QUALITY ASSURANCE AND QUALITY CONTROL DURING SAMPLE PREPARATION

QUALITY ASSURANCE AND QUALITY CONTROL DURING SAMPLE PREPARATION

As the complete analytical process involves sampling, sample preservation, sample preparation, and finally, analysis. The purpose of quality assurance (QA) and quality control (QC) is to monitor, measure, and keep the systematic and random errors under control. QA/QC measures are necessary during sampling, sample preparation, and analysis. It has been stated that sample preparation is usually the major source of variability in a measurement process. Consequently, the QA/QC during this step is of utmost importance. The discussion here centers on QC during sample preparation.

Quality assurance refers to activities that demonstrate that a certain quality standard is being met. This includes the management process that implements and documents effective QC. Quality control refers to procedures that lead to statistical control of the different steps in the measurement process. So QC includes specific activities such as analyzing replicates, ensuring adequate extraction efficiency, and contamination control. Some basic components of a QC system are shown in Figure 1.10. Competent

personnel and adequate facilities are the most basic QC requirements. Many modern analytical/sample preparation techniques use sophisticated instruments that require specialized training. Good laboratory

practice (GLP) refers to the practices and procedures involved in running a laboratory. Efficient sample handling and management, record keeping, and equipment maintenance fall under this category. Good measurement practices (GMPs) refer to the specific techniques in sample preparation and analysis. On the other hand, GLPs are independent of the specific techniques and refer to general practices in the laboratory. An important QC step is to have formally documented GLPs and GMPs that are followed carefully.

Sample Preservation Techniques

Quality assurance and quality control

Standard operating procedures (SOPs) are written descriptions of procedures of methods being followed. The importance of SOPs cannot be understated when it comes to methods being transferred to other operators or laboratories. Strict adherence to the SOPs reduces bias and improves precision. This is particularly true in sample preparation, which tends to consist of repetitive processes that can be carried out by more than one procedure. For example, extraction efficiency depends on solvent composition,

extraction time, temperature, and even the rate of agitation. All these parameters need to be controlled to reduce variability in measurement. Changing the extraction time will change the extraction efficiency, which will increase the relative standard deviation (lower precision). The SOP specifies these parameters. They can come in the form of published standard methods obtained from the literature, or they may be developed in-house. Major sources of SOPs are protocols obtained from organizations, such as

the American Society for Testing and Materials and the U.S. Environmental  Protection Agency (EPA).

Finally, there is the need for proper documentation, which can be in written or electronic forms. These should cover every step of the measurement process. The sample information (source, batch number, date), sample preparation/analytical methodology (measurements at every step of the process, volumes involved, readings of temperature, etc.), calibration curves, instrument outputs, and data analysis (quantitative calculations, statistical analysis) should all be recorded. Additional QC procedures, such as blanks, matrix recovery, and control charts, also need to be a part of the record keeping. Good documentation is vital to prove the validity of data. Analytical data that need to be submitted to regulatory agencies also require detailed documentation of the various QC steps.

Procedures in Quality Control

The major quality parameters to be addressed during sample preparation are listed in Table. These are accuracy, precision, extraction e‰ciency (or recovery), and contamination control. These quality issues also need to be addressed during the analysis that follows sample preparation. Accuracy is determined by the analysis of evaluation samples. Samples of known concentrations are analyzed to demonstrate that quantitative results are close to the true value. The precision is measured by running replicates. When many samples are to be analyzed, the precision needs to be checked periodically to

ensure the stability of the process. Contamination is a serious issue, especially in trace measurements such as environmental analysis. The running of various blanks ensures that contamination has not occurred at any step, or that if it has, where it occurred. As mentioned before, the detection limits, sensitivity, and other important parameters depend on the recovery. The e‰ciency of sample preparation steps such as extraction and cleanup must be checked to ensure that the analytes are being recovered from the sample.

Determination of Accuracy and Precision

The levels of accuracy and precision determine the quality of a measurement. The data are as good as random numbers if these parameters are not specified. Accuracy is determined by analyzing samples of known concentration (evaluation samples) and comparing the measured values to the known. Standard reference materials are available from regulatory agencies and commercial vendors. A standard of known concentration may also be made up in the laboratory to serve as an evaluation sample. Effective use of evaluation samples depends on matching the standards with the real-world samples, especially in terms of their matrix. Take the example of extraction of pesticides from fish liver. In a real sample, the pesticide

is embedded in the liver cells (intracellular matter). If the calibration standards are made by spiking livers, it is possible that the pesticides will be absorbed on the outside of the cells (extracellular). The extraction of Table 1.4. Procedures in Quality Control QC Parameters Procedure Accuracy Analysis of reference materials or known standards Precision Analysis of replicate samples Extraction efficiency Analysis of matrix spikes Contamination Analysis of blanks 28 sample preparation: an analytical perspective extracellular pesticides is easier than real-world intracellular extractions. Consequently, the extraction efficiency of the spiked sample may be significantly higher. Using this as the calibration standard may result in a negative bias. So matrix e¤ects and matrix matching are important for obtaining high accuracy. Extraction procedures that are powerful enough not to have any matrix dependency are desirable. Precision is measured by making replicate measurements. As mentioned before, it is known to be a function of concentration and should be determined at the concentration level of interest. The intrasample variance can be determined by splitting a sample into several subsamples and carrying out the sample preparation/analysis under identical conditions to obtain a measure of RSD. For example, several aliquots of homogenized fish liver can be processed through the same extraction and analytical procedure, and the RSD computed. The inter-sample variance can be measured by analyzing several samples from the same source. For example, different fish from the same pond can be analyzed to estimate the intersample RSD. The precision of the overall process is often determined by the extraction step rather than the analytical step. It is easier to get high-precision analytical results; it is much more difficult to get reproducible extractions. For example, it is possible to run replicate chromatographic runs (GC or HPLC) with an RSD between 1 and 3%. However, several EPA-approved methods accept extraction efficiencies anywhere between 70 and 120%. This range alone represents variability as high as 75%. Consequently, in complex analytical

methods that involve several preparative steps, the major contributor to variability is the sample preparation.

Statistical Control

Statistical evidence that the precision of the measurement process is within a certain specified limit is referred to as statistical control. Statistical control does not take the accuracy into account. However, the precision of then measurement should be established and statistical control achieved before accuracy can be estimated. Control Charts Control charts are used  for monitoring the variability and to provide a graphical display of statistical control. A standard, a reference material of known concentration, is analyzed at specified intervals (e.g., every 50 samples).The result should fall within a specified limit, as these are replicates.

The only variation should be from random error. These results are plotted on a control chart to ensure that the random error is not increasing or that a systematic bias is not taking place. In the control chart shown in Figure, replicate measurements are plotted as a function of time. The centerline

is the average, or expected value. The upper (UCL) and lower (LCL) control limits are the values within which the measurements must fall. Normally, the control limits areG3s, within which 99.7% of the data should lie. For example, in a laboratory carrying out microwave extraction on a daily basis, a standard reference material is extracted after a fixed number of samples. The measured value is plotted on the control chart. If it falls outside the control limit, readjustments are necessary to ensure that the process

stays under control. Control charts are used in many different applications besides analytical measurements. For example, in a manufacturing process, the control limits are often based on product quality. In analytical measurements, the control limits can be established based on the analyst’s judgment and the experimental results. A common approach is to use the mean of select measurements as the centerline, and then a multiple of the standard deviation is used to set the control limits. Control charts often plot regularly scheduled analysis of a standard reference material or an audit sample. These are then tracked to see if there is a trend or a systematic deviation from the centerline.

Control Samples

Di¤erent types of control samples are necessary to determine whether a measurement process is under statistical control. Some of the commonly used control standards are listed here.

1. Laboratory control standards (LCSs) are certified standards obtained from an outside agency or commercial source to check whether the data being generated are comparable to those obtained elsewhere. The LCSs provide a measure of the accuracy and can be used as audits. A source of LCSs is standard reference materials (SRMs), which are certified standards available from the National Institute of Standards and Testing (NIST) in the United States.

 2. Calibration control standards (CCSs) are used to check calibration.The CCS is the first sample analyzed after calibration. Its concentration may or may not be known, but it is used for successive comparisons.A CCS may be analyzed periodically or after a specified number of samples (say, 20). The CCS value can be plotted on a control chart to monitor statistical control.

Matrix Control

Matrix Spike

Matrix effects play an important role in the accuracy and precision of a measurement. Sample preparation steps are often sensitive to the matrix. Matrix spikes are used to determine their e¤ect on sample preparation and analysis. Matrix spiking is done by adding a known quantity of a component that is similar to the analyte but not present in the sample originally.The sample is then analyzed for the presence of the spiked material to evaluate the matrix effects. It is important to be certain that the extraction recovers most of the analytes, and spike recovery is usually required to be at least 70%. The matrix spike can be used to accept or reject a method. quality assurance and quality control For example, in the analysis of chlorophenol in soil by accelerated solvent extraction followed by GC-MS, deuterated benzene may be used as the matrix spike. The deuterated compound will not be present in the original sample and can easily be identified by GC-MS. At the same time, it has chemical and physical properties that closely match those of the analyte of interest. Often, the matrix spike cannot be carried out at the same time as the analysis. The spiking is carried out separately on either the same matrix or on one that resembles the samples. In the example above, clean soil can be spiked with regular chlorophenol and then the recovery is measured. However, one should be careful in choosing the matrix to be spiked. For instance, it is easy to extract different analytes from sand, but not so if the analytes have been sitting in clay soil for many years. The organics in the soil may provide additional binding for the analytes. Consequently, a matrix spike may be extracted more easily than the analytes in real-world samples. The extraction spike may produce quantitative recovery, whereas the extraction efficiency for real samples may be significantly lower. This is especially true for matrix-sensitive techniques, such as supercritical extraction.

Surrogate Spike

Surrogate spikes are used in organic analysis to determine if an analysis has gone wrong. They are compounds that are similar in chemical composition and have similar behavior during sample preparation and analysis. For example, a deuterated analog of the analyte is an ideal surrogate during GC-MS analysis. It behaves like the analyte and will not be present in the sample originally. The surrogate spike is added to the samples, the standards, the blanks, and the matrix spike. The surrogate recovery is computed for each run. Unusually high or low recovery indicates a problem, such as contamination or instrument malfunction. For example, consider a set of samples to be analyzed for gasoline contamination by purge and trap. Deuterated toluene is added as a surrogate to all the samples, standards, and blanks. The recovery of the deuterated toluene in each is checked. If the recovery in a certain situation is unusually high or low, that particular analysis is rejected.

Contamination Control

Sources of Sample Contamination

Many measurement processes are prone to contamination, which can occur at any point in the sampling, sample preparation, or analysis. It can occur in the field during sample collection, during transportation, during storage, in the sample workup prior to measurement, or in the instrument itself. Some common sources of contamination are listed in Table . Contamination becomes a major issue in trace analysis. The lower the concentration, the more pronounced is the effect of contamination. Sampling devices themselves can be a source of contamination. Contamination may come from the material of construction or from improper cleaning. For example, polymer additives can leach out of plastic sample bottles, and organic solvents can dissolve materials from surfaces, such as cap liners of sample vials. Carryover from previous samples is also possible. Say that a sampling device was used where the analyte concentration was at the 1 ppm level. A 0.1% carryover represents a 100% error if the concentration of the next sample is at 1 part per billion (ppb). Contamination can occur in the laboratory at any stage of sample preparation

and analysis. It can come from containers and reagents or from the ambient environment itself. In general, contamination can be reduced by avoiding manual sample handling and by reducing the number of discrete processing steps. Sample preparations that involve many unautomated manual steps are prone to contamination. Contaminating sources can also be present in the instrument. For instance, the leftover compounds from a

previous analysis can contaminate incoming samples.

Blanks

Blanks are used to assess the degree of contamination in any step of the measurement process. They may also be used to correct relatively constant,

Types of Blanks

Unavoidable contamination. Blanks are samples that do not contain any (or a negligible amount of ) analyte. They are made to simulate the sample matrix as closely as possible. Different types of blanks are used, depending on the procedure and the measurement objectives. Some common blanks are listed in Table. Blank samples from the laboratory and the field are required to cover all the possible sources of contamination. We focus here on those blanks that are important from a sample preparation perspective. System or Instrument Blank. It is a measure of system contamination and is the instrumental response in the absence of any sample. When the background signal is constant and measurable, the usual practice is to consider that level to be the zero setting. It is generally used for analytical instruments

but is also applicable for instruments for sample preparation. The instrument blank also identifies memory effects or carryover from previous samples. It may become significant when a low-concentration sample is analyzed immediately after a high-concentration sample. This is especially true where preconcentration and cryogenic steps are involved. For example, during the purge and trap analysis of volatile organics, some components may be left behind in the sorbent trap or at a cold spot in the instrument. So it is a common practice to run a deionized water blank between samples. These blanks are critical in any instrument, where sample components may be left behind only to emerge during the next analysis.

Solvent/Reagent Blank. A solvent blank checks solvents and reagents that are used during sample preparation and analysis. Sometimes, a blank correction or zero setting is done based on the reagent measurement. For example, in atomic or molecular spectroscopy, the solvents and reagents used in sample preparation are used to provide the zero setting. Method Blank. A method blank is carried through all the steps of sample preparation and analysis as if it were an actual sample. This is most important from the sample preparation prospective. The same solvents/reagents that are used with the actual samples are used here. For example, in the analysis of metals in soil, a clean soil sample may serve as a method blank. It is put through the extraction, concentration, and analysis steps encountered by the real samples. The method blank accounts for contamination that may occur during sample preparation and analysis. These could arise from the reagents, the glassware, or the laboratory environment. Other types of blanks may be employed as the situation demands. It should be noted that blanks are effective only in identifying contamination. They do not account for various errors that might exist. Blanks are seldom used to correct for contamination. More often, a blank above a predetermined value is used to reject analytical data, making reanalysis and even resampling necessary. The laboratory SOPs should identify the blanks necessary for contamination control.