The 5th International Symposium on Recent Advances in Food Analysis (RAFA 2011)

Conference organizers, the Institute of Chemical Technology in Prague, the Institute of Food Safety (RIKILT) in The Netherlands and the International Association of Environmental Analytical Chemistry (IAEAC), would like to invite all food scientists from universities, research institutes, national and international agencies, governmental and commercial laboratories, industry and other food business-related companies to attend the 

5th International Symposium on Recent Advances in Food Analysis (RAFA) 2011 at the Clarion Congress Hotel Prague, Czech Republic, 1–4 November 2011. 

Novel analytical applications in food research and a routine analysis are required to meet quality control (QC) and food safety criteria, comply with legal and labelling requirements, determine nutritional value and to detect food fraud/adulteration. It should be noted that, in spite of the legislative efforts, food scandals occasionally occur and can originate from contamination from pesticide residues, veterinary drug residues, endocrine disruptors, processing contaminants, migration from packaging materials or natural sources (including mycotoxins and marine toxins). Additionally, since modern biotechnology methods have been introduced to food production, GM food and food ingredients have become an issue and have led to a strong demand for adequate methods of analysis.  

As a result the science of food analysis is a rapidly evolving and exciting field. In all cases, sampling strategy, sample analysis, data handling and final exposure assessment are crucial steps that are closely interrelated. The desired level of consumer protection and the strict regulation of maximum limits force analytical chemists in food laboratories to lower quantification limits, improve QA/QC and increase sample throughput by introducing new approaches and highly innovative technologies, including the use of bioassays for bioactivity and toxicity screening; omics-based analysis including metabolomics-like profiling; on-line and at-line analysis approaches; spectrometric food profiling (NMR, NIR); (bio)nanotechnology and chip-based methods; solvent-free and other emerging isolation technologies; and hyphenated techniques such as LC–MS and MS–MS, fast GC–TOF-MS, GC–MS–MS, ambient MS and/or comprehensive chromatography (GC×GC, LC×LC).  

At the last RAFA conference in 2009, 530 scientists from 55 countries participated. Fifty seven oral communications (including 13 young scientists') and 440 posters were presented within the scientific programme. Ten vendor seminars and two satellite workshops were also organised. Scientific committee and organizers of the 

 aim to prepare a balanced programme with high-quality presentations followed by stimulating discussions, several satellite events, a state-of-the-art exhibition and an attractive social programme.  

Scientific contributions will be presented by leading scientists through key note lectures and contributed oral and poster presentations. Moreover, a platform for young scientists to present their scientific work will be offered. 

 Student Travel Grants will be also provided. The best poster presentation(s) by a young scientist(s) will be awarded. Several satellite events are planned currently to accompany the conference programme. 

An exhibition of the modern instruments used in food analysis will be on display during the symposium. Vendor seminars will be also organized to introduce recent instrumentation and scientific strategies for advanced food quality/safety control. Oral presentations can be submitted until 

For further information contact Monika Tomaniova on +420 605 423 973, e-mail 

Budapest Congress and World Trade Centre, Budapest, Hungary

15th Annual Green Chemistry and Engineering Conference

ACS Green Chemistry Institute, Washington DC, USA

Sherrington Building, University of Liverpool, UK

The 17th International Symposium on Separation Sciences (17-ISSS)

Hall of Grand Hotel Napoca, Cluj-Napoca, Romania

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Aggregated singletons for automated purification (ASAP) is a purification workflow that provides singleton sample purification, registration and delivery to the materials management department as 30 mM dimethyl sulphoxide solutions for biological screening. The singleton samples submitted are aggregated in a mini-array of 10–12 samples and then are analysed using an automated purification process. The steps in the process include pre-quality control (QC), preparative chromatography, solvent evaporation, reformat dilution and duplication, final QC and final registration. The turnaround time from samples received to delivery to materials management is two or three business days. The final QC data are uploaded to a database and are available to chemists via electronic laboratory notebook software. The final purity, weight recovery and registration information is available in a research database and an e-mail notification of completion is sent to the chemist. ASAP enables a high purification success rate; increases the likelihood of running mini-arrays that generate 5–10 analogues in a final step rather than one or two with the same 2–3 day turnaround time; and provides expert-level service and technology.

The aggregated singletons for automated purification (ASAP) workflow was introduced at Pfizer (Groton, Connecticut, USA) in April 2009. Singletons are unique, individual final compounds synthesized for 

 testing. The main driver and objective behind this initiative was to save synthesis costs and time. Typically a majority of the singletons are made in 100–300 mg amounts. Datasets across various projects show that only ~20% of the singletons survive primary and secondary screenings and hence ~80% of the compounds are made unnecessarily on the large scale. Pharmaceutical chemists can save considerable time and cost by making smaller (30–50 mg) batches. The chemists can submit synthesized compounds (30–50 mg) to ASAP to be purified, registered and delivered to the materials management department as 30 mM dimethyl sulphoxide (DMSO) solutions for biological screening. The workflow for compound synthesis to biological screening is shown in Figure 1.  

 Figure 1: Flow chart showing the steps in the process from compound synthesis to screening. 

The turnaround time from samples received for purification to delivery to the materials management department is two to three business days. Centralizing this activity in the purification group allows greater time for higher value tasks to be completed by practicing chemists; the purification scientists can provide expert-level service and technology, and also more opportunity for harmonization with screening (consistent and high quality samples delivered for biological assays). 

Following are the steps for sample submission to ASAP: The samples submitted are final products (compounds going for biological screening — no intermediates). The crude weight of the compound is 10–50 mg. Some type of an initial sample workup (for example, liquid–liquid extraction, solid-phase extraction and so forth) is highly recommended to remove metals or reagents used during the synthesis. The crude sample is fully dissolved in 900 µL of DMSO, filtered and placed in a 2D bar-coded, matrix capped tube. The crude sample is then registered as an "in-production singleton" sample via Chemistry e-Notebook electronic laboratory notebook software (CambridgeSoft, Cambridge, Massachusetts, USA) using the software's Global Registration tool, which has been customized for Pfizer. The biology assay–screen panel is assigned and the sample is submitted for purification using Pfizer's Auto-Purification submission website. The sample is then dropped off in the assigned submission dry boxes in a Singleton Matrix-Box container. 

The ASAP process is outlined in Figure 2. A total of 10–12 singletons are aggregated in a plate format and associated with a bar code using a 2D Matrix tube reader (Thermo Fisher Scientific, Waltham, Massachusetts, USA). An analytical plate of fixed concentration (1 mg/mL) is created using a Tecan Freedom Evo liquid handling system (Männedorf, Switzerland). The samples in the analytical plate are then analysed using reversed-phase (RP) liquid chromatography–mass spectrometry (LC–MS) and evaporative light scattering detection (ELSD) techniques. The analytical system comprised a Waters 2795 Alliance high performance liquid chromatography (HPLC) system and ZQ mass spectrometer (Milford, Massachusetts, USA) and a Polymer Labs 2100 ELSD system (Agilent Technologies, Santa Clara, California, USA). The initial purity of the sample can range from 5% to 80%. The pre-quality control (QC) gradient methods are 5 min in length with 2 mL/min flow-rates. Different column chemistries, modifiers and gradient conditions are used to develop methods best suited for purification. Even though the samples are aggregated in a miniplate and analysed in a high-throughput mode, a method is developed for each individual sample. The best method and conditions are then transferred to the preparative purification step. A Waters Auto-Purification Fractionlynx system is used for purification. Fraction collection is mass triggered. The preparative methods are gradients run over 10 min. The collected fractions are evaporated using Genevac Mega evaporators (Gardiner, New York, USA). The dry fraction tubes are then weighed on Tecan weighing stations. 

The dried, purified material is dissolved in DMSO to make 30 mM solutions. A maximum of 900 µL of the 30 mM DMSO solution is transferred to a plate. A daughter analytical plate is also created by transferring a 5 µL aliquot and adding enough DMSO to result in a 0.5 mg/mL concentration. Excess 30 mM DMSO solution is transferred to bar-coded 2 mL vials. Tecan liquid handling systems are used for dispensing the DMSO and transfer of samples to the plates and vials. The samples in the vials are evaporated using a Genevac HT-12 evaporator in a two-step evaporation process. 

The final QC is performed using the HPLC–MS–ELSD system or Waters Acquity UPLC/SQD/PL 2100 ELSD units, and the samples are registered if they meet the purity criteria (>80% purity by UV at 215 nm, >85% purity by ELSD and >50% mass spectral purity). Orthogonal QC methods are selected to ensure the final purity of the samples. The solubilized plate (maximum up to 900 µL of 30 mM DMSO stock) is sent to the materials management department for assay preparations. The compound is then released for the requested screening. The dry compounds are registered and shipped to the Pfizer Neat Store. The pre-QC and final QC data are uploaded in Pfizer's Global Analytical database as a PDF and the file also gets linked to the chemist's e-Notebook submission page. The recovery amount, purity and registration data are available through Pfizer's Research database. An e-mail notification is sent to the chemists to inform them that the samples have been delivered to the materials management department. A results spreadsheet is attached that provides detailed information regarding the samples, including the QC gradient conditions, mass observed, retention time, purity data and total recovery after purification. The entire process and data flow are handled through customized software. The software has been specifically designed for automated batch-singleton and library purification workflow. The software enables a user to handle multiple plates with accurate data flow. It also provides structures, chemical properties, CLogD data and acid–base labile prediction information for the compounds associated in the plate. This information helps minimize the time required for method development.  

The ASAP process was introduced in Pfizer R&D in April 2009. A major contributor to the success of ASAP is the strong partnership between the company's Analytical Chemistry and Medicinal Chemistry lines. A point of contact (POC) was established for each project using ASAP to facilitate communication between the two lines. Training sessions were conducted for each project joining ASAP. There was a gradual ramp-up of projects added to ASAP to ensure continuous progress of implementation. 

Figures 3 and 4 show pre-QC, prep and final QC data for samples analysed by ASAP. Figure 3 is an example of a sample that was submitted to ASAP with an initial purity of ~15%. The target mass was isolated and enough material was delivered to the materials management department for screening. Figure 4 is an example of a complex sample. Under acidic conditions, peak 4 in Figure 4(a) was coeluted with the target peak. However, after a method was developed in basic conditions, separation was obtained and the purified compound easily passed the final QC [Figure 4(c)]. 

A high-quality of purified sample is delivered to the materials management department with a 2–3 day turnaround time.  

The process provides a high level of purification expertise and technology. ASAP can purify compounds that chemists find difficult to purify using conventional techniques. 

The process provides a high success rate (>90% samples are registered).

Postpurification analysis: The final purity is assessed by MS–UV–ELSD and QC data are uploaded into the Global Analytical database. 

Final purity information (purity and weight recovery) is available in the research database.  

An e-mail notification is sent to the chemist. Data can be accessed through electronic laboratory notebook software.  

The process increases the likelihood of running mini-arrays to generate 5–10 analogues in a final step rather than one or two, with the same 2–3 day turnaround time. 

The ASAP process allows projects to choose synthetic routes that diverge at a late stage, which is the most effective way to prepare large sets of analogues. 

The ASAP process saves time and lets chemists focus on high-value activities such as making compounds for preliminary toxicity studies. 

To date, more than 5700 singletons have been submitted and >90% of the samples have been successfully purified. ASAP is currently supporting approximately 25 projects across different therapeutic areas. Although the samples are purified in an automated purification mode, the versatility of the technology allows purification of diverse molecules with respect to compound solubility, polarity and molecular weight. The next steps involve enhancing purification technologies such as adding normal-phase chromatography, supercritical fluid chromatography and on-column solvent exchange techniques to increase the scope of available chemical space. 

The authors would like to thank David Price, Rose Gonzales and Mark Noe for sponsoring ASAP and providing resources and staffing. 

 is an associate research fellow in the Analytical Chemistry department at Pfizer Global R&D (Groton, Connecticut, USA).   

Aggregated singletons for automated purification workflow delivers 30 mM DMS solutions for biological screening.

Aggregated Singletons for Automated Purification Workflow

This study presents a headspace gas chromatography method with flame ionization detection (GC–FID) for the determination of ethanol and methanol content in biological fluids such as blood, urine and saliva, emphasizing matrix effects onto headspace analytical results. In this context, a simultaneous procedure was established and validated, and it was revealed that headspace GC for methanol and ethanol determination in all routinely available biological fluids is applicable as a reference method and also in routine diagnostics and monitoring. GC was performed with a run time of 6 min. The method showed linearity in the range of 50–400 mg/dL both for methanol and ethanol (r

= 0.999, respectively) in all specimens with a detection and quantification limits less than 1.5 mg/dL and 2 mg/dL, respectively, as well as with good repeatability. Relative standard deviation (RSD) and percent bias were calculated for interday and intraday accuracy and precision at three concentrations (low 50 mg/dL, medium 200 mg/dL and high 400 mg/dL) for each biological fluid. A recovery rate of over 90% was obtained. Due to matrix effects of specimens, slight variations in validation data were presented and compared. The method and the obtained results suggest that the use of headspace GC could be extended from confirmatory analyses to routine application in toxicology laboratories.

Evaluation of ethanol in biological samples, including blood, urine and saliva, is frequently requested for legal purposes, such as driving under the influence and postmortem alcohol evaluation.

  Ethanol intake also has been associated with violent death.

  Additionally, methanol determination has recently gained a great deal of importance and has become an interesting scientific area in relation to unintentional oral ingestion by food and beverages causing blindness, coma and death by respiratory and cardiac arrest.

Methanol and ethanol testing has been performed using blood as the biological material for years. However, there is increasing interest in urine and saliva as a biological specimen because both are obtained in a noninvasive way.

  No significant endogenous ethanol production is observed in urine from healthy patients.

				 Furthermore, postmortem ethanol production in urine is less when compared with blood because negligible quantities of glucose are excreted in urine from individuals having normal carbohydrate metabolism. However, the probability of diabetes must always be kept in mind.

  The concentration of ethanol in saliva accurately reflects blood ethanol concentration as the ratio of the blood flow to the tissue mass of the salivary gland is high.

Numerous chemical and enzymatic methods have been described to determine volatiles in biological materials.

  Furthermore, chromatographic methods certainly stand out with higher precision.

				 For example, liquid chromatography (LC) has still been used as an analytical technique for the assessment of ethanol in matrixes other than human specimens, as well.

  However, combining ease of application with precision gas chromatography (GC) equipped with headspace is the most reliable method in use.

Extraction is the most important step for an analytical procedure for separation of the organic compound from the biological material. Regarding the volatile compounds, such as alcohols, headspace-GC analysis allows direct injection of specimens and is the most common procedure used.

				 However, in this technique, depending upon the sample matrix, the resulting data can vary mildly, which is explained by matrix effect.

In this study, a simultaneous and reliable headspace-GC–flame ionization detection (FID) method was validated to establish methanol and ethanol assessment in blood, urine and saliva as a routine forensic–toxicological analytic application. In addition, the influence of the specimen matrix onto the chromatographic response was also investigated for each of the biological fluids used for routine analysis. Therefore, the main purpose and the novelty of this article fundamentally depends upon validation and comparison of specimens in this respect. 

-butanol were obtained from Merck (Gernsheim, Germany). Headspace vials were purchased (Agilent Technologies, Palo Alto, California, USA). GC was performed on an HP 6890 series II gas chromatograph (Agilent Technologies) with a flame ionization detector (FID). The system was equipped with an HP 7694 E Headspace Sampler (Agilent Technologies). A 30 m × 320 µm, 0.25 mm 

 HP-Innowax (Agilent Technologies) column was used. Headspace conditions were adjusted according to the parameters described in the study conducted by Wasfi and colleagues.

				 Vial equilibrium time was set to 10 min. The sample volume was 1 mL and sample loop was 3 mL in volume. Headspace oven temperature, sample loop temperature and transfer line temperature were fixed to 70 °C, 80 °C and 90 °C, respectively, to avoid the possibility of condensation until injection. The GC oven temperature was held constant at 110 °C for 6 min. The GC system had an injection temperature of 180 °C and a detector temperature of 250 °C. 

 All biological specimens were collected by the volunteer laboratory crew of Ankara University Institute of Forensic Medicine. For collection of saliva and urine, clean polypropylene vessels were used by each volunteer; urine and saliva samples were collected, providing a pool. Blood samples from each volunteer were collected in anticoagulant tubes and pooled prior to analysis. Each pooled specimen was mixed by vortex before use. All specimens were kept at +4 °C until the time of analysis. 

Blank specimens (namely water, blood, urine and saliva) (800 µL) were placed into clean glass headspace vials containing 100 µL of 800 mg/dL 

-butanol as internal standard (IS). In the next step, 100 µL of ethanol and methanol standards was spiked, yielding concentrations of 50, 100, 200, 300 and 400 mg/dL. The total volume was 1 mL, achieving an IS concentration ten times diluted to 80 mg/dL. Each vial was sealed with a rubber cap and an aluminum crimp seal immediately after addition of the methanol and ethanol standards. Calibration standards were prepared five times for each specimen at each concentration. The precision within-run and between-run tests were performed with five replicates at concentrations of 50, 200 and 400 mg/dL. For evaluations of recovery, 200 mg/dL was chosen as mid-concentration and 10 replicates of this concentration were tested. 

 To overcome the risks of any artefacts during analysis, the IS was used. Thus, peak areas were measured and calculations were carried out considering peak ratios of analyte to IS. 

The method for each specimen was validated fully, as were previous validation studies,

  to follow criteria in agreement with ICH guidelines.

 The method demonstrated excellent chromatographic specificity with no endogenous interference at the retention times of methanol, ethanol and the IS (3.78, 3.61 and 5.30 min, respectively). The representative chromatogram of blood spiked with ethanol and methanol is displayed in Figure 1. Retention times for other specimens observed exactly the same revealing lack of matrix affect on retention time and duration of the analysis. 

 Figure 1: Representative chromatogram of  spiked human blood containing 200 mg/dL methanol, 200 mg/dL ethanol and 80  mg/dL n-butanol (IS). Peaks: 1 = methanol, 2 = ethanol, 3 = n-butanol.			

After establishing the chromatographic conditions, separate calibration curves were prepared for each specimen at ethanol and methanol concentrations of 50–400 mg/dL. For each concentration, five individual replicates were injected and linearity was obtained with the correlation coefficients (

) equal to 0.998 and 0.999, respectively, for methanol and ethanol in all biological specimens. 

The recovery tests of this analytical procedure were performed by spiking blank water, blood, urine and saliva specimens with 200 mg/dL of methanol and ethanol. A recovery rate of over 90% was obtained, and the recovery results are shown as percentages and ranges in Table 1. 

Table 1: The results of recovery studies for blood, urine, and saliva spiked with 200 mg/dL methanol and ethanol.			

 Precision, defined as relative standard deviation (RSD), was determined by five individual replicates at three different concentrations (

= 5). Accuracy, defined as % bias, was also determined at the same concentrations (

= 5). Intraday and interday accuracy and precision studies were carried out as well. Samples solutions of biological specimens were freshly prepared on the same day (intra) and on five consecutive days (inter). Detailed data of accuracy and precision studies are tabulated in Table 2. 

Table 2: Intra- and interday accuracy and precision data of water, blood, urine, and saliva spiked with methanol and ethanol			

 The limit of detection (LOD) and lowest limit of quantification (LOQ) were determined based on the standard deviation of the response and the slope of the calibration curve, according to ICH guidelines

  (LOD = 3.3 σ/S, LOQ = 10 σ/S, where σ is the standard deviation of the response and 

 is the slope of the calibration curve). Table 1 shows LOD and LOQ values of methanol and ethanol calculated for water, blood, urine and saliva. 

Comparison of Specimens and Matrix Effects:

 Regarding different specimens, dissimilarities in resulting data of validation parameters (Table 1 and Table 2) were observed. Intraday studies showed that for methanol and ethanol analysis, urine conduces to most precise results at mid-concentration in contrast to blood. For interday studies, high precision was obtained in saliva as well. Similar to precision data, analysis of both methanol and ethanol in urine and saliva had the highest accurate results for intra- and interday studies (Table 2). No matrix effect was presumed for water in this study due to constant homogeneity and no other molecule in its composition other than water itself. However, with rich protein content, blood certainly has the strongest matrix, affecting the volatile substance to be analysed in the headspace-GC system. In this respect, detection and quantification limits and recovery data were affected as well. Table 1 shows that blood has the lowest recovery rate and highest detection-quantification limits. 

In headspace-GC analysis, in addition to the phase transition between liquid and gas phase, volatile analytes are affected only by the physical and chemical properties of the sample. Therefore, the effect of matrix content on the analytical signal should be considered in particular.

  As performed in the present study, addition of IS is one of the suggested solutions for minimization of matrix effect.

A headspace-GC–FID method was established for simultaneous measurement of methanol and ethanol and was validated in terms of reproducibility, sensitivity, accuracy, precision and detection limits. It was revealed that headspace GC for methanol and ethanol determination in all routinely available biological fluids is applicable as a reference method and also in routine diagnostics and monitoring for forensic–toxicological and analytical purposes. For nonadvanced local toxicology laboratories, the method presented here stands out as simple and easily applicable.  

The influence of the matrix composition on the chromatographic response was investigated for each biological fluid. The matrix effect on headspace analysis of methanol and ethanol was determined in blood in comparison to saliva and urine, and had less protein content. 

The presence of proteins indicated stronger matrix effects in headspace-GC analysis. Matrix effect of blood was determined more in comparison to saliva and urine, which have less protein content. 

This study was supported by grants from the Ankara University Institute of Biotechnology Research Fund, project number 2004-118.  

2. D. Zuba, A. Parczewski and M. Reichenbacher, 

3. C.L. Winek Jr., C.L. Winek and W.W. Wahba, 

4. S.J. Heishman, E.G. Singleton and D.J. Crouch, 

14. B.S. Martinis, M.A.M. Ruzzene and C.C.S. Martin,

A simultaneous headspace-GC–FID method was validated to establish methanol and ethanol assessment in blood, urine and saliva.

Simultaneous Headspace-GC–FID Analysis for Methanol and Ethanol in Blood, Saliva and Urine: Validation of Method and Comparison of Specimens

What do you do when a peak grows over time?

I have been working with a woman, who attended one of my classes recently, to solve a problem with a liquid chromatography (LC) method in her laboratory. The problem makes a good case study for "LC Troubleshooting", because it allows us to review how to attack a problem that may not have an easy fix.  

The method is for the analysis of a pharmaceutical product in a cream formulation. A preservative is added to the formulation at a 0.2% level, but has a puzzling behaviour in one of the container types in a 12-month stability study at 25 °C. In a 1 oz tube, the preservative peak increases by about 20% from the day 1 concentration, but in a 2 oz tube under the same storage conditions, the same formulation shows no increase in the preservative. At a higher temperature, accelerated stress condition, no change is seen in either container. The challenge is how to separate the preservative from the interference and/or identify the interference so that it can be eliminated, if necessary. 

The method is run on a 150 × 4.6 mm, 5 μm particle C

 column thermostatted to 35 °C and uses a 35:65 methanol:buffer mobile phase; UV detection is at 270 nm. The buffer is prepared by adding 1 mL of triethylamine (TEA) to 1 L of water and adjusting the pH to 3.0 with concentrated phosphoric acid. Sample is prepared by dissolving an aliquot in methanol, then diluting to 50:50 methanol:water followed by injection of 50 μL of this solution. The preservative peak is eluted at about 7 min with a flow-rate of 1 mL/min. 

When confronted with problems like this, I like to take a four-step approach:  

2) Examine the existing method for potential problems.  

3) Plan some experiments that might solve the problem. 

4) See if there are any alternative  approaches that make sense.  

The goal of the current work is to isolate the impurity from the preservative. Once this is done, a determination can be made to decide whether the formulation needs to be modified to avoid the appearance of the impurity or if it can be ignored. I suspect that it can be ignored, because at ≈20% of a 0.2% peak, the concentration would be less than the 0.05% reporting level. 

Let's next take a look at the existing method — is there anything that raises a possible red flag? The first concern I have is when I see triethylamine-phosphate (TEAP) used as a buffer. This was a very common buffer when the older, low-purity, type-A silica columns were in use. The addition of TEA to the mobile phase made sense, because it acted to help suppress active silanol groups on the silica-based column packing. 

In these older columns, there was a significant amount of metal contamination, sometimes >100 ppm, of iron and aluminium. These metals served to "activate" silanol groups to form cation exchange sites on the surface. These were a primary cause of the significant peak tailing observed for bases when analysed on such columns. With today's higher-purity, type-B silicas used for the support in most columns, the metal content is reduced to less than 5 ppm in some cases, so the presence of ionized silanol groups is much less of a concern. This is especially true when the mobile phase pH is low, such as pH 3 used in the present method. For these reasons, TEA is seldom used today. Does it hurt? I doubt it, but I'm a strong believer in the KISS principle — Keep It Simple, Stupid. In other words, extra additives to the mobile phase that don't contribute positively to the separation just make the mobile phase more complicated. And more complicated means more chances for something to go wrong. So this suggests to me that the method may have been one that was based on something from the past and just extended to new conditions. 

A second concern with the current method is the injection of a fairly large volume of sample in a solvent that is stronger than the mobile phase. As a general rule, you don't want to inject more than about 15% of the volume of the peak of interest if you inject, with the mobile phase as the injection solvent; less for a stronger solvent. To see if the current conditions are reasonable, we can make some estimates.  

We need to estimate the peak volume of the peak of interest. This is based on the column efficiency and the retention time. A well-packed column operated with ideal test solutes will have a plate height, 

); for more realistic conditions I like to use 

. The column efficiency or plate number, 

 is the length of the column (same units as 

 is the particle size in microns. For the present column, then 

= (150 / 5) × 300 ≈ 9000. Let's call it 

= 10000 for more convenient mental math — we'll need the square root of this, 100, in a moment. 

, we need to figure out the peak volume. The standard way to calculate 

 is the peak width at baseline between tangents drawn to the sides of the peak. We can rearrange this and solve for 

 = (4 × 7)/100 = 0.28 min. We need to convert this to volume, so 0.28 min × 1 mL/min = 0.28 mL = 280 μL. I mentioned above that for injection in mobile phase, it is good to inject no more than 15% of the peak volume. 280 μL × 15% = 42 μL. So the 50 μL injection is a bit large if it were in mobile phase, but the sample is in 50% methanol and the mobile phase is 35% methanol, so it is in a stronger solvent.  

For stronger solvents, smaller volumes will be needed or extra peak broadening is likely. It would be easy to check to determine if this is a problem with the present method by injecting 50 μL, 25 μL, 10 μL and 5 μL aliquots of sample and measuring the peak width or plate number of the first peak of interest.  

If the smaller injections improve the plate number, the method should be changed accordingly. Perhaps it would be possible to dissolve the same amount of sample in a smaller volume of methanol and dilute with more water so that the sample concentration was the same, but the injection solvent was ≤35% methanol. Under such conditions, 50 μL injections would probably be OK. 

Our next task is to design some experiments that may allow us to separate the interference from the preservative. Complicating this is the presence of several other peaks in the chromatogram resulting from other formulation components plus the active ingredient. 

In several recent articles, we have looked at some of the variables that affect selectivity, especially the mobile phase %-organic,

  we have found that we can rank the separation power of selectivity variables for a wide range of compounds as:

where %B is the percent organic solvent in the mobile phase (10% change assumed), 

 is the gradient time in gradient elution (three-fold change), °C is the column temperature (10 °C change), solvent type is a change from methanol to acetonitrile or vice versa, column type is a change in F

 >65 (assumes ionizable compounds; >100 for non-ionizable ones), and a pH change of 5 units (applies only to ionizable compounds). 

I would start by investigating a ±10% change in methanol in the mobile phase and a ±10°C change in the column temperature; gradient time does not apply to this isocratic separation. The Rule of Three suggests that retention will change about three-fold for the 10% organic change. We would expect about 15–20% change in retention for a 10 °C temperature change if we assume 1.5–2% change in retention for each 1 °C change in temperature. Rather than trying to identify the location of the interference peak, I would focus on the peak area of the preservative. With overlapping peaks, the peak area is about 120% of the expected area, so any reduction in this area is evidence that the separation is improving. 

Next would be a change in solvent type, substituting acetonitrile for methanol. Because acetonitrile is a stronger solvent than methanol, I would start with 5–10% less acetonitrile, or 25–30% acetonitrile instead of 35% methanol. Again, watch for a change in the preservative peak area. Tetrahydrofuran can make large changes in selectivity, but is used less often today because of its poor UV transparency at <240 nm. However, the present method uses 270 nm for detection, so this limitation does not apply. It might be interesting to try tetrahydrofuran instead of methanol; I would start with 20–25% tetrahydrofuran. An alternative would be to substitute 10% of the methanol by tetrahydrofuran to obtain some selectivity difference. 

When it comes to a change in the column type, consult the USP-PQRI database

  to find a column with a significantly different selectivity. As the interference is unknown, we don't know if it is ionizable or not, so I would look for a column that had a combined F

 value of >100 and a column B-value of >0.15 (both of these are listed in the database

I don't know if there will be changes in selectivity with a change in pH, because we don't know if the impurity is ionizable or not, but pH is a very powerful variable if ionizable compounds are present. When we are looking for significant changes in selectivity, a large change in pH is suggested — perhaps 4–5 units of change would be a good place to try. 

In each case, when changing the variables, track the peak area of the preservative to look for changes. If two or more experimental runs are made with a variable (for example, two different temperatures), and changes in peak area are observed, it may be useful to use one of the retention mapping programs, such as DryLab (Molnar Institute, Berlin, Germany) to get more information from the collected data. If we use the reference conditions as one run and change only one variable (for example, the percentage of organic), we'll have the two calibration runs needed for retention mapping. 

If none of the changes shows promise, you could change to a different chromatography mode. Normal phase (NP) chromatography would be a good choice. Normal phase separates compounds based on adsorptive interactions between the sample molecules and the stationary phase. Another option would be HILIC (hydrophilic interaction chromatography), which separates based on a combination of partition and electrostatic interactions. The separation mechanism of both of these techniques is significantly different from reversed-phase (RP), which relies on hydrophobic interactions between the sample molecules and the stationary phase, so different selectivity would be expected. 

Another way to approach the current problem would be to try to isolate the impurity from the container. The impurity shows up when a smaller container size is used. One possible reason for this is that the surface area to volume ratio should be larger for the smaller container, so the impurity might be below a noticeable concentration in the larger tube. I would try to see if I could extract the impurity from the container, which is a plastic tube in the present case.  

Start with a new tube without any labels on it. If a label-free tube is not available, try to scrape the inner surface to get sufficient sample without any printing on it. The tube or sample of the tube should be ground or chopped to increase the surface area, then extracted in organic solvent, such as by sonicating in a glass test tube. I would try extracting separate aliquots in a chlorinated solvent (for example, methylene chloride), methyl-t-butyl ether, an aromatic solvent (for example, toluene), methanol and acetonitrile. The objective is not to dissolve the tube, but to extract the impurity from the tube matrix. The extraction solvent then could be evaporated to dryness and the residue redissolved in a small volume of mobile phase.  

Chromatograms resulting from injection of these extracts will hopefully contain a peak that is eluted at the same retention time as the preservative. This peak would presumably be the interference. Now this sample could be used as a reference standard to be injected independently and compared with the retention of a reference standard of the preservative. When dealing with only two peaks and in independent injections, the effects of the investigations of the various selectivity variables above will be much easier to interpret. 

If the isolated impurity can be separated from the preservative and the same conditions result in a reduction of the area of the preservative in the aged sample to ≤100% of the expected amount, it is likely that the isolated compound and the impurity are the same. A sample of the isolated material could then be submitted to mass spectrometry or other further analysis to determine its identity.   

The present problem of over-recovery of a preservative on aging of a pharmaceutica product serves as a good example to explore possible approaches to solving a problem of overlapping peaks in an LC separation. The approach discussed above can be used as a general technique to solve similar problems in other sample types. It is important to establish the goals of the project before you start, then have a systematic approach to solving the problem. If you ignore these two important points, it is easy to get caught in a problem-solving approach that relies more on hope and luck than scientific discipline. 

is vice president of LC Resources, Walnut Creek, California, USA. He is also a member of 

 editorial advisory board. Direct correspondence about this column should go to "LC Troubleshooting", 

4A Bridgegate Pavilion, Chester Business Park, Wrexham Road, Chester CH4 9QH, UK, or e-mail the editor, Alasdair Matheson, at 

LC Troubleshooting

The Case of the Too Big Little Peak

Ion chromatography (IC) is routinely used for ion analysis. However, the presence of high concentration of matrix ions in some samples can pose a challenging analytical problem especially when pursuing trace level analysis. Often the matrix ions interfere with the analysis of the target analytes causing peak broadening and affecting the sensitivity of peaks of interest in a deleterious fashion. In this article, we discuss an inline two dimensional matrix elimination ion chromatography (MEIC) method to analyse samples containing high levels of matrix ions. The method was successfully applied for the analysis of trace level of bromate ion in the presence of large amount of interfering matrix ions in a variety of environmental water samples.

Ion chromatography (IC) with suppressed conductivity detection is a primary method established for analysing ions in aqueous sample matrices such as drinking water and waste water. In fact, water analysis is the biggest application of IC.

  The technique provides an easy method for analyte quantification and is convenient for contaminant monitoring. Over the years, with the introduction of low noise suppressor technology, in-line eluent generation, continuously-regenerated trap columns (CR-TC) and carbonate removal devices (CRDs) for the removal of carbonate from the eluent and the sample, the detection limit of IC has been improved greatly, facilitating the direct analysis of trace level analytes.

For the analysis of trace- level analytes in a low ionic strength matrix, such as ultra pure water, a simple large loop injection or standard pre-concentration method is adequate to improve the method detection limit. However, for samples which contain a high ionic strength matrix, such as in some drinking waters and waste waters, the determination of trace level analytes becomes more challenging. The presence of high levels of matrix ions in these samples can overload the separator column, causing the analyte peak shape to smear or distort. Furthermore, the matrix ions can co-elute with the analytes of interest making analysis difficult with a direct injection of the sample. The analysis becomes even more problematic when a concentrator column is used as a high concentration of matrix ions can act as an eluent and elute the analytes off the concentrator column.  

For samples containing a relatively high level of analyte (concentration in the mg/L regime) a simple sample dilution can be used to lower the matrix ion concentration and minimize the matrix effect. However, if the analyte concentration is low, such as in the low μg/L regime, the sample dilution will also lower the analyte concentration. which makes trace analysis difficult. 

One strategy adopted was to pursue post-column derivatization to selectively derivatize the peak of interest to increase its response, relative to the underivatized matrix ions.

  Usually a UV/vis detection scheme was commonly used with this strategy. However, many of the analytes commonly encountered in drinking water samples do not possess good chromophores for UV/vis detection, and therefore are not suitable for this approach. Furthermore, many of the post-column reactions require harsh reaction conditions and toxic reactants. Additionally, derivatization is an additional processing step and can be prone to error. 

Another approach used to address the challenge of trace analysis in the presence of high matrix ion concentrations, included the use of higher capacity columns that provided a better peak capacity to handle the large amount of matrix ions. Although this method was successful to some extent, the increased capacity also required the use of a higher eluent strength and increased the overall run time. Furthermore, based on the capacity of available commercial columns, this method was not suited for analysing the wide range of matrix ion concentrations present in some drinking and waste water samples. 

Another approach was to pursue sample pretreatment solutions such as using a solid phase extraction (SPE) cartridge.

  For example, a pretreatment step with a silver cartridge can selectively remove chloride from the water samples. However, the SPE methods are only selective to some ions and can be labour intensive, inconsistent and prone to errors (operator or operation related). The SPE phase also needs to be chosen judiciously so that only the matrix ions are eliminated without affecting the target analytes. For example, a silver form cartridge could be used for removing sulphides. However, it should be noted that this phase also removes thiosulphate making sulphur speciation difficult.

Another approach that was more automated than those previously discussed was a "heart-cut" column-switching approach that was used to divert the matrix ions from the separated analyte peaks.

  A pre-column and a diverter valve were installed in front of the separator column. Only the portion of eluent that contained the analyte of interest was allowed to pass through to the separator column, while the rest of the matrix ions were diverted before the separator to waste. The resolving power of the above approach was marginal and due to the system pressure constraints the pre-column was limited to a shorter length guard column for the matrix diversion step. 

When using IC with suppressed conductivity detection, the post suppressor effluent is weakly dissociated. For hydroxide eluent, the suppressed effluent is weakly dissociated deionized (DI) water.  

A simplified version of the "heart-cut" column-switching approach was implemented by adding a concentrator column after the suppressor.

  This is a single separator column approach, where the portion of the suppressed effluent containing the ions of interest is selectively concentrated onto a concentrator column and re-analysed with the same separator column. This approach overcame the pressure limitation of the previously discussed "heart-cut" approach. However, the analysis time increased with the matrix concentration and several runs were required for analysing a sample containing high levels of matrix ions.

  Additionally, the presence of highly retained ionic species from one run may interfere with the analysis in the following run, thus mandating the need to run blanks between injections of samples containing high levels of matrix. Overall, the use of this method is limited because the run time is prohibitive and highly dependent on the matrix concentration. 

Recently, a new two dimensional heart-cut IC method called matrix elimination ion chromatography (MEIC) was introduced to analyse perchlorate in the presence of high ionic strength matrix.

  A high capacity IonPac AS20 column (Dionex, Sunnyvale, California, USA) was used as the first dimension column to separate perchlorate from the matrix ions. After suppression, the portion that contained perchlorate, the ion of interest, was focused onto a concentrator column and then analysed in the second dimension. Ideally, a column with a different selectivity should be used in the second dimension to impart a different selectivity.  

The benefit of a different selectivity is that the resolving power is significantly enhanced and the chance of another analyte coeluting with the analyte of interest is greatly reduced. Lin et al. showed that 

-chlorobenzene sulphonate eluted very close to perchlorate using an IonPac AS16 column (Dionex).

  Switching to a different chemistry with a different selectivity for the first dimension, using an IonPac AS20 column, ensured no possibility of interference from the presence of 

-chlorobenzene sulphonate for the analysis of perchlorate. Furthemore, Lin's publication also used a 2 mm separator column in the second dimension. The use of a smaller cross sectional area column in the second dimension mandated a four-fold lower operational flow-rate relative to the first dimension 4 mm column, resulting in a four-fold increase in sensitivity relative to the first dimension using a concentration-sensitive detector such as a conductivity detector (CD). The detection limits can be substantially improved further if a capillary column format is used for the second dimension analysis. 

Bromate is a disinfection byproduct typically encountered when water is disinfected with ozone during the water treatment process. It has been shown that bromate is a possible carcinogen and long term exposure to bromate can pose significant health risks. Currently bromate is regulated around the world by various environmental agencies. The US EPA regulates bromate at a maximum contamination level (MCL) of 10 μg/L and a maximum contamination level goal (MCLG) of 0 μg/L. 

There are several published US EPA methods for bromate analysis.

  EPA method 300.1 used a large loop injection with an IonPac AS9-HC column. Subsequently, a hydroxide-selective column, IonPac AS19 developed by Dionex was shown to provide a better detection limit.

  Although both methods worked well for some samples with limited matrix ion concentration, samples containing higher levels of matrix ions required an offline SPE treatment. In this study, we show the application of an inline MEIC method for bromate analysis in municipal drinking water samples and in commercial bottled waters. 

 All experiments were performed using Dionex columns  and an ICS-3000 ion chromatographic system (Dionex) consisting of a dual pump (DP) module, a dual eluent generator (EG) module, detector/chromatography (DC) module, two six-port injection valves and an AS Autosampler. The column and compartment temperature were maintained at 30 °C. Chromeleon chromatography workstations (Dionex)were used for the instrument control, data acquisition and processing. Figure 1 shows the schematic of the MEIC setup.  

Figure 1: The experimental setup for matrix-elimination ion chromatography (MEIC).			

An IonPac AS19 analytical column (4 × 250 mm) and an AG19 guard column (4 × 50 mm) were used for the first dimension analysis. The hydroxide eluent was generated from EGC KOH cartridge by feeding in a stream of deionized water. A continuously-regenerated anion trap column (CR-ATC) was used to remove any residual contaminants in the deionized water feed. An ASRS 300 4 mm suppressor was operated under external water mode. A PEEK tubing of 1000 μL was used as the sample loop. A carbonate removal device (CRD200 4 mm) was placed after the suppressor for removal of carbon dioxide from the carbonate peak in the sample. The addition of the CRD also helped to lower the amount of carbonate in the second dimension. The cell effluent was directed to the injection valve in the second dimension. 

An IonPac AS24 analytical column (2 × 250 mm) and AG24 guard column (2 × 50 mm) were used for the second dimension analysis. The hydroxide eluent was generated from EGC KOH cartridge by feeding in a stream of deionized water. A CR-ATC was used to remove any residual contaminants in the deionized water feed. An ASRS 300 2 mm suppressor was operated under external water mode. A Carbonate Removal Device (CRD200 2 mm) was placed after the suppressor for removal of carbon dioxide from the carbonate peak in the sample. A UTAC-LP1 concentrator column was placed in the second injection valve for concentrating the target sample. 

 Deionized water (18.2 MΩ cm, Millipore, Billerica, Massachusetts, USA) was used for eluent and sample preparation. Sodium bromate was purchased from Sigma-Aldrich (St Louis, Missouri, USA). A certified 1000 mg/L bromate solution was obtained from Ultra Scientific (N. Kingstown, Rhode Island, USA) and used as a secondary bromate standard. 

 A stock solution of 1000 mg/L bromate was prepared by dissolving 0.118 g of sodium bromate in DI water and diluting to 100 mL. The calibration standard solutions were prepared by serial dilution of the stock solution. 

Ethylenediamine (EDA) is used as a preservative reagent for bromate and is added to the drinking water samples to remove any hypobromous acid in the drinking waters. A stock solution of 100 mg/L ethylenediamine was prepared by diluting 2.8 mL of EDA (Sigma-Aldrich) in DI water to a final volume of 100 mL. When the EDA stock solution is stored at 4 °C, the stock solution can be used for more than a month. Each sample and standard was spiked with 50 mg/L EDA by adding 50 μL of EDA stock solution into 100 mL of sample and standard solution. 

 The level of the matrix ions were chosen to represent a higher limit for most of the drinking water in the public drinking water systems. A synthetic high ionic water matrix, which consists of 100 mg/L chloride, 100 mg/L bicarbonate, 100 mg/L sulphate and 10 mg/L each of N (as nitrate) and P (as phosphate), was prepared as specified in the US EPA method 300.1 from the corresponding salts. 

The drinking water samples were obtained from various public drinking water sources, following the standard EPA procedure, and stored at 4 °C. The bottled water sample was purchased from the grocery store and used without any treatment. 

 The ideal first dimension column should provide good separation between the analyte and the matrix ions. For bromate analysis, chloride is the main peak eluting next to the bromate peak. If the two peaks elute too close to each other, there will not be an adequate window for heart-cutting the peak of interest. The presence of other ions will increase the overall ionic strength of the sample, leading to bromate retention time shift and peak broadening. The IonPac AS19 column (4 × 250 mm) was chosen as the first dimension column because it is a hydroxide-selective phase and a high capacity anion exchange column that was capable of handling the high matrix concentration. It provided good separation of bromate from chloride. 

The benefit of choosing hydroxide as the eluent is because the suppressed effluent is water and it provides the best environment for concentrating and capturing the peak of interest into the concentrator column for further analysis in the second dimension. Additionally, the water background provides the best sensitivity for ion analysis.  

Figure 2 shows the analysis of bromate with the IonPac AS19 column in the presence of various concentrations of matrix ions in a standard ion chromatography setup. As the matrix concentration increases, the retention time for the bromate peak shifts to earlier retention time, the peak also became broad along with a concomitant reduction in the peak height. These effects made the peak area integration a difficult task and affected the overall bromate quantification.  

Figure 2: The effect of matrix concentration on the bromate peak shape. The matrix consists of chloride and sulphate and the concentration is: a) 0; b) 50 mg/L; c) 100 mg/L; d) 150 mg/L; e) 200 mg/L and f) 250 mg/L.			

 For the MEIC approach, the cut window is defined here as the time window required for setting the valve timing to capture the peak of interest entirety into the concentrator column. The start of the cut window was determined by the injection of high ionic water matrix spiked with 15 μg/L bromate. Under this condition the bromate peak became a broad hump, and the front of the peak indicated the bromate peak started to elute off the first dimension column. Typically, the start of the cut window was set 0.4 min before the rise of the bromate peak. The end of the bromate peak was determined by the injection of 15 μg/L of bromate prepared in deionized water (termed as the reagent water sample). An additional 0.4 min was added to the end of the bromate peak to compensate for the system delay volume between the detector cell and the second injection valve. The overall cut window was 1.8 min wide for this setup. This cut window was adequate for the complete capture of the bromate peak from the suppressed effluent in the first dimension. Figure 3 shows an example of the cut window determination using the above method.  

Figure 3: The first dimension analysis of the bromate peak in a) reagent water and b) high ionic water. The bromate concentration is 15 Î¼g/L. The bromate retention time (tR) is 9.2 minutes. The start of the cut window (t1) is 8.0 minutes and the end of the cut window (t2) is 9.8 min.			

The cut window should be monitored continuously with the first dimension analysis during the life of the column and adjusted accordingly to ensure complete capture of the bromate peak. 

 The ideal second dimension column should provide good separation between the bromate peak and any other contaminants. Since the majority of the matrix ions were already eliminated in the first dimension, the second column only needed to provide good separation between the bromate peak and other peaks that elute close to the bromate peak in the first dimension. The IonPac AS24 column was chosen for the second dimension analysis. This column is also a hydroxide-selective, high capacity anion exchange column. The column provided excellent separation between bromate and other peaks. Figure 4 shows the second dimension analysis of the bromate peak, both in reagent water and in the presence of high ionic water matrix. Most of the chloride peak was removed by the first dimension column, and the remaining small amount of chloride did not affect the bromate peak recovery and integration. This figure illustrates that the method provides consistent recovery even in the presence of matrix ions.  

Figure 4: The second dimensional analysis of 15 Î¼g/L bromate (Peak 1) in a) reagent water and b) high ionic water matrix. The bromate peak shows excellent recovery in both sample matrixes.			

Table 1 shows the precision and accuracy of the present method for the two samples with a spike level of 0.5 μg/L and 5 μg/L of bromate respectively. The recovery values are well within the US EPA set limit of ±25% for samples containing bromate concentration within 5 times the minimum reporting level (MRL) and ±15% for those above five times the MRL.

The peak area obtained from the first dimension was also compared with the peak area from the second dimension. Table 2 listed the bromate peak area from the first and the second dimension analysis in reagent water. A larger peak area was obtained from the second dimension. The signal enhancement was approximately proportional to the ratio of the cross section area of these two column formats, yielding nearly a four-fold increase in sensitivity. Furthermore, this method is not limited to the 4 mm/2 mm column format shown here, and the second dimension can be lowered further to a 1 mm column format, or even a 0.4 mm capillary column format, thus is theoretically capable of providing further enhancement of the sensitivity.  

Table 2: Response factor for 15 Î¼g/L bromate between the first and second dimension analysis.			

 The method performance was evaluated by pursuing method linearity, MDL and precision and recovery tests. 

The peak area response versus concentration was plotted for bromate in the concentration range of 0.15–15 μg/L in reagent water. A quadratic fit was used to fit the data as shown in Figure 5. A good correlation coefficient of 0.9997 was obtained. The method also showed very good method detection limit (MDL), precision and recovery. The MDL was determined by performing seven replicate injections of 0.2 μg/L bromate standard in reagent water. Using the calculation listed in US EPA method 300.1, the MDL for bromate is determined to be 0.037 μg/L. This is substantially lower than the detection limits reported in US EPA method 317.0 (0.12 μg/L) and 326.0 (0.17 μg/L), where a post-column derivatization approach was used to enhance the bromate detection.  

Figure 5: The calibration curve for bromate in the second dimension. The peak area response is plotted against the concentration using a quadratic fit.			

Table 3 listed the precision and recovery data for a variety of real world drinking water samples and a bottle water sample. The samples were spiked with 0.5 μg/L and 5 μg/L bromate. The bromate recovery and method reproducibility was excellent as is shown from these results.  

Table 3:  The precision and accuracy of bromate analysis in various water samples spiked with 0.5 and 5.0 Î¼g/L bromate.			

The effect of the preservative agent ethylenediamine (EDA) was also investigated for the reagent water and high ionic strength matrix. Table 4 showed the comparison data between the sample spiked with EDA and without any EDA. Both samples showed good recovery with minimal impact on retention time. The stock EDA solution was maintained at 4 °C for a month and no noticeable effect was observed for the analysis.  

Table 4:  Effect of EDA on bromate retention time and recovery.			

Overall the MEIC method was fully automated and analysis of a variety of samples with various matrix levels was feasible by the present method. The above method is presently used in US EPA method 302.0 and 314.2.

This article describes a 2D matrix elimination ion chromatography method to analyse samples containing high levels of matrix ions.

LCGC Europe-06-01-2011

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Testing the Critical Interface: Leachables and Extractables