically unstable and tends to precipitate (Kostewicz et al. 2004). The precipitation of solid particles may play a role in the bioavailability of low soluble weak bases in the gastrointestinal tract by lowering the extent of permeable molecules in the small intestine. Thus, precipitation may affect the safety or therapeutic efficiency of drug. Fasted state favors precipitation because stabilized physiologically pH and lack of food components that may prevent precipitation by solubilization and environmental effects. Besides, the drug permeation through the membrane of the small intestine may prevent precipitation. Therefore, drug development has increased the
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interest in studying this phenomenon, supersaturation and precipitation behavior of new drug molecules as early phase as possible (Bevernage et al. 2013).
The most accurate methods to study precipitation and supersaturation are in vivo measurements from a human lumen or plasma profiles (O’Dwyer et al. 2019). Another accurate way to study drug supersaturation and precipitation behavior is to use animal models. However, these studies can be expensive, time-consuming and ethical questions can appear. In addition, before first studies in human or animals, drug must undergo developing phases that need in vitro testing. In vitro studies include full- and small-scale studies. Where full-scale methods focus on, for example, formulation developing, small-scale studies are used for screening, for example, lead compounds from the bigger group of molecules. In addition, at the early-stage of drug development, an available amount of active pharmaceutical ingredient (API) is often limited; thus, small-scale tests are crucial.
The early-stage procedures focus on high throughput screening or imitating the gastrointestinal conditions as accurately as possible (O’Dwyer et al. 2019). In general, in these initial procedures, no clinical doses can be used; thus, they do not replace larger scale tests in later drug development.
However, they can provide useful data and prevent unnecessary tests at lower costs. For imitating the gastrointestinal conditions, biorelevant media has been developed and often used in in vitro procedures. The composition of biorelevant media is made to correspond to physiological fluids which use has improved the functionality of in vitro testing.
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Figure 1. A schematic illustration of permeation route of orally administered drug to systemic circulation. On this route, bioavailability can be affected, for example, by incomplete dissolution, permeation and/or metabolism in the gut and liver (first pass extraction) (Chan and Steward 1996).
1.2 Classification of the drug substances
In 1995, Amidon et al. introduced a widely accepted biopharmaceutical classification system (BCS), whereby orally administered immediate release (IR) drugs can be divided into four classes upon their intestinal permeability and aqueous solubility (Table 1). According to the BSC, the rate and the extent of the oral absorption are due from three major feature of the substance: solubility, permeability and dissolution rate. The drug expresses a high solubility if clinically anticipated dose is dissolved in 250 mL or less, high permeability if more than 90 % of drug is absorbed in vivo, and fast dissolution if 85 % is dissolved in pH range 1-7.5 in less than 15 minutes, although the class boundaries may vary slightly depending on the used method and authority (FDA 2000, EMEA 2010). Generally, the solubility and dissolution rate does not limit the absorption of the BSC class I and III drugs but can limit the extent of the absorption of BCS class II and IV drug. The dissolution rate is also used to evaluate the possible in vitro-in vivo correlation (IVIVC) and furthermore, this model has been used to evaluate the suitability of the drug forms to be a biowaiver by pointing the drug bioequivalence by in vitro testing. Especially, the pH-dependent BSC class II drugs may tend to supersaturate and precipitate in the small intestine due to the pH transform from the stomach to the small intestine.
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Table 1. The biopharmaceutical classification system (Amidon et al. 1995).
Solubility Permeability
Class I High High
Class II Low High
Class III High Low
Class IV Low Low
Despite extensive use of the original BSC system, it has some disadvantages for purposes of early drug development (Rinaki et al. 2003, Wu and Benet 2005, Tsume et al. 2014). From the Pharmaceutical development aspect, for example, there is not always need to determine the solubility of the pH-independent molecules in acidic pH even though it usually covers the upper gastrointestinal pH because it has no clinical meaning. In addition, used solution buffers are simple in the model of the BCS, although bile acids can affect the substantial solubility of the drug in the small intestine. The BCS classification also requires mass balance studies or expensive in vivo data in order that the permeability behavior can be determined. Thus, it is unsuitable sometimes for early drug development purposes.
In 2010, Butler and Dressman proposed a Developability Classification System (DCS), which is more focused on factors that affect drug absorption in the gastrointestinal tract. In the DCS, the BCS class II is divided into dissolution rate limited class IIa and the solubility limited class IIb. If dissolution rate limits the oral absorption, the drug tends to have utterly oral absorption, contrary to solubility limited drugs have more significant potential to precipitate in the small intestine, which may decrease the absorption potential. Respectively, If the compound supersaturates in the small intestine, permeation through the gut wall may prevent the precipitation of class IIa drugs more likely. In the DCS, solubility test conditions focus on small intestine conditions, which is considered as the site where most of the drug is absorbed. Therefore, more biorelevant media as fasted state simulated intestinal fluid (FaSSIF) and fed state simulated intestinal fluid (FeSSIF) are used in DCS definition.
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1.3 Physiological and anatomical factors of human gastrointestinal tract affecting the behavior of the drug molecules in the gastrointestinal tract.
Conventionally, bioavailability (BA) of the orally administered drug can be considered as a percentage of drug dose that reaches the systemic circulation (Amidon et al. 1995, van de Waterbeemd and Gifford 2003). BA of the orally consumed dose can be described with the following equation:
𝐵𝐴 = 𝑓𝑎𝑏𝑠∗ (1 − 𝐸𝐼) ∗ (1 − 𝐸𝐻) (1)
Where fabs is a fraction absorbed through the intestinal gut wall and Eim and EH are the degree of the extraction in the intestinal lumen and the hepatic first pass metabolism. In the small intestine and liver, the extent of the extraction and metabolism is drug specific affected by metabolizing enzymes, active efflux and the transportation routes of the drug molecules (Agoram et al. 2003).
In addition to metabolism aspect, solubility, dissolution and permeation of the drug substances play a key role in the BA. Therefore, also physiology of the human body affects drug behavior in the gastrointestinal tract.
1.4 Intestinal fluids
Human gastric fluids include food components, intestinal fluids and hormonally secreted fluids such as bile acids. The composition of human gastric and intestinal fluids differs greatly between the individuals, although no significant gender differences have been observed (Moreno et al. 2006, Lindahl et al. 1997). Bile acids concentration is usually around 3.0 mM in the small intestine, while stomach concentration is around 0. The major bile acids in the small intestine is reported to be taurocholic acid, glycocholate and glycochenodeoxycholate. The first of these is reported to cover up almost to half the salts. The bile acids in the gastrointestinal tract can form micelles affecting the solubility of the drug molecules by solubilization (Faberberg et al. 2010). Solubilization is generally the enhancement of apparent solubility of the drug substances by dispense of the lipophilic molecules into micelles of intestinal fluids which can be produced by natural gastrointestinal surfactants or consumed food components. With these in mind, solubilization is different in fasted and fed state due to the differences in the extent of the hormonally secreted fluids. According to Dressman et al. (2007), the bile components as salt conjugates, cholesterol and phospholipids are the main cause of solubilization in the small intestine, while extending of the
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natural surfactants in the stomach is mainly due to the reflux from the upper small intestine.
However, surfactants may enter with the consumed food in the stomach. In addition to these, the volume of the available fluid plays a role in solubilization at the site of dissolution that is primarily affected by eating.
1.5 pH of the gastrointestinal tract
The pH of the surrounding environment alters in different sections of the human gastrointestinal tract, which can especially affect the function of substances having pH-depended solubility. The human gastrointestinal tract (GI-tract) is the muscular tube which travels through the body from the oral cavity to the rectum. Consumed drug enters quickly to the stomach after swallowing. The pH in the stomach is usually 1-3 in healthy adults but can vary widely between people (Dressman et al. 2007, Koziolek et al. 2016). The pH in the stomach is affected by age, culture, diseases and drugs affecting the gastrointestinal tract. Eating or drinking can temporarily increase the pH of the stomach due to the buffering effect but normally after a few hours, the gastric acid decreases the pH back to an initial condition. After the stomach, surrounding pH increases in different parts of the intestines that are in order a small intestine, duodecum and large intestine. The small intestine consists of three distinct regions: the duodenum, jejunum and ileum. The duodenum is the proximal section of the small intestine between the stomach and jejunum, which is around 2.5 meters long midsection. The pH in the proximal section of the small intestine is in the fasted state approximately 6-6.5 but eating can temporarily decrease it slightly. The pH remains more stable in the distal section of the jejunum, approximately in 7-7.5 despite of the consumed food. Thus, the pH of the stomach and small intestine along the consumed food can affect the solubility of pH-dependent drug molecules. Considering the small intestine as the primary absorption site of BCS II drugs, the gastrointestinal pH is the principal determinant of the drug solubility that can ionize at the pH range 2-8 (Koziolek et al. 2016).
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1.6 Physio-chemical aspects of precipitation behavior of BCS class II drugs in the small intestine 1.6.1 Dissolution and supersaturation
The solubility of drug substance refers to the amount of solute in the saturated solution in the specific temperature. Correspondingly, a solution having precisely the same amount of solute as its solubility is called a saturated solution. This saturated point, over which the solution is no longer thermodynamically stable, is influenced not only by temperature but also by the molecular size, polar surface area and other chemical nature of the solute and environment as the solute-solvent interactions and pH. The DCS class IIb drugs usually have pH-depended solubility; Thus, their solubility can dramatically decrease when entering in the small intestine. The percentage of pH- depended solubility drugs in the ionized form at any pH can be calculated using the Henderson- Hasselbalch equation write as:
𝑝𝐾𝑎 − 𝑝𝐻 = log 𝑖𝑜𝑛𝑖𝑧𝑒𝑑 𝑓𝑜𝑟𝑚 𝑛𝑜𝑛𝑖𝑜𝑛𝑖𝑧𝑒𝑑 𝑓𝑜𝑟𝑚 (2)
Where pH value is the pH of the medium, and pKa is the ten-point logarithm of the acid constant of drug. A dissolution is an event which describes the interaction of solvent with ion or molecule of the drug substance. Dissolving involves the solid going into the liquid phase. The crystal structure of the orally administered drug has to decompose by the interaction of solute-solvent forces, which comprises bond formation, hydrogen bonding and van der Waals forces. Dissolution is assessed by its rate, which can be described by the Noyes-Whitney equation (Kaur et al. 2018);
𝑑𝑚 𝑑𝑡 =𝐷𝑆
ℎ (𝐶𝑠− 𝐶) (3)
Where dm/dt means the solute dissolution per time, D is a diffusion coefficient, S is a surface area of solute particles, h is a thickness of the diffusion layer, Cs is a saturation concentration and C is a bulk concentration.
When the pH decreases rapidly in the small intestine, the solution may become supersaturated. The supersaturated state is a thermodynamically unstable, and the drug molecules tend to precipitate, and concentration starts to settle to its equilibrium solubility. An equilibrium solubility depicts the dynamic reaction between the solute and the precipitate, in which molecules are constantly dissolved in the liquid from the precipitated particles, and at the same time, the dissolved molecules
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are precipitating. Degree of supersaturation (DS) can be used for evaluating a supersaturated system, and it can be calculated using following the equation (Bevernage et al. 2013);
𝐷𝑆 = 𝐶𝑠
𝐶𝑒𝑞 (4)
where Cs is a concentration of supersaturated system and Ceq is a equilibrium solubility.
1.6.2 Precipitation
Precipitation as a phenomenon can be described in a two-step process; nucleation and crystal growth but they usually occur simultaneously (Lindfors et al. 2008). In order that substance can precipitate in the solution, it must first dissolve over its equilibrium solubility. A supersaturated solution is a metastable state ergo the free energy per dissolved molecule is higher than their macroscopic crystalline phase. The nucleation can also be divided into homogeneous and heterogeneous nucleation. Classical nucleation theory (CNT) is one of the most used theory to describe the nucleation kinetics of crystals from supersaturated solutions (Erdemir et al. 2009) The homogeneous formation of nuclei is more uncommon, and it is thermodynamic can be surveyed through the free energy of Gibbs (figure 2). The diagram describes the free energy change required for cluster formation. In terms of surface and volume free energy, after the ΔG exceeds the required free energy for the critical radius of nuclei, thermodynamic starts to favor the solid state of matter.
Nuclei can be formatted by the mobility of temperature movements and typically requires 100- 1000 atoms to reach the critical nuclei radius. The heterogeneous nucleation can start on the surface or impurity of solution. CNT assumes that formatted precipitate is spherical; thus the needed Gibbs energy ΔG(r) to create a precipitate in a supersaturated system can be calculated using the following equation (Perez et al. 2008):
ΔG(r) =4
3𝜋𝑟3Δ𝑔 + 4𝜋𝑟2𝛾 (5)
Where r is a critical radius after a particle is solid, Δg is the driving force of precipitation per unit volume and γ the specific interfacial energy between the nuclei and the solution. The surface tension of substance is also one of the most determining factors of the nuclei formation (Sugano et al. 2009).
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When a solution is in supersaturated state ergo in pseudo steady-state, rate of nucleation (J) can be expressed by Arrhenius reaction rate equation (Erdemir et al. 2009):
𝐽 = 𝐴𝑒𝑥𝑝(−Δ𝐺𝑐𝑟𝑖𝑡
𝑘𝑇 ) (6)
Where k is the Boltzmann’s constant, A is the pre-exponential factor, T is temperature and Gcrit is the free energy required to nuclei formation (Also called as activation energy) and A is the pre- exponential factor.
The nuclei growth and the precipitation rate can be thought of as a reciprocal process of dissolution (Lindfors et al. 2008, Sugano 2009). Then, the limiting factors of precipitation are diffusion of crystallizing component from bulk to crystal surface and the attachment of crystallizing component to the crystal lattice. The precipitation rate is also strongly related to the number of nuclei in solution. Also, crystal growth started by heterogeneous nucleation from surface, impurity or undissolved nuclei, can substantially affect the rate of precipitation of compounds.
Classification of drugs has been made according to their precipitation kinetics (Baird et al. 2010, Van Eerdenbrugh et al. 2010, Van Eerdenbrugh et al. 2014). Based on measured precipitation kinetics of various drugs by different approaches, drugs have been divided into three classes; Class I (fast precipitating), class II (Intermediate precipitating) and class III (slow precipitating). Brand et al. (2010) and Van Eerdenbrugh et al. (2010) used DSC screening method for detecting the crystallization from amorphous undercooled melts. Substance belonged to the class I, if
Figure 2. Schematic illustration of Free energy diagram for homogenous nucleation (Erdemir et al. 2009)
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crystallization was observed during cooling from the undercooled melt before the glass transition (Tg), class II, if crystallization was observed during the reheating process above Tg and class III, if crystallization was not observed during the heating sequence. In addition, Van Eerdenbrugh et al.
(2010) studied crystallization tendencies of 93 drug molecules by rapid solvent evaporation using a spin coating. The classification was class I if crystallized and amorphous areas of matter were observed comparable on the first day, class II if same happened at least in seven days and class III if crystallization was not observed or it was slightly after seven days. They found that 68 % of cases were identical to the results from undercooled melts. Later in 2014, Van Eerdenbrugh et al.
studied the same crystallization classes for amorphous active pharmaceutical ingredients in aqueous environments. They induced supersaturation by a solvent-shift method and observed crystallization in situ by synchrotron radiation. Class boundaries were in this study: class I if precipitation was observed during 150s, Class II if precipitation occurred after 1h and class III if precipitation required a longer period. The results gained with different approaches to define the crystallization classes were comparatively coherent.
In 2017, Hancock introduced an indicative approach to predict the crystallization potency of molecules by their 2D molecule structures. According to Hancock, a drug-like molecule is more readily to precipitate if it has a fever rotatable bonds and has a lower molecule weight and vice versa. Following this kind of thinking, Hancock conducted a classification that is showed in table 2.
Table 2. Classification for predicting crystallization properties of drug-like molecule based on molecule structure (Hancock 2017)
Number of rotatable bonds Mw less than 300 Mw over than 300
0-3 Fast Moderate
4-6 Fast to Intermediate Intermediate to Slow
>6 Intermediate to Slow Slow
18 1.7 Permeation of orally administered drugs
The drug can pass across the intestinal epithelium either actively or passively (Artursson et al.
2001). Drug absorption includes carrier mediated route, transcytosis, passive transcellular and paracellular transportations (figure 3). Passive transcellular transportation is due to diffusion of drug molecule through the cell membrane, which is a two-way process, thus concentration gradient over the membrane determines the extent of passive diffusion. Respectively, paracellular diffusion occurs between the cells. The rate of passive transportation is affected by physicochemical properties of molecules, for example, molecular weight, log P and polar surface area (Camenish et al. 1998). The absorption area in the small intestine mainly consists of a single monolayer epithelial tissue whose surface is increased by microvilli, villi and folds of the intestine. Tight junctions between the enterocytes can restrict the paracellular transport route. The permeation of well absorbable drugs happens regularly through the tips of the villi’s, but less permeable substances may enter deeper between the villi’s due the diffusion, and thereby the absorption area is more extensive for them, which increases their rate of permeation naturally.
Figure 3. A schematic Illustration of a single monolayer of the small intestine and drug transportation routes; 1. represents the passive transcellular transportation, 2. Represents the passive paracellular transportation, 3. Represents the active carrier-mediated transcellular transportation and 4. represents the transcytosis routes (Artursson et al 2001).
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All the transportation routes are studied widely with caco-2 cell line, which is a line of heterogeneous human epithelial colorectal adenocarcinoma (Arthursson et al. 2001, Camenish et al. 1998. Lennernäs et al. 2014). Passive transportation is assumed to be significant absorption route for lipophilic compounds including BCS class II drugs. However, notable is that if the main transport mechanism of a compound is the carrier-mediated route or its passive diffusion is slow, the accuracy of in vitro models may be not predictive (Lennernäs et al. 2014).
Based on the in-silico calculations of properties of thousand drugs, Lipinski et al. (2001) have unraveled a “rule of five” that can be used to assume when chemical properties of orally administrated drug compounds are likely for permeation. In general, according to Lipinski’s rule, problems in permeation and absorption are expected if more than one of the following criteria is penciled; Molecule has more than 5 H-bond donors, molecule weight is over 500, log P is over 5, molecule has more than 10 h-bond acceptors and passive permeation is not dominant transportation route (active transportation can increase the bioavailability of the compound even if the more than one former criteria is fulfilled). Later, another rule has been proposed to improve the predictions of possible absorption and oral bioavailability. Veber et al. (2002) studied an oral bioavailability of 1100 drug candidates in rats and their observations suggested that compounds that have 10 or fewer rotatable bonds and the polar surface is >140Å have good oral bioavailability. In general, they discovered that planarity and polar surface predicted the oral bioavailability more than molecular weight.
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1.8 Small-scale methods for studying the precipitation behavior in vitro
1.8.1 Biorelevant media
In small-scale assays, biorelevant media are usually used to mimic the gastrointestinal fluids. The first biorelevant media was simulated intestinal fluid (SIF), developed by USP (Jantratid et al.
2008). The composition of the proximal small intestine alters clearly between the fasted and fed state, thereby, simulating intestinal fluids have been developed for both state; fasted state simulated intestinal fluid and fed state intestinal fluid. Also, their modifications have been developed, because the composition of small intestine varies between the sections. Also, development takes place all the time because new information becomes continuously available. The composition of commonly used biorelevant media and their modifications simulating the small intestine fluids are shown in table 3.
Table 3. The compositions of biorelevant media simulating environment of small intestine in fed and fasted state. (Jantratid et al. 2008, Dressman and Reppas 2000)
FaSSIF FaSSIF-V2 FeSSIF FeSSIF-V2
Sodium Taurocholate (mM) 3 3 15 10
Lecithin (mM) 0.75 0.2 3.75 2
Maleic acid (mM) - 19.12 - 55.02
Sodium hydroxide (nM) 0 34.8 - 81.65
Potassium chloride (mM) 103 - 204 -
Sodium chloride (mM) (Or equivalent amount to 103 mM KCL)
68.62 (Or equivalent to 204 mM KCL)
125.5
Potassium dihydrogen phosphate (mM)
2.9 - - -
Glycerol monooleate (mM) - - - 5
Sodium oleate (mM) 0.8
pH 6.5 6.5 5 5.8
Osmolality (mOsm kg-1) 270±10 180±10 635 ± 10 390±10
Buffer capacity (mmoll-1 ΔpH-
1)
- 10 25 25
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It has been highly shown that these biorelevant media has improved the in vitro-in vivo correlations of early drug development testing (Jantratid et al. 2008, Dressman and Reppas. 2000). Biorelevant media contains micelle formed by bile acids and phospholipids that increases the apparent solubility of drug. Fed state biorelevant media contains more components than fasted state, which indicates that food may increase the solubility of some compounds. In addition, the pH of fed state biorelevant media is lower that increase the solubility of basic compounds.
1.8.2 Approaches to induce the supersaturation on in vitro procedures
Commonly used method to study the supersaturation and precipitation in small-scale assays is a solvent-shift method (Lindfors et al. 2008, Morrison et al. 2014). In this method, the compound is dissolved initially in a high solubilizing stock solution, for example DMSO, which result in a highly concentrated solution, after which the concentrated solution is applied to lower soluble environment resulting supersaturated solution. For example, Yamashita et al. (2011) studied the efficacy of precipitation inhibitors with itraconazole using solvent-shift method on 96 well-plate template procedure. They used FaSSIF II as a medium and DMSO as a stock solution. For detecting the precipitation, they used HPLC/UV analysis. Results indicated that small-scale procedure correlated well with the full-scale USP paddle dissolution experiment. The method is highly suitable for the early-stage of drug development due the required amount of compound is commonly low.
Another common technique to induce the supersaturation in in vitro tests is a pH-shift method. In this technique, supersaturation is caused by raising the pH of the sample to change the solubility of the substance. For example, Kim et al. (2003) used the pH-shift method for developing the micro crystallization process for indomethacin. Initially, they produced 200 mL of saturated indomethacin solution, then they adjusted pH to 7.3 using Zn-acetate and continued to pH 8.3 using NaOH. After that, they add HCL by the peristaltic pump to adjust pH to 6. The produced supersaturated solution was stored and analyzed after 24h. The pH-shift method is suitable to use if the solubility of the test substance is pH-depended.
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1.8.3 Small-scale in vitro assays for studying precipitation
At the early-stage of drug development, small-scale in vitro assays are utilized to evaluating precipitation of new molecules for pharmaceutical profiling and early formulation development (O’Dwyer et al. 2019). Benefits of the small-scale In vitro assays are small quantities of the APIs and lower requirement of biorelevant media than the full-scale procedures as USP II apparatuses.
However, the small-scale assays do not replace the full-scale methods to study the drug behavior of clinically relevant doses, thus results from the small-scale studies can lead the development to the right direction and help to avoid the unnecessary tests in further development.
High-throughput or miniaturized assays are commonly used in lead optimization and early drug development for studying the precipitation behavior of drug substances (Dai 2010). The advantages of high-throughput procedures are relatively low costs in biorelevant media and required amounts of drug molecules are low as the available amounts are often limited. In recent years, these kinds of precipitation assays have become more common. For studying the precipitation risk in the small intestine, different variable procedures are illustrated in the literature, in which high-throughput 96 well-based platforms and its different variations are used (Alsenz et al. 2007, Dai 2007O’dwyer).
Some of these 96 well-based platform assays have been developed to screen the drug solubility in simulating gastrointestinal fluid media and solvent casting is often used in these tests. In 2007, Alsenz et al. developed a partially automated solubility screening (PASS) assay for early drug development. The procedure determines drugs thermodynamic solubilities on 96-well plates with automatism. Based on fast solubility screening in biorelevant media, the precipitation risk in a gastric environment was evaluated. Disadvantages of high-throughput assays are that they do not take into account the permeation and the small volume of a used matrix may not be directly comparative to the real situation with clinical dose. In addition, solvent casting may cause solubility changes in the sample.
In 2013, Mathias et al. approached to study drug supersaturation and precipitation with the micro- dissolution test in the conditions that mimic the transportation of content from the stomach to the small intestine by changing media and pH (pH-shift method) as the schematic figure 4 illustrates.
In the test, drug powder or solution, representing clinical dose, was introduced into the simulated intestinal fluid (SGF, pH 2) and dissolution was observed for 20 min by UV fiber optic, after which
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bile acid and buffer capacity modified FaSSIF was applied to the compartment. After that, they observed the dissolution for another 180 min. The overcome of the mixture of initial SGF and modified FaSSIF resulted in the pH of 6.5 FaSSIF, which were introduced by Dressman and Reppas (2000). Researchers studied a set of compounds and they used as a poorly soluble weak base, for example, ketoconazole. Ketoconazole seemed to dissolve entirely at the gastric pH 2.
After FaSSIF transfer, the concentration decreased dramatically from approx. 780 µg/mL to 200 µg/mL and stayed supersaturation state approx. 60 min before it started slowly precipitate.
Figure 4. Schematic illustration of one-compartment microdissolution test (Mathias et al. 2013)
For studying the dissolution, supersaturation and precipitation behavior of drug substances, Pion Inc. has been developed a microdissolution system (µDiss system) that utilizes a UV fiber optic to monitor a concentration of the sample to be analyzed. The system provides real-time information on the concentration of formulations or drug powders and allows an eight parallel simultaneously analysis. The system detects UV spectra and draws concentration-time profile, where the supersaturation and precipitation can be observed by the changes in the concentration. In addition,
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the required amounts of biorelevant media are usually 1-10 mL on the device. Palmelund et al.
(2016) developed a standardized method to study the drug precipitation and supersaturation behavior using µDiss system with solvent-shift method to induct a supersaturation. Researchers used a DMSO as a stock solution and FaSSIF level II as a medium. They utilized obtained induction times and degree of supersaturation of six different substances to classical nucleation theory and found out regression on precipitation profiles for all test compounds.
While UV-approaches are advanced and widely used for detecting dissolution and precipitation in small-scale procedures, other methods are also used, for example infrared (IR) and Raman spectroscopy. Coutts-Lendon et al. (2003) used Fourier transform infrared (FT-IR) imaging spectroscopy for studying the dissolution of testosterone in a dispersed mixture of thin polyethylene oxide matrix film. Polymer erosion and dissolution were detected from changes in monitored spectra. In addition, researchers managed to identify drug release mechanism by FT-IR imaging and changes at the bulk polymer/solvent boundaries. In 2011, Arnold et al. studied dissolution and precipitation of dipyridamole using in-vitro transfer test that simulated the stomach-small intestine transition step (conducted to USP apparatus II). Precipitation was monitored using Raman spectroscopy, in which fiber optic was conducted, in the acceptor vessel. FeSSIF-V2 was used on the acceptor side. Raman spectroscopy provided real-time data about the precipitation, which was able to form to the kinetic nucleation and growth theory. Disadvantages of Raman spectroscopy are that it is more complicated and requires a higher cost than FT-IR (Kuentz 2014). However, water causes less interference in the spectrum, thus it allows more complex media for experiments.
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1.9 Small-scale assays for studying precipitation with permeation step added 1.9.1 One-compartment system
One approach to study the absorption of drug substances in vitro is to utilize an organic phase layer on top of the aqueous donor layer in one-compartment system as shown in figure 5 (Frank et al.
2014). The method is called biphasic dissolution test, where drug partitioning through the layers mimics the absorption step. The organic layer can generate the sink conditions for the aqueous layer, but the situation differs from the multi compartment system and in vivo situation due the lack of membrane, which may lead to the unrelated results. In addition, the method may involve micellar solubilization and emulsification which does not occur in the small intestine. In 2014, Frank et al.
assessed the precipitation and drug release of the poorly soluble weak bases e.g., dipyridamole, by single-phase mini-dissolution tests and a mini-scale biphasic dissolution model with pH-shift
(miBIdi-pH), shown in figure 5.
Figure 5. Schematic illustration of Schematic illustration of the mini-scale biphasic dissolution model including the dual paddle; model comprises two phases (aqueous phase and octanol) and is temperature-controlled; volume of the aqueous phase = 50 mL; volume of the octanol phase = 30 mL.
26 1.9.2 Multi-compartment systems
For studying the dissolution, supersaturation and precipitation in the absorptive environment, Pion Inc. has been proposed a two-chamber system (µFlux), which can be attached to their µdissolution apparatus. A lipid-coated membrane is generally used between the chambers, and the drug concentrations are measured in situ in the donor and acceptor chambers by UV fiber optic, the same way as previously described. Therefore, the system is also suitable for studying the uptake, as the permeation rate, of drug in the acceptor side. Absorption of the drug through the membrane reflects drug absorption in vivo, which clearly differs from one compartment system. Therefore, predictability of in vivo behavior and biorelevance of the two-chamber system may be improved.
Borbás et al. (2015) studied an in vitro permeation enhancement of cyclodextrin based electrospun formulations of aripiprazole throughout artificial membrane that simulated oral mucosa membrane.
By using µflux platform (figure 6), they observed that electrospun fibers enhanced dissolution, supersaturation and precipitation properties, as well as total permeated amount on acceptor side, compared to physical or crystalline forms of studied API, thus benefit of this compartment is real- time data from both donor and acceptor chamber.
Figure 6. Schematic illustration of µflux compartment (Borbás et al. 2015).
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Recently described in vitro approach for studying the interplay of drug dissolution and permeation is new setup Permealooptm (figure 7)(Sironi et al. 2018). The advantage of this setup is more relevant absorption area related to in vivo situation compared to other existing setups. The setup also allows more realistic doses within physiological transportation times. Sironi et al. (2018) studied dissolution/permeation interplay of formulations of BCS class IV drug substance under development and noticed a trend that due the large permeation area, dissolution became a limiting factor. However, this may not be the case with high permeable substances as BCS class II substances. Due the more relevant absorption area, researchers implicated that the setup allows more reliable in vitro results of dissolution/permeation interplay. The figure illustrates the principals of this setup, which is consisted of three main parts: donor and acceptor chamber, peristaltic pump and permeation cell.
Figure 7. Schematic figure of permealooptm (sironi et al. 2018).
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1.10 Summary
Many different approaches have been developed to evaluate the supersaturation and precipitation behavior of poorly soluble weak bases in the small intestine. Also, the interest for modeling the supersaturation and precipitation phenomena in the early stages of drug development has increased recently as well as the interplay between the absorption and precipitation. Estimations based on the molecule structure, physicochemical properties or results from in vitro methods provides a rough assessment of possible in vivo behavior in the small intestine. After all, different approaches provide a useful tool for early-stage of drug development to screen and investigate the supersaturation and precipitation properties of new drug substances. Studying the supersaturation and precipitation properties are essential because absorption potential of poorly soluble weak bases can be improved by increasing their supersaturation tendency and lowering precipitation kinetics by convenient excipients and/or formulations. In addition, the
In recent years, initialization of new technologies as UV-fiber optics and other detection procedures have improved the use of small-scale methods. In addition, new apparatuses and biorelevant media have improved the predictability and IVIVC of the small-scale methods. However, the challenge is often the lack of in vivo data. Also, the complexity of the small-scale methods varies widely as does their potential for drug development because drug development often requires fast and low- cost methods. Thus, proper small-scale procedures may improve the efficiency and lower the research and development costs. However, the small-scale methods, technology and biorelevant media are constantly advancing as more information and data becomes available all the time.
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II Experimental part
2.1 Aim of the study
The aim of this study was to develop an in vitro method for studying the supersaturation and precipitation behavior of poorly soluble weak bases, and their permeation properties through the lipophilic membrane under the standardized conditions that simulate the small intestine in the fasted state. The purpose was also to test the hypothesis that permeation may have an effect on supersaturation and precipitation kinetics.
The intention was to develop the method for the early-stages of drug development; therefore, it should be relatively fast and inexpensive for studying the small quantities of new drug substances.
Ideally, the method could be used to classify substances based on their preliminary potency to stay in the supersaturated state, precipitation kinetics and the flux through the membrane, and possibly in the future, create a library of substances against which new substances could be compared.
As test compounds, four commercial compounds and two of Orion’s own compounds under the development were selected to this study. The substances were selected based on their different structures and physicochemical properties to develop a method that has some discriminating power for compounds with different precipitation and permeation properties. Initially, the conditions of the method had to be standardized. This was followed by a study of supersaturation and precipitation behavior of the substances with and without the effect of permeation. In addition, the risk of drug precipitation in the small intestine was evaluated based on their solubility at the pH of the stomach and at the pH of the small intestine.
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2.2 Materials and methods 2.2.1 Reagents and media
Felodipine (FEL, purity 100 %) and indinavir (IND, purity ≥ 97.2 %) were purchased from European Directorate for the quality of medicines & healthcare (EDQM). Albendazole (ABZ, purity 100 %) and dipyridamole (DPD, purity ≥98 %) were obtained from Sigma-Aldrich. In addition, two of Orion’s own compounds under development were used in this study; compound Y (COMP Y) and compound X (COMP X). The molecular structures of commercial compounds are shown in table 5. Physicochemical properties of test compounds are shown in table 6. The molecule structures are drawn using ChemDraw Professional, version 15.1.0.144
Precipitation experiments were carried out using a biorelevant FaSSIF pH 6.5 as a medium that was prepared by mixing Simulated Intestinal Fluid (SIF)-powder (Biorelevant.com 2019) and phosphate buffer pH 6.5 (FF6368, Oy FF-Chemicals Ab). According to manufacturer’s directions (Biorelevant.com 2019), 100 mL, 200 mL or 500 mL of FaSSIF was prepared at a time, depending on the need that could be used within 24 hours of preparation. The composition of prepared FaSSIF is shown in table 4. FaSSIF was used to simulate the conditions of the small intestine such as a pH and a composition of the fluids. In addition to FaSSIF, acceptor sink buffer (ASB) was also used as a medium in a µflux experiments. ASB was purchased from PION Inc.
Table 4. The composition of prepared FaSSIF (biorelevant.com). The composition may differ depending on used buffer.
Component Concentration (mM)
Taurocholate 3
Phospholipids (lecithin) 0.75
Sodium 148
Chloride 106
Phosphate 29
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In solubility studies, phosphate buffer pH 2.1 (FF2417, Oy FF-Chemicals Ab), adjusted to pH 2.0 with Orthophosphoric acid 85 % (Merck KGaA) was used to simulate the pH of the stomach. The pH measurements were performed with Mettler Toledo MP225.
Dimethyl sulfoxide (DMSO, Chromasolv + for HPLC grade) was obtained from Sigma-Aldrich and was used as a pre-solvent in precipitation experiments. The methanol (HPLC grade) was from J.T.Baker. Acetonitrile (Ph.eur) and 0.1 % Formic acid (Ph.eur) were from Merck KGaA, and they were used as eluents in HPLC-analysis.
Table 5. Molecular structures of commercial compounds.
Table 6. Physiochemical properties of the test compounds (ABZ= Rathod et al. 2016),
(FEL=Palmelund et al. 2016, sigma-aldrich.com), (DPD= Hörter and Dressman 2001, Bergström et al. 2004), (IND= Choi et al. 2008). Due to confidentiality requirements, only limited amount of information about COMP X and Y is given.
Albendazole Indinavir Felodipine Dipyridamole COMP X COMP Y
Chemical formula
C12H15N3O2S C36H47N5
O4
C18H19Cl2N O4
C24H40N8O4 - - Molecular
weight (g/mol)
265.33 613.36 384.25 504.32 ~485 ~380
pKa 3.4 5.9 (3.7) - 6.4 4.7 3.2
Log P 3.14 2.9 5.3 3.9 2.15 3
Albendazole Indinavir Felodipine Dipyridamole
32 2.2.2 Solubility studies
The solubility of ABZ, FEL and IND were determined in FaSSIF at pH 6.5 and in phosphate buffer at pH 2.0. The solubilities of COMP X and COMP Y were previously determined in the same media by Orion. For each commercial test compounds, the solubility was defined in triplicate (n=3) in both media at 37 °C by a 24-hour shake-flask method. An excess amount of substance powder was loaded to 10 mL Erlenmeyer flask and filled with 5 mL of the adequate medium; FaSSIF or phosphate buffer that was preincubated to 37 °C in an Innova 40 incubator shaker (New Brunswick Scientific). The prepared flasks were placed back into the shake flask apparatus and stirred at 150 round per minute (rpm). After 24 hours, the samples were periodically filtered into HPLC vials (approximately 1 mL) using PTFE syringe filters with a pore size of 0.45 µm. The treated samples were placed into autosampler at 37 °C for HPLC analysis. The concentrations of prepared samples were measured using an Agilent Series 1100 HPLC system, consisting of the autosampler, quaternary pump and UV-dis DaD (Diode array detector) detector. Analyses were performed on Kinetex 2.6 µm C18 100Å 50 x 3mm HPLC column using a gradient elution (Gradient: 0 min to 8 min = B 5 % to B 80 %, 8 min to 10 min = B 80 %, 10 min to 11 min = B 80 % to B 5 %, eluents:
A = 0.1 HCOOH, B = ACN.) with a flow rate 0.8 mL/min. Injection volume was 5 µL and used ultraviolet absorbances were 232 nm for ABZ, 260 nm for IND and 238 nm for FEL. Before the determination of equilibrium solubility, the standard curves were prepared at the range of 1.5 - 150 µg/mL (r2>0.99) for each model compounds. Therefore, the Indinavir samples from phosphate buffer were diluted tenfold in order that presumed concentration hits in the linear standard curve.
The solubility of DPD was evaluated from its concentration-time profile obtained from the supersaturation and precipitation studies.
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2.3 Experimental settings 2.3.1 The µdissolution apparatus
An optimization of test parameters, supersaturation-precipitation and permeation studies were carried out using a µDISS ProfilerTM (PION Inc.). The apparatus monitored UV-spectra (200-700 nm) of the sample in situ with the individual diode array spectrophotometers; each has a separate UV-probe that was dipped directly on the sample (figure 8). At the end of the probes, different pathlength tips were used based on the obtained UV-spectra of each sample.
The apparatus yielded a reliable result if the measured UV-peak was not over 1.5 AU. Used tip lengths and monitored wavelengths are shown in table 7. Different wavelengths had to be used on the acceptor side because absorbance maxima were not necessarily identical in different media and the concentrations to be analyzed were lower. The collected spectra were analyzed using Au PRO™ software, version 5.5.3.5413 (PION Inc., USA). The software calculated the concentration- time data set based on the congruent of the spectrum of the sample and the standard curve. In all analysis, the second derivate of the spectrum was used to reduce the interference of the precipitated
Figure 8. The µdissolution apparatus and separate UV probe with a 5 mm tip pathlenght
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particles (PION Inc., Palmelund et al. 2016). Analyzed data were exported to Excel for result calculations, statistical analysis and graphical presentations.
Table 7. Used tip pathlengths and the monitored wavelengths Compound Probe Tip path
Length donor chamber (mm)
Spectrum wavelengths (nm)
used in FaSSIF
Probe Tip path length
Acceptor chamber (mm)
Spectrum wavelengths (nm) used in ASB
ABZ 20 322-347 20 320-340
FEL 5 400-425 20 280-320
IND 5 270-285 20 275-320
DPD 5 450-475 20 450-475
COMP X 5 300-310 20 288-320
COMP Y 5 359-366 20 356-366
2.3.2 Solvent-shift method
The samples were subjected to the supersaturated state by the solvent-shift method using a DMSO as a stock solvent. The method was based on differences in the solubility of substances in different media; pipetting a solution, to which the substance was well dissolving, into the medium with the lower solubility excited a transitory supersaturated state. The DMSO stock solutions were made by dissolving the accurately weighed amount of test substance in DMSO to correspond the desired concentration when spiking into the medium of the sample. In advance, the same amount of FaSSIF was removed from the medium to keep the total volume constant. Methanol was also tested as a stock solvent, but the model compounds were unable to dissolve in it for sufficient quantities.
35 2.3.3 Initial conditions of experiments
All samples were preincubated at 37°Celsius in the heating blocker before the experiments were initiated. Magnetic crossbar stirrers were used in all precipitation studies and the mixing was on before the stock solution was pipetted into containers. Optimization of test parameters -experiments were initiated using a “staggered start”, where the stock solution was spiked in series into the parallel sample media for 30 seconds, after which the measurements began. In the precipitation and precipitation-permeation studies, the stock solution was pipetted in series into the parallel sample media every 30 seconds. However, delays were removed in the data processing. The theoretical initial concentrations of the samples are summarized in table 8.
Table 8. Determined ranges of the standard curves and initial concentrations used in the precipitation experiments.
Standard curve concentration range (all over r>0.99) (µg/mL)
theoretical Initial concentrations in precipitation studies
donor chamber acceptor chamber
0.5 mM (µg/mL)
0.25 mM (µg/mL)
10-fold (µg/mL)
2,5-fold (µg/mL)
ABZ 2-27 0-20 - - 12 3
COMP X 0-291 0-31 243.3 121.6 470 117.7
COMP Y 0-193 0-31 187.8 93.9 110 27.5
IND 0-310 0-31 307 153.5 - -
FEL 0-355 0-29 192.1 96.1 340 85
DPD 0-292 0-53 251.3 126.2 - -
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2.3.4 Determination of linearity using µdissolution apparatus
Before the supersaturation and precipitation studies, a standard curve was prepared for all individual UV-probe with each test compound. The standard curves for donor chambers of the µflux (figure 9) were prepared in 1:1 methanol-FaSSIF solution, hence, it was impossible to prepare the curves straight into FaSSIF due the poor solubility of the substances. The standard curves for the acceptor side of the µflux were prepared in ASB. Obtained curves (all r>0.99) were saved to the Au PRO™ software and were used throughout the experiments
For detecting the linearity in FaSSIF, stock solutions were prepared for ABZ, DPD, COMP Y and COMP X by weighting the correct amount into the volumetric flask and dissolving in DMSO. An adequate amount of a DMSO stock solution of the compound was pipetted into 200 mL of standard medium followed by approximately 30 seconds of stirring. Thereafter the UV absorbance was determined by spectrophotometers of µDISS profilertm, after which the addition of DMSO stock solution was repeated 5-6 times until the sufficient concentration was obtained. For indinavir and felodipine, standard curves were obtained by detecting UV-spectra from the 5 separated diluents from the 25 mL of 1:1 methanol-FaSSIF stock solution where the DMSO was not used. For all model compounds, the standard curves for the acceptor chamber were prepared in 20 mL of ASB as former described. Determined ranges of the standard curves are also performed in table 8.
Bare methanol and DMSO were also tested as the standard medium of the standard curve, but both solvents caused a distortion in the standard spectrum when compared to the sample. In addition, DMSO could be detrimental to the UV-probes and tips at high concentrations. Methanol concentrations of 20 %, 30 %, 40 % and 50 % in the standard medium were studied, but there was no significant difference between the absorbance peaks across used wavelengths, thus it was decided to use the 1:1 solution to ensure sufficient solubility of the substances.
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2.4 Optimization of test parameters
The parameters to be optimized were stirring speed and concentration of DMSO in the sample. A rapidly precipitating COMP X and a relatively slow precipitating ABZ were selected as a test compound. Initially, the behavior of ABZ was studied in rounded test tubes (figure 9). The effect of DMSO on precipitation was studied at a concentration of 0.5 %, 1 % and 2 %. Total sample volume was 10 mL of FaSSIF. Three DMSO stock solutions were prepared in different volumes such that adding 50 µL, 100 µL or 200 µl caused a tenfold concentration (12 µg/mL) from the previously determined equilibrium solubility of ABZ in the sample. The effect of stirring speed was studied at 100 rpm, 150 rpm and 200 rpm along with DMSO screening.
After screening the effect of parameters in test tubes, test parameter optimization was performed using the µflux chambers (figure 9) with a rapidly precipitating COMP X and ABZ to investigate the effect of the container on precipitation. The total volume used in the chambers was 16 mL of FaSSIF; DMSO stock solutions were prepared such that adding 160 µl and 320 µl will correspond to 1 % and 2 % of DMSO in the sample. The hole between the chambers was closed with a round parafilm piece.
Figure 9. Rounded test tube on the right and µflux component on the left that consists of donor chamber and acceptor side separated by artificial membrane
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2.5 Precipitation studies
The precipitation profiles of the substances were defined at various concentrations based on concentration and/or equilibrium solubility to study the effect of drug concentration on precipitation kinetics. The precipitation studies were carried out using µFlux chambers (total volume 16 mL) in the µDISS Profilertm with stirring speed at 150 rpm. For each model compounds, DMSO stock solutions were made such that 1 % (160 µL) of the solution produced a studied concentration in the sample.
For COMP X, COMP Y and FEL, the studied initial concentrations were 0.5 mM, 0.25 mM, 10- fold and 2.5-fold from the previously studied equilibrium solubility. Only 0.5 mM and 0.25 mM were studied with IND and DPD. ABZ did not reach the desired concentration when 0.5 mM and 0.25 mM initial concentrations were used; only concentrations 10-fold and 2.5-fold were studied.
Table 8 summarized the all used initial concentrations.
2.6 Precipitation-permeation studies
Precipitation-permeation studies were performed using µFlux with an artificial membrane (PVDF, polyvinylidene fluoride 0.45 µm, 1.54 cm2) between the donor and acceptor chambers. The membrane surface was treated with 25 µL of n-dodecane before the donor-side was filled with 16 mL of FaSSIF, and acceptor side was filled with 16 mL of ASB. Studied initial concentrations were 0.5 mM and 0.25 mM with all model compounds expect ABZ. The experiments were initiated by pipetting 160 µL of DMSO stock solution into the donor-side. Both chambers were stirred at 150 rpm. Stirrers were started on before the solvent-shift method.
