Biologics, and in particular monoclonal antibodies (mAbs), are an important class of therapeutics, and their market share keeps growing. The production of antibodies is a complex and lengthy process. In-process characterization of the mAb would help in optimizing the production steps. Efficiency in mAb characterization can be obtained by automating analysis and reducing hands-on time. Although mass spectrometry (MS) is an essential technique for detailed characterization of biomolecules, its use is limited to purified samples. However, the hyphenation of an MS system to two-dimensional liquid chromatography (2D-LC) allows for the analysis of more complex samples. The first dimension of a 2D-LC system can be used to purify the sample from its matrix or separate compounds using mobile phases that are not MS-compatible, whereas the second dimension coupled to MS can be used to desalt or separate the different variants or species obtained on the first dimension. A 2D-LC–MS system installed in a full good manufacturing practice (GMP)-compliant environment using validated software was used for the characterization of mAbs in complex mixtures at the intact and subunit levels using a Protein A affinity column with no sample preparation steps. In the second application, MS characterization of mAb subunits was made possible by digestion of the mAb online by an immobilized IdeS enzyme. The addition of a disulfide bridge reduction step online led to analyzing smaller molecules to access fine characterization.

Monoclonal antibodies (mAbs) represent a large part of pharmaceuticals currently under development (1). Monoclonal antibodies are 150 kDa molecules consisting of two heavy chains of ~50 kDa and two light chains of ~25 kDa, connected by disulfide bridges. The production of mAbs is a lengthy and complex process, taking place in several steps. However, it is important to follow the mAb critical quality attributes (CQA) along the production steps, and to assess that no modification or degradation has occurred on the protein. The presence of the mAb in a production medium is a hindrance to its rapid and efficient analysis. Techniques such as mass spectrometry (MS), commonly used to determine the molecular weight and the presence of modifications (2), require the use of purified samples, making sample preparation steps mandatory. These steps are timeconsuming, while fast characterization is expected. Online purification and sample preparation would be of great benefit to quickly characterize these products.

Typical modifications followed during the production process are the glycan composition, the presence of the terminal lysine on the heavy chains, the formation of pyroglutamic type of residues, or oxidation. These modifications can be determined by analyzing the molecule at the intact level, yet even more detailed information is obtained by working at the subunit level. Both chemical and enzymatic approaches are used to decrease the complexity of the analysis of the mass spectrometric data. Reduction of intramolecular disulfide bridges with a reducing agent, such as tris(2-carboxyethyl)phosphine hydrochloride (TCEP) or dithiothreitol (DTT), enables the analysis of light and heavy chains separately (25 and 50 kDa, respectively). This is commonly done offline in microtubes, but online reduction has already been reported by Camperi and associates (3).

Another way to obtain subunits is to enzymatically digest the mAb with, for instance, the IdeS enzyme (4), which cleaves above the hinge region. This leads to the formation of a subunit of ~100 kDa (Fab region) and two Fc/2 subunits of ~25 kDa. By using a reducing agent on this digested sample, three subunits can be obtained with average molecular weights of ~25 kDa: Fc/2, LC, and Fd.

Recent developments in chromatographic columns have made the purification and digestion of samples directly on a chromatographic system possible. For instance, pepsin columns have been largely used for many years for automated hydrogen deuterium exchange mass spectroscopy (HDX-MS) studies (5). There are also reports of trypsin columns used for online digestion of proteins (6). Such columns can be fitted on a twodimensional (2D) system, allowing for online sample preparation on the first dimension, followed by desalting or separation of the species on the second dimension (3). In other words, the flow at the output of the column used for purification or digestion purposes is coupled to a second column used for desalting or separation prior to MS analysis. A 2D liquid chromatography system (2DLC) coupled to a mass spectrometer enables the analysis of mAbs after online purification, using the second dimension of the system to desalt the sample or for further separation. This has been described previously with homemade systems adapted to the analysis (7).

Here, two applications are presented describing the use of a 2D-LC–MS system for MS characterization of mAbs without sample preparation in a fully good manufacturing practice (GMP)-compliant environment. The use of a high performance liquid chromatography (HPLC) column based on affinity allows for the purification of the mAb from its medium prior to MS analysis. Here, a Protein A affinity column was used in a two-dimensional LC system coupled to a mass spectrometer allowing for a fully automated analysis of the mAb without hands-on sample preparation. Furthermore, columns with immobilized enzymes are also a way to fasten analysis. For instance, a column with immobilized IdeS enzyme has been developed. The use of such a column on a 2D system with the addition of an online reduction step allows for the characterization of mAbs at the subunit level, with three species of ca. 25 kDa. In this range of molecular mass, excellent chromatographic resolution and mass accuracy can be obtained, allowing for detailed characterization of the mAb and of its quality attributes. These analyses, as well as data processing, are fully automated and can be performed using a fully GMP-compliant software and a qualified 2D-LC–MS system.

Adalimumab (Humira) and nivolumab (Opdivo) were used as model mAbs to perform these tests. All reagents and solvents were obtained from Sigma, Merck, or Biosolve. The 2D-LC–MS system used in this study consists of three pump systems (one quaternary pump [QSM] and two binary pump [BSM]), an autosampler, two Waters CM-A column managers (one used to connect the columns of each of the two dimensions and one used to fit seven trap columns with two valves: nine positions, eight ports), a photodiode array (PDA) detector, and a Xevo G2-XS QTof (Waters). The system was used in heart-cutting mode. Data were acquired and processed with the fully GMP-compliant UNIFI software (Waters). During development, samples were injected on the first dimension, and detected by UV to verify proper elution, equivalent to a first-dimensional (1D) system. In a 2D setup, samples are injected on the first-dimension column (

D), and by switching position on the valve of the column manager, the fractions of interest are sent to the trap columns. At the end of the 1 D gradient, the trap column can be flushed for desalting or used for online reduction for instance. Finally, the compounds are eluted from each trap column onto the second-dimension column (

D) by sending the flow through the output of the trap column towards the second-dimension column (

D). Detection was performed on the coupled ESI-QTOF-MS (Xevo G2-XS QTof) system. With this setup, up to seven trap columns can be connected, allowing a maximum of seven heart-cuts per sample injection.

Two-Dimensional Liquid Chromatography Coupled to Mass Spectrometry

Application 1: Characterization of mAbs Present in Complex Mixtures

Samples were injected “as is” (0.5 µg for analysis at the intact level, or 0.2 µg if reduction was performed) on the 2D-LC–MS system. On the first dimension, eluent A was phosphate buffer saline (PBS) at pH 7.4, and eluent B was PBS complemented with 12 mM hydrochloric acid (HCl) at pH 2.4. Elution on the MAbPac Protein A column (35 × 4 mm, 12-µm, Thermo Scientific) was in a step gradient with 1 min at 100% A, followed by 2.5 min at 100% B at 0.3 mL/min. Trapping was done with a BioResolve column (RP mAb polyphenyl, 30 × 2.1 mm, 2.7-µm, Waters). Online reduction of disulfide bonds was performed with a solution of 10 mM DTT in 50 mM ammonium bicarbonate set on line B with a flow of 0.5 mL/ min for 5 min, followed by a washing step of 10 min with 0.1% formic acid (FA) in H

O at 0.5 mL/min (line A). When on-trap reduction was not needed, desalting was performed for 10 min with 0.1% FA in H

O at 0.15 mL/min. For these steps, with or without reduction, the trap column was heated at 80 °C. On the second dimension, elution was performed on a BioResolve column (RP mAb polyphenyl, 50 × 2.1 mm, 2.7-µm, Waters) with 0.1% FA in H

O as eluent A, and 0.1% FA in acetonitrile as eluent B at 80 °C. Gradient for elution of intact mAbs was as follows: 2 min isocratic at 5% B; from 2 to 3 min, linear gradient to 20% B, followed by a linear gradient to 13 min to 90% B at 0.3 mL/min before washing the column and equilibration in the starting conditions. The gradient for elution of mAbs after reduction was as follows: 2 min isocratic at 5% B at 0.3 mL/min; from 2 to 3 min, linear gradient to 20% B at 0.2 mL/min followed by a linear gradient to 13 min to 40% B and linear gradient to 14 min to 90% B at 0.2 mL/min, before washing the columns and equilibration in the starting conditions. Total run time for such analysis was 45 min at the intact level, and 55 min at the reduced level.

Mass spectra were acquired on an online Xevo G2-XS (Waters) coupled to the 2D-LC–MS system, equipped with a z-spray electrospray ionization source, a quadrupole, and an orthogonal time of flight. For the analysis of mAbs at the intact level, capillary voltage was set at 2.75 kV, cone voltage at 150 V, source temperature at 100 °C, desolvation temperature at 600 °C, cone gas flow at 0, and desolvation gas flow at 800 L/h. For the analysis of mAbs subunits, capillary voltage was set at 2.5 kV, cone voltage at 120 V, source temperature at 100 °C, desolvation temperature at 500 °C, cone gas flow at 100, and desolvation gas flow at 1000 L/h. 

Application 2: Automated Characterization of mAbs at the Subunit Level: 

Samples (1 µg) were injected onto the system. On the first dimension, eluent A was 200 mM ammonium acetate. Isocratic elution was performed on a HPLC Fabricator column (Genovis) at 37 °C for 20 min. On the BSM used for fitting the trap columns, a Bioresolve RP mAb polyphenyl (30 × 2.1 mm, 2.7-µm, Waters) was installed and 0.05% FA + 0.05% trifluoroacetic acid (TFA) in H

O was set on line A. Online reduction of disulfide bonds was performed with a solution of 10 mM DTT in 50 mM ammonium bicarbonate set on line B, with a flow of 0.5 mL/min for 5 min, followed by a washing step of 10 min with 0.05% FA + 0.05% TFA in H

O at 0.5 mL/min. If no reduction was needed, no washing was done before elution on the second dimension. The trap column was heated at 80 °C. On the second dimension, elution was performed on a MabPac RP (50 × 3 mm, 4-µm, Thermo Scientific) column with 0.05% FA + 0.05% TFA in H

O as eluent A, and 0.05% FA + 0.05% TFA in acetonitrile as eluent B. The gradient was as follows: isocratic for 2 min at 5% B at 0.3 min, linear gradient from 2 to 3 min at 0.2 mL/min to 28% B, linear gradient to 23 min to 36% B at 0.2 mL/min. Elution was performed at 80 °C. Mass spectra were acquired on the Xevo G2-XS coupled online to the 2D-LC system with the same parameters as described above for subunits.

To induce oxidation, nivolumab was incubated with H

 for 45 min at RT in the presence of 0, 0.075, or 0.2% H

 . The oxidation reaction was stopped by addition of methionine to the solution. Samples were injected “as is” to the 2D-LC–MS system without further preparation for online IdeS digestion with and without DTT reduction and with the optimal conditions defined above.

Tests were performed to evaluate the feasibility of online reduction of disulfide bridges present on mAbs on the 2D-LC system. The reduction reaction was performed after the heart-cut, when the fraction of interest is on the trap column, prior to elution on a second dimension. Initial disulfide bridge reduction tests were performed with TCEP because it is known to be a good reducing agent, independently of the pH of the solution. Tests were performed by injecting the mAb directly on the trap column without using a column on the first dimension for development method purposes. The initial runs consisted of a flow of 0.5 mL/min of 1 mM TCEP in 10:90 (v/v) acetonitrile–water sent through the trap column for 5 min while the compound was trapped. At this stage, three trap column temperatures (room temperature, 50 °C, and 80 °C) were tested. Both the light and heavy chains were present, indicating that the reduction was successful. However, for each of the subunits, multiple peaks were observed. Based on the analysis of the mass spectra, it was found that intramolecular disulfide bridges were not completely reduced. This was not improved by increasing the flushing time of TCEP to 20 min or the concentration of TCEP to 20 mM. This phenomenon has been previously described in the literature (3).

As a result, further tests were performed with DTT. One disadvantage of this reducing agent is that its optimum activity is at pH 8 and its stability is limited (8). This means that a buffer needs to be used to control the pH. DTT was prepared in 50 mM ammonium bicarbonate and, as described above, a flow of 10 mM DTT in ammonium bicarbonate was sent to the trap column for 5 min. In these conditions, only one peak for each light and heavy chain was observed (Figure 1). Complete reduction was confirmed by deconvoluting the MS spectra obtained, in which only the species with all disulfide bridges reduced were found. Furthermore, after keeping the DTT solution on the system overnight at room temperature, comparable efficiency in the reduction of the mAb was obtained. This indicates that such solutions can be used for a long sequence in which multiple samples are analyzed. This successful online reduction was further used as a step in a full 2D-LC–MS analysis.

Characterization of mAbs in Complex Mixtures

In the development phase, elution on the Protein A column was tested in a 1D setup using UV detection to ensure proper elution of the mAb from the Protein A column. Good reproducibility (0.2% RSD on UV signal for triplicate injection) was observed, as well as linearity of the UV signal as a function of the injected amount. After this successful step, the complete 2D setup was used by injecting adalimumab. As proper elution and MS signal were obtained for the mAb, the influence of the starting medium was tested. The elution of adalimumab diluted in water and adalimumab diluted in a complex cell culture medium were compared. There was no influence of the starting solution on the elution on the second dimension and on the MS data. The same retention time, peak shape, and deconvoluted masses were observed.

It was found during the different tests performed that the desalting step (flushing of the trap column while the mAb was trapped) had an impact on peak tailing in the second dimension. Extensive desalting with high flow rate or duration led to a large tailing of the mAb peak. To avoid such peak tailing, the desalting step was initially removed. By looking closely at the spectra, it became clear that desalting was necessary to obtain a mass spectrum of acceptable quality that could be correctly deconvoluted. Several adjustments were needed to have both limited tailing and good MS data quality. The influence of the duration and flow rate of the desalting step was evaluated. Eventually, a desalting step of 10 min at a moderate flow rate of 0.15 mL/min was found to be a good compromise in addition to optimized MS parameters (Figure 2).

After this, the online reduction step with DTT, as described above, was tested in a full 2D-LC setup. As observed for the test without a column on the first dimension, the light and heavy chains were well separated, and all disulfide bridges (inter- and intramolecular) were fully reduced (Figure 3). For this type of analysis, even less material is needed than for intact analysis. It was indeed observed that injected amounts higher than 0.4 µg led to saturation of the MS signal.

In conclusion, a fast method was developed for the analysis of mAbs at the intact or subunit levels present in complex mixtures. Peak identification was performed automatically with UNIFI software. Within less than 1 h, without prior sample preparation, using a fully automated and GMP-compliant system, MS data were obtained, thereby allowing for a full characterization of the antibody.

Automated MS Characterization of mAbs at Subunit Level

The analysis of mAbs at the subunit level was performed using an immobilized IdeS column. Elution on this column is isocratic and digestion occurs using a low flow, so there is enough time for proper digestion. Initial tests only consisted in checking that the mAb would elute properly from the column using the 1D setup with UV detection. For these first steps, a mobile phase consisting of PBS was used and adalimumab was chosen as model mAb. By working with the complete 2D-LC–MS system, it was confirmed that the IdeS digestion was complete as the expected F(ab’)2 and Fc/2 species were observed. Extrapolation was performed by working with another mAb, namely nivolumab, and by including the online DTT reduction step as described above. No intact nivolumab was observed after IdeS digestion only, but the presence of heavy chain was detected after enzymatic digestion followed by reduction. The presence of the heavy chain shows that the enzymatic digestion was incomplete, as the IdeS enzyme is cleaving above the hinge region (Figure 4).

To try and solve this issue, several tests were performed such as lowering the flow rate on the Fabricator column or by injecting lower amounts of nivolumab. Still, the presence of heavy chain was detected. It has been described that one way to improve the digestion is to increase the ionic strength (9), but the digestion was still incomplete using PBS 2×. At this stage, it was decided to test a different eluent. By using ammonium acetate, digestion was complete, but concentration had to be increased to 200 mM (from 150 mM tested initially) to obtain a sharp peak in the first dimension, which would allow for a clean heart-cut.

Case Study: Quantifying Oxidation on Nivolumab

Oxidation was induced at three levels to evaluate the potential of such an automated method for detection and quantification of these type of modifications. Oxidation mainly occurs on the Fc part of the antibody. The oxidized forms elute earlier than the non-modified Fc/2 fragments (Figure 5). It is even possible on this example to distinguish between mono-oxidized and di-oxidized species. The different compounds were identified automatically with UNIFI software. Based on these identifications, the oxidation ratio was calculated. In this example, with rather high H

 concentrations, oxidation up to 74% was calculated on the Fc/2 species after IdeS digestion and online reduction (Figure 6). For the samples that were only digested with IdeS, the same trend of oxidation level as a function of H

 concentration was observed. Calculated levels were, however, slightly higher, with an oxidation of 86% calculated for the highest level of H

With this example, it was demonstrated that without prior sample preparation, modifications present on mAbs can be easily determined. The level of modification was quantified by mass spectrometry at the subunit level using a 2D-LC–MS workflow.

Two approaches were developed to characterize mAbs with mass spectrometry using innovative two-dimensional liquid chromatography workflows. For both approaches, detailed information on monoclonal antibodies can be obtained at the intact or subunit levels without any sample preparation, using a fully automated and GMP-compliant 2D-LC–MS system.

With these techniques, optimization of the mAb production process is made easier and faster by analyzing samples without manual purification. The second approach shows the potential for automated quality control (QC) multiple quality attributes monitoring of mAbs without any sample preparation.

These methodologies open the way to fully compliant at-line monitoring of monoclonal antibody quality attributes.

(1) Castelli, M. S.; McGonigle, P.; Hornby, P. J. The Pharmacology and Therapeutic Applications of Monoclonal Antibodies. Pharmacol. Res. Perspect. 2019, 7 (6), e00535. DOI: 

(2) Zhang, Z.; Pan, H.; Chen, X. Mass Spectrometry for Structural Characterization of Therapeutic Antibodies. Mass Spectrom. Rev. 2009, 28, 147–176. DOI: 

(3) Camperi, J.; Dai, L.; Guillarme, D.; Stella, C. Development of a 3D-LC/MS Workflow for Fast, Automated, and Effective Characterization of Glycosylation Patterns of Biotherapeutic Products. Anal. Chem. 2020, 92, 4357–4363. DOI: 

(4) von Pawel-Rammingen, U.; Johansson, B. P.; Björck, L. IdeS, A Novel Streptococcal Cysteine Proteinase with Unique Specificity for Immunoglobulin G. EMBO J. 2002, 21, 1607–1615. DOI: 

(5) Narang, D.; Lento, C.; Wilson, D. J. HDX-MS: An Analytical Tool to Capture Protein Motion in Action. Biomedicines 2020, 8, 224. DOI: 

(6) Šlechtová, T.; Gilar, M.; Kalíková, K.; et al. Performance Comparison of Three Trypsin Columns Used in Liquid Chromatography. J. Chromatogr. A 2017, 1490, 126–132. DOI: 

(7) Camperi, J.; Dai, L.; Guillarme, D.; Stella, C. Fast and Automated Characterization of Monoclonal Antibody Minor Variants from Cell Cultures by Combined Protein-A and Multidimensional LC/MS Methodologies. Anal. Chem. 2020, 92, 8506–8513. DOI: 

(8) Getz, E. B.; Xiao, M.; Chakrabarty, T.; Cooke, R.; Selvin, P. R. A Comparison between the Sulfhydryl Reductants Tris(2-carboxyethyl) phosphine and Dithiothreitol for Use in Protein Biochemistry. Anal. Biochem. 1999, 273, 73–80. DOI: 

(9) Nägeli, A.; Björk, S.; Nordgren, M.; Nyhlén, H. Automated Middle-level Antibody Analysis Using On-Column FabRICATOR Digestion with LC-MS. Genovis AB Application Note. 

https://www.genovis.com/wp-content/uploads/genovis-application-note-fabricatorhplc-06.pdf

are with Quality Assistance in Donstiennes, Belgium.

Articles

Featured Article

The methodologies demonstrated here open the way to fully compliant at-line monitoring of monoclonal antibody quality attributes.

2D-LC–MS Approaches for the Analysis of In-Process Samples and for the Characterization of mAbs in a Regulated Environment 

As chromatography technologies change, our approaches to using them in ways that value reliability, as well as the ways we should approach troubleshooting and fixing problems, should also change. In this instalment, we survey several protective and troubleshooting strategies, and discuss which approaches have changed over time, and which ones have not. Understanding how the use of these approaches has evolved is helpful both for designing reliability into new methods and when considering updates to legacy methods that have been in use for decades.

In recent months, I’ve been hearing from several readers of this column that they’ve appreciated the more educational, “back-to-basics” flavour of some of the “LC Troubleshooting” instalments this past year. So, this month I’ve decided to dip a little further into that theme and provide some perspective on the evolution of various troubleshooting topics over the last few decades. My view is that this kind of perspective is particularly valuable to those who are relatively new to the field. There are some aspects of “the way we do things” that may seem peculiar on the surface, but, in fact, are very important to the reliability of high-performing liquid chromatography (LC) methods. On the other hand, some aspects of certain methods and ways of doing things are simply unnecessary in 2023 because LC technology has evolved in such ways that the old tricks aren’t needed anymore. Sometimes, implementing the old tricks with new technology—though they provide no benefit—doesn’t do any harm, but they do add cost to analyses because they take time and resources to implement. Thus, we really ought to let them go if they are not adding any value to the method. In other words, let’s be smart about the methods we deploy. If we can’t come up with a better explanation for why something about the method is the way it is, then it’s time to let it go.

Topic #1: Inline Filters, Guard Columns, Saturator Columns, and Cleanup Columns

Frequent readers of “LC Troubleshooting” know that this topic of inline filters, guard columns, and other protective devices is one of my favourites to write about. This is because I think this is an area where tremendous gains in LC system reliability and performance can be realized by following a few simple and low-cost guidelines. Figure 1 shows a flow diagram of a simple LC system, with an emphasis on the proper locations of different protective devices. Location is important—using the correct device in the wrong location will substantially, or totally, reduce the effectiveness of the device. In the following paragraphs, I will briefly review the primary function of each device and discuss how this has changed with the evolution of LC technology. Note that the discussion assumes that we are talking about reversed-phase LC separations. Similar arguments can be made for other modes of LC, but the details will be a bit different. Readers interested in learning more details about each device can refer to past articles focused more specifically on these topics.

Inline filters are typically located between the sample injection point and the analytical LC column. They can also be used effectively in other locations, when called for by special circumstances. The primary role of the inline filter is to trap particulate matter that would otherwise flow to the LC column and either contaminate the stationary phase, occlude the column inlet frit, or both. Typically, the through‑pore sizes of these filters are in the range of 0.2 to 2.0 μm, which means that, in principle, they will trap any particles larger than this. The major source of particulate matter in the mobile phase at this point, which can be trapped by the inline filter, is the sample injection device. Most modern injection valves turn a polymeric rotor seal against a metallic stator. In this situation, the metal wins, and small pieces of the polymeric rotor seal are shed and released into the mobile phase over time. If these are not trapped out of the mobile phase, they will accumulate at the column inlet, causing a decrease in performance (for example, tailing peaks, loss of efficiency), and, in the worst case, occlusion of the column inlet to the point where the pressure drop across the column is so high that it cannot be used any longer. At this point, the column must be replaced. Given that this is usually about a $1000 fix, one can buy and replace many inline filters and still save money (and time, as a result of better method reliability), even if it only saves the life of a single column. Readers interested in learning more about inline filters can refer to previous instalments (1). Inline filters have been recommended for several decades, and I think this is still great advice.

Guard columns are located between the sample injector and the analytical LC column. When an inline filter is also installed, the guard column is usually installed between the inline filter and the analytical column. Also, when an inline filter is used (please do), the primary function of a guard column, which typically contains a small amount (usual lengths are 5 to 10 mm) of the same material in the analytical column, is to trap any material from the injected sample that would otherwise cause damage to the analytical column. In most cases, such damage (which may be reversible, but likely inconvenient) occurs as a result of strong adsorption of some molecules from the sample by the stationary phase that are not eluted from the column during normal operation. For example, these could be lipids or proteins from a biological sample, which, if accumulated over time from many sample injections, could change the stationary phase chemistry enough to cause significant changes in the resolution of target analytes of interest. The financial analysis here is not as simple as it is with inline filters. The cost of a guard column is typically 10–20% of the price of an analytical column, so one has to think about how many analytical columns will be saved (or how much inconvenience can be avoided) through routine use of a guard column. In my own laboratory, we don’t use guard columns very often, but that is because much of our work is with relatively clean (chemically and physically) samples. In cases where we are analyzing complex biological samples, we routinely use guard columns. This technology is several decades old, but still a great investment in situations that call for it (1).

C/D) Cleanup Trap (C: Aqueous Solvent Line; D: Mixed Solvent):

Whereas guard columns discussed in the previous section are placed after the sample injector to protect the analytical column, the same type of column can also be located between the pump and sample injector for the purpose of “cleaning up” the mobile phase (we’ll call it a trap here to differentiate the use from B, above). When a trap containing a lipophilic sorbent (for example, C18‑silica) is installed in the flow path of a mostly aqueous solvent line, prior to the point at which the mobile components are mixed, this configuration can be very effective for removing lipophilic contaminants in the aqueous solvent that would otherwise interfere with the analysis. Figure 2 shows a dramatic example of the removal of contaminants that would otherwise interfere with ultraviolet (UV) detection at 214 nm. When used in this way, the trap must be removed periodically and washed with strong solvent. It is important to note here that this approach can only be implemented with pumps based on a high pressure mixing design (see [2] for details on pump design).

Alternatively, such a trap column can also be implemented at position D in Figure 1. In this case, the mobile phase is passed through the trap after the components, which are drawn from two or more solvent bottles, have been mixed. In this implementation, the trapping efficiency is typically not as great as it is when the trap is used on the line of a single solvent; however, one advantage of placing the trap at location D is that we have the opportunity to catch contaminants from any of the solvent sources. This approach is frequently used in the analysis of polyfluoroalkyl substances (PFAS), where leaching of PFAS from instrument components into the mobile phase is a major challenge, especially in applications focused on trace analysis. Readers interested in this approach are referred to the August 2018 edition of “LC Troubleshooting”, where I described this approach in more detail (3).

The implementation of trapping columns upstream from the sample injection point is a newer development relative to the long history of the use of guard columns. This is, in part, due to the continuing quest for lower and lower detection limits. In these applications, even minor mobile phase contaminants become major interferences that stand in the way of improved detection limits, and removing them from the mobile phase stream in real time can be highly beneficial.

The last protective device for discussion here is a so‑called “saturator”, or “sacrificial” column, installed at location E in Figure 1. The primary function of this column, which would typically be packed with silica particles, is to saturate the mobile phase with dissolved silica. When implemented with high pH mobile phases (for example, mobile phases above pH 7), which dissolve the silica, the idea is that because the mobile phase is already saturated with dissolved silica when it reaches the analytical column, the rate of dissolution of silica particles in the second column is largely suppressed (4,5). Thus, this is where the name “sacrificial” column comes from—the silica in the saturator column is sacrificed to prevent the death of the analytical column. This is one technology that has been driven almost entirely to extinction in the practice of modern LC, largely due to the development of silica-based phases that can be used at high pH (>10) without fear for rapid dissolution of the silica. When faced with a legacy method that calls for the use of a saturator column, one should ask if this is really the best option, or if the method can be updated by leveraging contemporary column technologies.

Newcomers to LC may have never heard of the concept of “repairing” a column. For old-timers, repairing columns was simply part of the know how needed to keep a laboratory running. So, what is this about? In the early days of high performance liquid chromatography (HPLC), particle sizes on the order of 10 to 40 μm were common, and a column could be prepared by literally pouring the packing material into an empty column and settling the bed by tapping on the tube until no additional particles could be added. As the columns were not prepared under pressure, with regular use, the particle bed could settle and voids (that is, empty spaces containing only mobile phase, and no particles) could form, typically at the column inlet, which would in turn lead to peak tailing and loss of efficiency. To repair the column, one could take off the inlet endfitting, remove the inlet frit, and add some packing material to fill the void. Reassemble the inlet fitting, and voilà! Column performance was restored. Fortunately, or unfortunately, the days of this type of column repair are mostly behind us. Modern columns are prepared by packing the particles into the columns at very high pressures, and the preparation procedures are optimized to avoid settling of the bed and development of voids. Column manufacturers strongly advise against disassembling a column to try to repair it, and that is good advice. To me, vintage columns are a bit like vintage cars. One can fix most problems with a vintage car with pliers, a screwdriver, and a handful of wrenches. However, the vintage car will break down frequently, and certainly cannot be driven at 100 miles per hour. A newer car, like my 2013 hybrid, is difficult to fix without appropriate training from the manufacturer, so that could be viewed as a disadvantage. However, the hybrid car doesn’t break down very often, and is much higher‑performing than my grandfather’s Model T. Personally, I’m glad the days of column repair are behind us. We’re now used to 50 mm columns that will give us 15,000 plates out of the box, and our methods are better for it!

In this instalment of “LC Troubleshooting”, I’ve discussed some troubleshooting and protective strategies that have long histories in the LC community. Some of them, such as the use of inline filters, have not changed much over decades. Others, such as the use of saturator columns, have changed dramatically because of the introduction of new column technologies, to the point where the use of saturator columns is not recommended in the practice of modern HPLC. Understanding the history of these practices, and how they have evolved over time, is a useful facet of knowledge for aspiring LC troubleshooters.

(1) Stoll, D. R. Filters and Filtration in Liquid Chromatography—What to Do. 

(2) Stoll, D. R. Mixing and Mixers in Liquid Chromatography – Why, When, and How Much? Part I, The Pump. 

(3) Stoll, D. R. Contaminants Everywhere! Tips and Tricks for Reducing Background Signals When Using LC–MS. 

(4) Atwood, J. G.; Schmidt, G. J.; Slavin, W. Improvements in Liquid Chromatography Column Life and Method Flexibility by Saturating the Mobile Phase with Silica. 

(5) Bidlingmeyer, B. A. Liquid Chromatography Problem Solving and Troubleshooting. 

Events

LC Troubleshooting

As chromatography technology evolves, our use of it should change also. This article outlines a number of protective and troubleshooting methods for LC and how these approaches have changed over time.

Evolution of LC Troubleshooting: Protective Devices and Column Repair

Good Laboratory Practice (GLP) is a regulatory requirement to help ensure the quality, reliability, and integrity of pharmacological and toxicological studies during drug development. This article overviews GLP regulations and related public standards, focusing on practices relevant to analytical and bioanalytical chemists.

Nonclinical and clinical studies are the two pillars of new drug development (1,2). Many of these studies are regulated by health authorities, as described in our previous overview article on pharmaceutical regulations (3). Here, we discuss Good Laboratory Practice (GLP) regulation described in Title 21 Code Federal Regulations (CFR) Part 58 (4), enacted in 1978 to ensure data accuracy and integrity of nonclinical laboratory studies (5–8). Two types of mandatory nonclinical studies conducted in the preclinical stage on new molecular entities (NMEs) are pharmacology/drug disposition and toxicology (safety) evaluations. Pharmacology/drug disposition studies investigate the pharmacological effects and the mechanisms of action of the drug in animals, providing information on the absorption, distribution, metabolism, and excretion (ADME) of the investigational product (9,10). Toxicology studies monitor the toxicological effects of the drug 

While GLP regulations are requirements for conducting pivotal nonclinical safety studies before first-in-human clinical trials, the principles and practices of GLP are often adopted and combined with Good Clinical Practice (GCP) (12,13) for clinical bioanalytical testing (such as those tests for blood, plasma, urine, or tissues collected from test subjects during clinical trials). These public standards are known as 

This paper highlights the principles and practices of GLP relevant to both analytical and bioanalytical chemists supporting nonclinical studies.

Table 1 lists the terms and acronyms used in the paper.

GLP in Drug Development and Registration of Other Products

GLP is a quality system covering the required organizational processes and the conditions under which pivotal nonclinical studies are planned, performed, monitored, recorded, reported, and retained (4,5). GLP studies are required to register new chemicals, food, colour additives, human and animal drugs, medical devices, biological products, biocides, or agrochemicals (4,5). This paper focuses on drugs for human use. However, agencies such as the United States Environmental Protection Agency (EPA) also issue GLP regulations for products under their purview (16), as promulgated in 40 CFR 160 (FIFRA) and 40 CFR 792 (TSCA).

Regional authorities such as the FDA, EMA, and OECD establish GLP regulations for human-use drugs. In the USA, the FDA has published the GLP in the Code of Federal Regulations (CFR) – Title 21 CFR Part 58 (4). Currently, OECD has 38 member countries that have adopted the OECD GLP principles and guidance documents (8). There are EU directives relating to adopting GLP principles, some of which reference OECD-published guidelines (17,18). While there are many similarities between regional GLP regulations, not all aspects are the same, especially for terminologies (19). As described in a previous paper (3), it is incumbent on the sponsor to fully understand the regulations within the jurisdiction they wish to conduct studies.

We will briefly discuss pharmacokinetic (PK) and toxicokinetic (TK) studies, which are nonclinical studies that aim to demonstrate that the drug candidate is safe for initial human testing and exhibits the desired pharmacological activities. Before the drug can be tested in humans, GLP preclinical PK studies should be performed in rodent and non-rodent species. PK studies determine the concentration of the drug candidate within various parts (organs) of the animal at defined time points after drug administration. PK studies aim to obtain bioavailability data (how the drug is absorbed into the systemic circulation) and to allow extrapolation to human equivalent doses (9–11). TK studies also determine the concentration of the drug within different parts of the animal at defined time points after administration of the drug. They are designed to aid the interpretation of toxicity findings. TK studies use exaggerated concentrations of the drug candidate to study how toxic the drug may be (maximum tolerable dose). Preclinical toxicology studies often comprise acute (single dose), subacute (repeat dose), genotoxicity, and safety pharmacology studies. A 28-day repeat dose toxicology study in rodents and non-rodents is typically needed before investigational new drug (IND) application for human clinical trials (11,20).

In addition to preclinical PK and TK studies for safety evaluation that should be conducted under GLP, other studies may include general toxicity studies (acute, sub-chronic, and chronic), local tolerance studies, genotoxicity studies, carcinogenicity studies, developmental and reproductive toxicity studies, immunotoxicity studies, analytical studies of biological sample collected from animals, and analytical studies of the dose formulations (21).

Table 2 lists 10 principles of GLP according to OECD, with brief descriptions of each (4,8). The reader is referred to the official guidance documents and the company’s internal standard operating procedures (SOPs), if available.

While GLP and current Good Manufacturing Practice (cGMP) regulations have similar goals to ensure data accuracy and integrity and are enforced by the FDA in the USA, there are significant differences (3–5). GLP applies to the preclinical or nonclinical safety testing phase of drug development and focuses on short-term projects and standalone studies often conducted in contract research organizations (CROs) (22). The principles of GLP are adopted and followed in bioanalytical testing in clinical studies. cGMP regulations apply to the late-stage drug manufacturing process of drug substances and products, including clinical trial materials and commercial manufacturing (23). cGMP will be further described in our next instalment.

Analytical and Bioanalytical Chemists Supporting GLP Studies

Table 3 lists a nonclinical study’s GLP elements divided into five broad categories: Resources, Practices, Analytical and Bioanalytical Testing, Protocol and Study, and Reporting of Study Events. We will provide examples of practice and testing elements relevant to chemists in this section.

Good documentation practice (GDocP) is a core element of GLP compliance (24). Pharmaceutical companies establish their own GDocP aligned with industry standards. For example, the acronym “ALCOA+” is often used to describe components of GDocP: 

Attributable, Legible, Contemporaneous, Original, and Accurate

. For the chemist, this means using an electronic lab notebook or ELN to contemporaneously record reagents, solvents, samples, balances, weights, pipettes, and equipment used to prepare and analyze the test and control articles. The analyst must document the technical procedures and data analysis techniques, including the chromatography data system (CDS) processing method and integration parameters. All raw data and corresponding GLP documentation must be retained and archived as per SOPs.

Chain of custody is essential to maintaining the integrity of the GLP study, so there must be documentation of the delivery, receipt, storage, preparation, analysis, and disposition of test and control articles. The study director or test facility manager typically enforces these regulatory aspects. The quality assurance unit (QAU) may conduct an in-study inspection of the analytical chemist preparing test and control article samples to assure correct procedures are followed.

We highlight two specific roles for the analytical chemist working in the lab—the analytical chemist responsible for characterizing the GLP test article and monitoring its stability (21 CFR Part 58.105[a] and [b]); and the bioanalytical chemist responsible for the analysis of blood, plasma, serum, other bodily fluids, or tissues after administration of the test article to the test systems (21 CFR Part 58.120 [4,22], Part 58.130[a] and [c]). Both roles are essential in supporting GLP studies.

Analytical chemists support GLP studies by developing methods to characterize test articles (drug substances and early-phase drug product formulations) to determine identity, strength, purity, composition, or other characteristics that appropriately define it (2,4). Test articles in GLP studies should be characterized and documented using GLP-compliant methods and procedures (21). The chemist uses phase-appropriate method validation for GLP studies (3,21), as there is often little data available on degradation products and pathways at this early stage of development. In addition, a toxicology study is often conducted using simple formulations or carriers before a final drug product formulation is fully established. High performance liquid chromatography (HPLC) with ultraviolet (UV) detection is commonly used for testing small molecule test articles. The equipment must have proper qualification documentation for a GLP study (7).

Stability of the test and control articles (such as drug substance and dosing solution when applicable) must be established to assign appropriate storage conditions and assure that the concentration of the test article does not change outside of established ranges from the date of manufacture through the end of the study.

Bioanalytical methods employed in GLP studies are validated in accordance with International Council for Harmonisation (ICH) M10 (25). The guidance applies to bioanalytical methods used to measure concentrations of chemical and biological drug(s) and their metabolite(s) obtained in nonclinical TK studies, nonclinical PK studies conducted as surrogates for clinical studies, and all phases of clinical samples.

Bioanalytical chemists may use techniques such as LC–mass spectrometry (MS), enzyme-linked immunosorbent assay (ELISA), electrochemiluminescence, or surface plasmon resonance to measure the concentration of drug and metabolite in a particular biological matrix such as whole blood, serum, or plasma (26,27).

Core bioanalytical assay validation typically consists of evaluations of the method’s precision, accuracy, selectivity, and specificity. Additional validation experiments are performed to characterize the assay and evaluate the stability of the analyte in the appropriate biological matrix. For example, selectivity must be evaluated in relevant patient populations, presenting a challenge for projects with rare disease indications (26). Stability in the biological matrix is determined over an appropriate concentration range for the assay being validated. Typically, stability is evaluated at room temperature, frozen, and after multiple freeze-and-thaw cycles (25). It is also sometimes necessary to evaluate the assay’s performance in the presence of co-administered medications or elevated levels of the endogenous target (26).

GLP bioanalytical support of large molecule clinical studies also includes immunogenicity testing (28,29). Immunogenicity is the tendency of a drug candidate to elicit an immune response to itself, resulting in the possibility of altered PK or potential adverse clinical events. Immunogenicity testing typically consists of screening, confirmatory, titration, and neutralization assays to identify and characterize the immune response fully (30).

Analytical chemists are essential in determining the concentration, homogeneity, and stability of test articles and reference articles for nonclinical studies. Bioanalytical chemists are essential in analyzing specimens from nonclinical test systems and clinical test subjects. Compliance with GLP ensures the reliability and integrity of these studies and the accuracy of the data submitted to regulatory authorities.

This paper provides a high-level overview of GLP regulations and related standards for pharmaceutical scientists in nonclinical and clinical studies. While the goal of the regulation is straightforward, compliance activities are diversified and variable, driven by the company’s SOPs, resources, and compliance culture. The information presented here stems from health regulations, guidance documents, and the authors’ experience. Presenting a concise overview of this complex topic is challenging. The reader is referred to cited references and the company’s internal SOPs for more definitive compliance activities in the laboratory.

The authors thank the reviewers for providing timely technical and editorial inputs to this article: Kirk Smith of Smith & Co. Consulting, Alice Krumenaker of Hovione, Mike Shifflet from Kenvue, Doug McDowell of Eurofins Biopharm Products Testing, Kate Evans of Longboard Scientific Consulting, Bob McDowall of McDowall Consulting, David VanMeter of Sartorius, Michael Swartz of Karuna Therapeutics, Chris Tudan of Veloxity Labs, Aimin Tan of Nucro-Technics, and He Meng of Sanofi.

Drug Discovery and Development: Technology in Transition

(2) Dong, M. W. Drug Development Process: Nonclinical Development of Small Molecule Drugs. 

(3) Doneski, L.; Dong, M. W. Pharmaceutical Regulations: An Overview for the Analytical Chemist. 

Title 21, 58, Good Laboratory Practice for Nonclinical Laboratory Studies (Government Printing Office, Washington, DC, USA) 

https://www.ecfr.gov/current/title-21/chapter-I/subchapter-A/part-58

Nonclinical Safety Studies for the Conduct of Human Clinical Trials and Market Authorization for Pharmaceuticals 

Good Clinical Practice: Pharmaceutical, Biologics, and Medical Device Regulations and Guidance Documents Concise Reference

Good Laboratory Practice for Nonclinical Studies (Drugs and the Pharmaceutical Sciences)

(8) OECD Principles of Good Laboratory Practice, Environment Directorate Organization for Economic Cooperation and Development, 1998. DOI: 

Lippincott Illustrated Reviews: Pharmacology, 

Winter’s Basic Clinical Pharmacokinetics

, 6th ed; Lippincott Williams & Wilkens, 2017.

Casarett & Doull’s Essentials of Toxicology

(12) Kolman, J.; Meng, P.; Scott, G. (Ed.) 

Good Clinical Practice: Standard Operating Procedures for Clinical Researchers

https://database.ich.org/sites/default/files/ICH_E6-R3_GCP-Principles_Draft_2021_0419.pdf

(14) Ezzelle, J.; Rodriguez-Chavez, I. R.; Darden, J. M.; et al. Guidelines on Good Clinical Laboratory Practice (GCLP): Bridging Operations Between Research and Clinical Research Laboratories. 

(15) Good Clinical Laboratory Practice, World Health Organization. 

https://assets.publishing.service.gov.uk/media/57a08b54e5274a31e0000ac6/gclp-web.pdf

Title 40, 160, Good Laboratory Practice Standards (Government Printing Office, Washington, DC) 

https://www.ecfr.gov/current/title-40/chapter-I/subchapter-E/part-160

(17) Directive 2004/9/EC of the European Parliament and the Council of 11 February 2004 on the Inspection and Verification of Good Laboratory Practice (GLP) (February 2004).

(18) Directive 2004/10/EC of the European Parliament and of the Council of 11 February 2004 on the Harmonization of Laws, Regulations, and Administrative Provisions Relating to the Application of the Principles of Good Laboratory Practice and the Verification of Their Applications for Tests on Chemical Substances (February 2004).

(19) Huntsinger, D. W. OECD and USA GLP Applications. 

Good Laboratory Practice (GLP) 101–Regulations and Basic Studies 

(21) Tahl, K.; Brown, J. G. Principles of Good Laboratory Practice and Nonclinical Development in Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective. 

(22) Andola, H.; Purohit, V. K., Good Laboratory Practice Requirements: An Overview. 

Title 21, 210 and 211, Current Good Manufacturing Practice for Finished Pharmaceuticals (Government Printing Office, Washington, DC, USA) 

https://www.ecfr.gov/current/title-21/chapter-I/subchapter-C/part-211

(24) WHO, TRS 966 - Annex 5: WHO Good Data and Record Management Practices. Annex 5, WHO Technical Report Series 966 (World Health Organization, 2016).

Bioanalytical Method Validation and Study Sample Analysis 

(26) Stevenson, L.; Kelley, M.; Gorovits, B.; et al.. Large Molecule Specific Assay Operation: Recommendation for Best Practices and Harmonization from the Global Bioanalysis Consortium Harmonization Team. 

(27) Vandivort, T. Pharmacokinetic and Toxicokinetic Studies in Fundamentals of Pharmaceutical and Biologics Regulations: A Global Perspective. 

(28) Williams, K.; Erickson, R.; Fischer, S. K. Overcoming Disease-Specific Matrix Effect in a Clinical Pharmacokinetic Assay Using Microfluidic Immunoassay Technology. 

(29) Law, W. S.; Genin, J. C.; Miess, C.; et al. Use of Generic LC–MS/MS Assays to Characterize Atypical PK Profile of a Biotherapeutic Monoclonal Antibody. 

Immunogenicity Testing of Therapeutic Protein Products — Developing and Validating Assays for Anti-Drug Antibody Detection 

is the director of regulatory CMC for Arcutis Biotherapeutics.

is a principal scientist at Boehringer Ingelheim Pharmaceuticals.

is a principal of MWD Consulting. Direct correspondence to 

Cover Story

An overview of GLP regulations and related public standards.

Good Laboratory Practice: An Overview for the Analytical Chemist

This instalment of “Sample Prep Perspectives” reports the results obtained from a new survey on sample preparation techniques. This is our first survey since 2016 and its findings are compared with the results of previous surveys dating from 1991. Results uncover trends in the field over the last generation and their impact. The survey investigated trends in areas such as which technologies are currently being used, sample loads, sample sizes, automation, the use of solid-phase extraction (SPE) devices (cartridges, disks, plates, tips), SPE chemistries, selection criteria, and problems encountered. Respondents were also asked about sample preparation technologies on the horizon.

periodically surveys readers to uncover trends in the techniques, practice, and applications of sample preparation for chromatography. This year’s results are the seventh in this series (1–6). During these 32 years, several new technologies, including stir-bar sorptive extraction (SBSE), QuEChERS (quick, easy, cheap, effective, rugged, and safe) extraction, pressurized liquid extraction (PLE), and others have been introduced. Sample preparation needed to keep pace with developments in chromatography, including the more widespread use of mass spectrometry (MS) with chromatography, improvements in chromatography columns, such as exhibited in the increasing application of ultrahigh‑pressure liquid chromatography (UHPLC), and the continued push for more highly sensitive methods (for example, the U.S. Environmental Protection Agency [EPA]-proposed method to monitor perfluoroalkyl substances [PFAS] in drinking water at levels of four parts per trillion). Researchers promoting sample preparation in 1991 are approaching retirement or have already retired, while the new generation of laboratory workers has hopefully gained an appreciation for sample preparation that was missing a generation ago. Thus, this year’s survey is a golden opportunity to look at how the field has changed with regard to the increased attention to sample preparation over the last 30 to 40 years.

Similar to previous iterations of the survey, the publishers of 

distributed an internet-based survey to a statistically representative group of readers in March 2023, using a similar set of questions to the prior surveys. The response increased compared with previous surveys (541 respondents). During this month’s instalment of “Sample Preparation Perspectives”, we will look at general trends that have emerged and the current state of the field. In the January 2024 column, we will present Part 2 of the survey, focusing on trends in automation and technique-specific survey results.

The survey audience was largely similar to previous years, though there are some differences in their field of work. Far fewer respondents came from the pharmaceutical and over-the-counter drug sector than 10 years ago (6.4% in 2023 compared with 25.5% in 2013), while more worked in the environmental (15.5% vs. 13.8%), organic chemicals (15.0% vs. 6.1%), and medical/biological (11.3% vs. 9.1%) sectors. Figure 1 summarizes the self-reported fields of survey respondents in the 2013 and 2023 surveys. There is a good distribution of workplace organizations from which survey participants come, as depicted in the pareto chart in Figure 2. Compared with 2013, only about a third as many respondents come from private industry (16.4% in 2023 compared with 47.7% in 2013), but that amount is made up by increased numbers employed by research institutes and independent or contract laboratories. While the plurality of survey respondents still come from research and development positions, there are fewer research and development scientists and laboratory managers among the survey respondents than a decade ago, though those in academia, technical support, quality control, regulatory, all increased. These results, shown in Figure 3, demonstrate a nice distribution of job functions, with a balance between laboratory workers and supervisors, research and routine analysis, and other functions. Finally, we’ve never previously determined the geographic distribution of those who respond to our survey. This distribution seems to be representative of analysts globally, with 32.8% of respondents coming from North America, 27.5% from Central and South America, 24.5% from Europe, 12.0% from Asia, Australia, and the Pacific Rim, and 3.2% from Africa and the Middle East.

In the original 1991 survey, Majors provided a baseline for the status of the field of sample preparation, establishing the rationale for the research that advanced the area (1). Importantly, he queried surveyed researchers on their opinion of the importance of sample preparation. (For the purposes of this discussion, sample preparation is considered as the combination of all steps between the sample collection and storage steps and the actual analysis [that is, chromatography and detection]). Nearly all respondents (91%) felt sample preparation was a very (60%) or moderately (31%) important step in the analytical process. This reiterated the axiom borrowed from computer programming, “garbage in, garbage out”. This question was not asked in subsequent surveys, so after the development and adoption of new sample preparation technologies, automation, and other advances, does this strong opinion still predominate? After 32 years, chemists still have an overwhelmingly (84.5%) positive opinion of the importance of sample preparation. However, as observed with Figure 4, this opinion has moderated to some extent, with the moderately or minimally important categories seeing increased response. Several potential reasons could lead to this. As modern sample preparation addresses concerns such as cost, efficiency, time, and solvent use, the role and importance of these steps becomes less apparent.

Another observation not updated since 1991 was the distribution of time spent in a typical analysis. In 1991, analysts spent ten times as long processing their samples as the actual analysis (61% vs. 6%), and sample collection accounted for a similar amount of time (6%) as the analysis. Data management took the other significant block of time (27%). In the current survey, time is more evenly distributed across these areas. Significant improvements in sample preparation time via automation and newer sample preparation technologies appear to have lowered this time to be on par with the analysis. A little puzzling is the increase in relative time spent on sample collection, which can perhaps be attributed to a decrease in sample processing and analysis times and an increase in the time spent collecting more difficult or complex samples. Another possibility could be that more analysts are involved with the sample collection, as opposed to receiving samples brought to the laboratory by others, demonstrating better knowledge of sample collection requirements. These survey results are represented pictorially in Figure 5.

A new question in this year’s survey asked what influences the purchase of sample preparation products. Looking solely at “very important” factors, products leading to high recovery have the strongest influence (33.0% very important), but, overall, price (31.7% very important, 46.4% important) and time savings (29.2% very important, 47.7% important) are the greatest contributing factors, as displayed in Figure 6. Regarding price, for capital-intensive instrumental systems, it is hoped that those recommending purchase can delineate between the acquisition cost and the amoritized cost per sample. Product sterility is less of a concern, likely important mainly for analysts working with biological samples.

Adding a green perspective to chemical analysis has recently become increasingly important, not just an emerging interest. Our survey uncovered an overwhelming majority (88.6%) of respondents concerned with the environmental, health, and safety effects of the solvents used during sample preparation. To address these concerns, 39.0% of respondents are using solventless sample preparation methods such as solid-phase microextraction (SPME) or thermal desorption, and 30.8% are using smaller amounts of traditional aqueous or organic solvents. Others (20.6%) are considering direct sample analysis without sample preparation. Only 9.6% of analysts are using nontraditional solvents such as supercritical fluids or ionic liquids. Green solvent selection has been extensively studied and will be the focus of an upcoming “Sample Preparation Perspectives” column in 2024. Until then, analysts with concerns over the environmental, health, and safety considerations of solvent use may wish to consult resources provided by the American Chemical Society (ACS) Green Chemistry Institute (7,8) or other published solvent selection guides.

Analytical Errors and Problems with Sample Preparation

The 1991 survey also identified the major sources of error in an analytical scheme as sample processing (22.6%), operator (17.1%), and contamination (14.6%). These three items add up to over half (54.3%) of the error in an analytical process and can largely be attributed to the sample preparation steps. That is, in addition to the sample processing, sample preparation is the most labour‑intensive step in an analysis and the solvents, derivatizing agents, and other chemicals used in sample preparation provide opportunity for inadvertent addition of contaminants to the sample. Three decades later these three sources of error still contribute significantly. (Note that in the 2023 survey, participants were allowed to choose two responses to the question “During a typical analysis, what are the major sources of error?”) However, calibration was identified as the largest contributing factor to analytical error in the most recent survey, with integration also one of the major concerns.

These results are shown in Table 1. If each survey respondent selected two items for this question, the error contributed by “sample processing” decreased by about half over the last generation. Presumably, we can account for this because of the increased attention being placed on sample preparation in contemporary practice, the development and use of more efficient sample preparation techniques, and the increased use of automation (to be discussed in Part 2 of this survey). We can also assume that operator error will be minimized with increased use of automation. Perhaps the most alarming is the contribution of contamination to analytical error, given the solvent intensity of many sample preparation schemes and the potential for these solvents to introduce contaminants.

Turning to sample preparation, historically time and labour intensity, cost, and lack of reproducibility have been identified as the most frequent sample preparation problems. These were followed by insufficient sample knowledge, poor sample recovery, and contamination. The results from 10 years ago are presented in Table 2, along with those from the current survey. This year, poor sample recovery, lack of reproducibility, and interpretation of results rose to the top of the frequent sample preparation problems list, followed by cost and a cluster of items that includes time and labour intensity and insufficient sample knowledge. Looking into these results is both encouraging and perplexing. The significant decrease in time and labour intensity (from 60.8% in 2013 to 23.8% in 2023) is promising and may reflect the advances in the use of modern sample preparation techniques during this time. The numbers of respondents identifying cost (29.3% in 2013 vs. 26.8% in 2023), insufficient sample knowledge (22.7% vs. 22.5%), and contamination (12.4% vs. 13.8%) are largely unchanged. Perplexing is the sharp increase in responses to poor sample recovery (27.6% vs. 37.6%) and lack of reproducibility (24.0% vs. 30.9%). Perhaps a trend towards smaller sample sizes or more difficult sample matrices may explain this observation. Sample size will be discussed in Part 2 of these survey results and a discussion of sample matrices will follow.

During each survey, we query the types of sample matrices analyzed on a regular basis. This year’s results, compared with those from a decade ago, are listed in Figure 7. Significant changes occurred over the past decade. Several matrices decreased in the frequency of which they are analyzed, including pharmaceuticals and over-the-counter drugs (36.0% in 2013 vs. 23.3% in 2023), drinking water (18.4% vs. 14.9%), animal and biological tissues (20.9% vs. 13.1%), physiological fluids (18.4% vs. 11.3%), wastewater (17.6% vs. 10.2%), solvents (16.2% vs. 10.9%), and organic chemicals (23.5% vs. 15.3%). Matrices analyzed more frequently include air (8.9% in 2013 vs. 21.5% in 2023), polymers and monomers (16.7% vs. 31.7%), plants and biomass (14.1% vs. 31.3%), inorganic chemicals (8.2% vs. 24.0%), metals (7.8% vs. 19.3%), soils (11.8% vs. 18.4%), foods and food products (11.5% vs. 15.3%), grains (7.1% vs. 12.2%), cosmetics (6.6% vs. 9.3%), and gases (4.7% vs. 9.3%). “Other” sample matrices include biodiesel, illicit drugs, explosives, flavours and fragrances, fermentation broths, and honey, eggs, and dairy. It is probably fair to say that there is a more even distribution of analysts working across these sample matrices.

Figure 8 shows the sample types encountered in the respondent’s laboratories. Most significantly for solids, but in every case, the frequency for each sample type has decreased, indicating that laboratories appear to be more focused on the type of samples they analyze. The number of sample types per laboratory seems to have decreased from about two in 2013 to one and a half currently. The number of samples analyzed per week per analytical instrument has increased over the last decade, as demonstrated in Figure 9. However, the trend for the next two years is unclear, as 45.4% of survey respondents expect this number to increase and 39.1% expect a decreased sample load. This observation of fewer sample types, but increased sample loads, is perhaps a result of consolidation of laboratory operations concurrent with the pandemic or a similar systemic change.

The increased emphasis placed on sample preparation over the past generation has led to major changes in the practice of analytical chemistry in the laboratory. The current state of the field was presented, along with errors associated with sample preparation and general sample information. Part 2 of the survey results will be presented in the January 2024 “Sample Preparation Perspectives” column and will cover sample sizes analyzed, laboratory techniques used, automation, and solid-phase extraction (SPE) phases utilized.

(1) Majors, R. E. Trends in Sample Preparation 

(2) Majors, R. E. Trends in Sample Preparation 

(3) Majors, R. E. Trends in Sample Preparation 

(4) Majors, R. E. Trends in Sample Preparation. 

(5) Majors, R. E. Trends in Sample Preparation. 

(6) Raynie, D. E. Trends in Sample Preparation. 

https://learning.acsgcipr.org/guides-and-metrics/solvent-selection-guides/

Sample Preparation Perspectives

Results from our recent survey on sample preparation techniques uncover trends in the field over the last generation and their impact going forwards.

Trends in Sample Preparation, Part 1: Current State of the Field

Q. Why are per- and polyfluoroalkyl substances (PFAS) attracting attention at the moment and why is the analysis of these analytes important?

PFAS are the most persistent of all persistent organic pollutants (POPs). They stay in our bodies for many years, and they are not degraded at all in nature. The more we produce, the more they accumulate in the environment. The analysis is relatively complex because we deal with hundreds, if not thousands, of compounds with various chain lengths and different degrees of fluorination, both polar and neutral.

Q. You recently published a paper to determine several PFAS groups in food packaging material from fast-food restaurants in France (1). Can you tell us about the analytical method you used in this research project and any challenges you encountered developing the method?

The challenge is clearly in the separation; the sheer number of compounds that need to be separated properly because they all have their own toxicity is staggering. Total fluorine methods exist, but they may include compounds that do not belong to the PFAS and are thus prone to overestimation. The ionic compounds are normally analyzed by liquid chromatography tandem mass spectrometry (LC–MS/MS) and the neutral ones by gas chromatography (GC)–MS. Different types of mass spectrometers can be used. We used triple quad LC–MS/MS with electrospray ionization (ESI) in the negative mode. When buying a new LC system, it is important to ensure that no PFAS are leaking from the tubing in the instrument because that can causes a high background. Most companies are aware of that and can change the tubing prior to delivery.

In our paper, we started with the method used by Schaider et al. (2). We extracted twice with methanol and used larger cartridges (500 mg instead of 250 mg), and we used 1:1 (v/v) methanol–acetonitrile with 0.3% acetic acid, instead of only methanol. The parameters were optimized to analyze the polyfluoroalkyl phosphate esters (PAPs) with LC–MS/MS.

We used a 2.1 mm × 150 mm, 2.5‑μm particle-size C18 column, which was specifically designed for high pH, preceded by a 2.1 mm × 100 mm delay pre-column. The mobile phase used for the PAPs separation was a solution of ammonium acetate 2 mM (A) and methanol 100% (B) at a flow rate of 0.3 mL/min. The gradient was as follows: initial 95% of A during 0.5 min, decreasing to 50% A at 2 min, decreasing to 1% A at 10 min, kept constant at 1% A for 8 min, and, finally, re-conditioned for 5 min. For separation of the other analytes, the mobile phase consisted of a solution of ammonium acetate 2 mM (A) and 1:1 (v/v) methanol acetonitrile (B) at a flow rate of 0.45 mL/min. The gradient was as follows: initial 90% of A during 0.2 min, decreasing to 40% A at 6 min, decreasing to 5% A at 10 min, kept constant at 1% A for 8 min, and, finally, re-conditioned for 5 min.

Optimal source parameters for PAPs were: gas temperature: 400 °C, curtain gas: 30 psi, nebulizer gas: 55 psi, heater gas: 65 psi, and capillary voltage: 4500 V. For the other analytes the optimal parameters were: gas temperature: 400 °C, curtain gas: 35 psi, nebulizer gas: 60 psi, heater gas: 50 psi, capillary voltage: 4000 V. The detection limits obtained were extremely low, with 1 pg/g for 6:2/6:2 fluorotelomer phosphate diester (6:2/6:2 diPAP) to 28 pg/g for 4:2 fluorotelomer phosphate monoester (4:2 mPAP). Out of the 38 target PFAS or PAP compounds, 36 were detected.

Q. What is novel about your analytical approach and what benefits does it offer the analyst?

In this approach we analyzed PAPs, which are PFAS that include a phosphorus atom. They are often used in food packaging materials. We managed to develop a method for PAPs and PFAS.

The method we developed was suitable for the analysis of a series of PAPs and other PFAS. We found PAPs, but also other PFAS in many of the 47 food packaging materials from France that were analyzed. 6:2/6:2 diPAP was found in all samples. Perfluoroalkyl carboxylic acids (PFCAs), particularly perfluorooctaneoic acid (PFOA) and PAPs, were present in the highest concentrations—up to 287 ng/g for 8:2/8:2 fluorotelomer phosphate diester (8:2 diPAP). PFAS such as perfluorobutane sulfonate (PFBS), perfluorohexanesulfonic acid (PFHxS), perfluorooctane sulfonate (PFOS) (linear and branched), and 10:2 fluorotelomer sulfonic acid (10:2 FTS) were also detected. 6:2/6:2 diPAP has been reported in other paper-based materials such as baking paper, takeaway paper bags, cardboard cups, toilet paper, burger wrapping paper, and muffin cups, and also in paper mill waste streams. Gebbink et al. (3) reported that 6:2/6:2 diPAP is the main compound of Zonyl-RP and other Zonyl-based technical PAP mixtures, which are often used in food contact material manufacturing. Zonyl-RP is used to line grease-resistant packaging for candy, popcorn, and many other food products, and was already under discussion in 2005 because the human body may break down this product to the highly persistent and toxic PFOA (4). The PFAS/PAP levels were substantial and warn us that we should be careful with these packaging materials. The longer the contact with the food, the higher the chance the PFAS/PAPs enter the food and us.

Q. Are you planning to extend this research further in relation to food packaging?

At the moment there are no other plans in our university for further research on food packaging materials, mainly because there are many other questions related to PFAS that focus on production plants, human milk and blood, and eggs Some fast‑food companies have declared that they will stop using fluorine-based compounds in their packaging materials within the next one to two years.

We are currently working on an European research project called REVAMP, which focuses on the synthesis of analytical standards for PFAS (and chlorinated paraffins). There is an urgent need for such standards, and we have managed to synthesize over 40 new PFAS compounds (5).

Q. What other techniques have you used for PFAS analysis?

We have used GC–MS for the analysis of neutral PFAS (6). We have also used LC–MS/MS for the quantification of extractable perfluoroalkyl acids (PFAAs) and perfluorooctane sulfonamide (PFOSA) in textiles (7).

(1) Dueñas-Mas, M. J.; Ballesteros-Gómez, A.; de Boer, J. Determination of Several PFAS Groups in Food Packaging Material from Fast-Food Restaurants in France. 

(2) Schaider, L. A.; Balan, S. A.; Blum, A.; et al. Fluorinated Compounds in U.S. Fast Food Packaging. 

(3) Gebbink, W. A.; Ullah, S.; Sandblom, O.; Berger, U. Polyfluoroalkyl Phosphate Esters and Perfluoroalkyl Carboxylic Acids in Target Food Samples and Packaging- Method Development and Screening. 

https://www.foodnavigator.com/Article/2005/11/21/DuPont-hit-by-allegations-over-safety-of-packaging-chemical

(6) van der Veen, I.; Hanning, A.-C.; Stare, A.; et al. The Effect of Weathering on Per- and Polyfluoroalkyl Substances (PFASs) from Durable Water Repellent (DWR) Clothing. 

(7) van der Veen, I.; Weiss, J. M.; Hanning, A.-C.; de Boer, J.; Leonards, P. E. Development and Validation of a Method for the Quantification of Extractable Perfluoroalkyl Acids (PFAAs) and Perfluorooctane Sulfonamide (FOSA) in Textiles. 

Food Analysis

Alasdair Matheson spoke to Jacob de Boer of Vrije Universiteit Amsterdam about a recent innovative research project investigating per- and polyfluoroalkyl substances (PFAS) in fast food packaging.

Determining PFAS in Fast Food Packaging

In 2011, a series of workshops dedicated to sorptive extraction techniques was launched under the moniker SBSE Technical Meeting. This series of workshops has been a major meeting place for SPME and SBSE users, where theoretical considerations and practical experiences could be exchanged in an informal way. During these meetings, the green analytical chemistry aspects of techniques such as thermal extraction, headspace sampling, SPME, and SBSE were highlighted and demonstrated.

The Green Analytical Chemistry Workshop (1st TGAC) will be held
5–6 February 2024, at Novotel Paris-Charenton, Paris, France.

October 2023 | LCGC Europe

2D-LC–MS Approaches for the Analysis of In-Process Samples and for the Characterization of mAbs in a Regulated Environment

Evolution of LC Troubleshooting: Protective Devices and Column Repair

Good Laboratory Practice: An Overview for the Analytical Chemist

Trends in Sample Preparation, Part 1: Current State of the Field

Determining PFAS in Fast Food Packaging

The Green Analytical Chemistry Workshop (1st TGAC)