The Elisa guidebook

3.5.4¡ª

Working Standards

Working standards are very important forms of standards and are prepared in the laboratory in relatively large volumes. The extensive testing and validation

Page 331

required for the introduction of reference standard is not normally necessary, but the donor laboratory must assume responsibility for maintaining appropriate quality. This form of standard is common in animal disease diagnosis.

4¡ª

Shelf Life and Reagent Considerations

QC relies on the source and accurate preparation of reagents. The quality of reagents for certain stages can be more critical than others. With in-house assays, new reagents must be thoroughly characterized, and once this is done the controls can be restricted to those used for monitoring assay performance.

Regular checks are needed to examine deterioration in reagents. Assays based on kit material also require attention even though reagents are provided, because often producers do not provide complete test formats of individual reagent batches. A major problem is that test kit reagents have to be transported, and this can affect reagents (factors of robustness have already been mentioned). Each kit delivered must be checked. Kit overlapping is important, in which the new kit is evaluated against the old by testing the same samples. Reagents from the old kit can be substituted in order that the activity of new reagents can be determined. Instructions for the kits must be followed exactly, e.g., the reconstitution of freeze-dried reagents. These must be opened very carefully. because powdered material can easily be lost owing to the difference in pressure (lower) in the vial. There are manufacturing guidelines concerning reagents (8). These can be summarized as follows:

1.Liquid and freeze-dried reagents should be stored at 2¨C8¡ãC.

2.Reagents transported in dry ice should be stored at ¨C20¡ãC.

3.After reconstitution, freeze-dried reagents should be stored at 2¨C8¡ãC for short times, or as samples at ¨C20¡ãC.

4.Thawed reagents should not be refrozen.

4.1¡ª Liquids

Water quality plays a critical role for some reagents. Untreated water can contain inorganics, organics, dissolved gases, suspended solids, colloids, microorganisms, and pyrogens. Deionization and reverse osmosis are used to prepare water for laboratory use. Cation and anion-exchange resins are used to remove all dissolved ionizable substances and provide a primary water source. When coupled to specific ion-exchange resins or activated carbon resins, all organic or colloidal matter can be removed. Reverse osmosis uses a semipermeable membrane to separate substances from the water.

Most immunoassays can be performed with a water quality of 5 Ω/cm at 25¡ãC with an organic content of <2 ppm. Thus, use of deionization controlled by a conductivity meter is adequate to obtain water for assay and washing use in ELISA.

Page 332

Water quality can be a major problem in some countries. Attention has been focused on devising special units suitable for developing countries.

4.1.1¡ª

Aqueous Protein Solutions

Proteins can be relatively fragile in aqueous solution so that enzymes and antibodies need to be handled with care. High temperatures, and acid or alkaline solutions should be avoided. Temperatures above 40¡ãC cause denaturation of proteins. Solutions of proteins that are stirred vigorously are denatured by shearing action. The shelf life of proteins is prolonged by cold storage but attention should be focused on the state of the protein. For most enzymes in a dry phase, storage at 2¨C8¡ãC is good. Other enzymes may be unstable even dry and should be stored at ¨C20¡ãC. Repeated thawing is disastrous. Organic solvents should be avoided with enzymes except at concentrations of <3%. Enzyme labels can be supplied as liquids but need addition of cryoprotectants such as glycerol and polyethylene glycols, (approx 40% final concentration).

4.1.2¡ª Preservatives

Common preservatives in diagnostic reagents are as follows:

1.Thimerosal (0.01%): This is expensive, difficult to dispose of (mercuric compound), and can affect assays.

2.Sodium azide (0.02¨C0.1%): This is biostatic, difficult to dispose of, and can inhibit enzyme reactions.

Although both are used for various reagents in ELISA, they do pose problems of safety and disposal. A commercial product, ProClinTM, from Rohm and Haas, Spring House, PA, is recommended in ref. 8. It is reported to be a broad-spectrum biocide, having good compatibility and stability and low toxicity at inuse levels. It eradicates bacteria, fungi, and yeast cells at very low concentration, does not interfere with enzyme reactions, and can be disposed of without restrictions.

4.2¡ª

Shelf Life Evaluation

Evaluation of shelf life is related to the ruggedness of a test. The shelf life is a measure of the time within which the performance characteristics of a test are maintained under specified handling conditions. The change in quality is a function of factors such as storage temperature, humidity, package protection, and formulation. These are key factors in kits, which have to be dispatched and which may not be collected or used under the predetermined optimal conditions. This is particularly important in some developing countries, so that kit formulations must be tested for performance under a wider set of variables. There is an attempt to measure product expiration times with commercial kits

Page 333

through practical determination of stability. This is also tied up with governmental regulations. For example, the Food and Drug Administration requires written testing programs designed to examine the stability of products based on these factors:

1.The sample size and the test intervals for each attribute measured.

2.Reliable, specific, and meaningful tests to assess quality.

3.The conditions under which held-back samples are stored.

4.Testing to be conducted under the same conditions as in the intended market.

5.Tests to be conducted at the time of dispensing, as well as after reconstitution of reagents.

4.2.1¡ª

Types of Stability

Physical, bacteriostatic, and functional stabilities are important. Physical appearance such as discoloration and precipitation is undesirable. Most products contain bacteriocidal or bacteriostatic compounds to prevent deterioration through microbial growth. Thus, on storage, the active component must remain at a sufficiently high level to work. Functional changes are damaging to the assay's performance (can reduce analytical and diagnostic sensitivity and specificity). These can involve functional changes owing to antibody degradation, as well as chemical changes affecting function, e.g., in chromophore quality owing to oxidation or reduction.

4.2.2¡ª

Criteria for Shelf Life

A typical quality criterion for shelf life is that the product must retain at least 90% of its original value throughout its life. This performance is often applied to assessing the results of stability testing. Reagents used in ELISA, and diagnostic kits in general, must have a long shelf life. Most reagents are stable when unopened. It is desirable to have single lots of reagents, which can be used over a long period in many laboratories. Stability involves factors of degradation. The rates of degradation for given reagents are defined by the laws of chemistry and physics. The dominating factor for a given pH, ionic strength, composition, and so on, is temperature. Thus, degradation of any product can be monitored at high temperatures and the information extrapolated to the anticipated storage temperature, to determine the usable shelf life.

4.3¡ª

Real-Time Stability Testing

The testing of products in real time has to be regarded as the gold standard for determination of expiry dates. However, this is not practical in most cases. Products must be left to allow a degradation to be observed. Methods to measure at least a 1% degradation, as distinct from interassay variation, must be available. The reliability can be increased if a single lot reference is included

Page 334

with each test point. Sample recovery among samples can be normalized to this reference to minimize the impact of systematic drift and imprecision. The reference materials themselves should be sufficiently stable so that a single lot provides unchanging performance throughout stability testing. In brief, the realtime data collection is complicated by drift or changes in the testing method used over a period of time.

4.4¡ª

Accelerated Stability Testing

Accelerated stability testing is often used when developing clinical reagents to provide an early indication of shelf life. The method involves subjecting products to several high temperatures. The amount of heat input needed to cause product failure is determined. An efficient system requires at least four ''stress" temperatures (10). Temperatures that cause denaturation should not be used. This is particularly true for labile proteinaceous reagents, such as antibodies and enzymes. One advantage is that samples can be subjected to elevated temperatures, stored at low temperature, and then assayed at the same time as unstressed controls. There are several approaches to analysis, involving different mathematical methods.

4.4.1¡ª

Protocol for Accelerated Stability Testing

Four parameters for accelerated stability testing must be considered (9):

1. Preparation of samples: The samples must be as close to, if not identical to those to be used in assays. This includes containers.

2.Storage conditions: Four temperatures for storage should be examined. The highest temperature is determined by the type of substance being examined (e.g., to avoid denaturation of proteins, and by the length of time available to devote to the assays). Lower temperatures may be needed when the containers themselves are affected.

3.Analytical procedures: The analytical method used must be meaningful for the active reagent of the product. Chemical assays are reliable up to 2¡ãC but biological assays only to 5¡ãC. It is vital that the initial assay be titrated extremely accurately in multiple replicates to allow the determination of degradation.

4.Analysis and interpretation of data: Methods are reviewed in ref. 8, Chapter 10. These exploit the Arrhenius relationship, which states that the functional relationship between time and stability of a product stored under constant conditions is dependent on the order of reaction and the rate constant that determines the speed of reaction. A general guideline is shown in ref. 8, Chapter 10 which delineates the steps as follows:

a.Select four temperatures. Define degradation, e.g., loss of total function or clinical parameter (enzyme concentration, percentage of binding of a reference material to an antibody at a predetermined concentration, and so on). Place the reagents in incubators at the predefined temperatures. If degrada-

Page 335

tion is not observed within a reasonable time (e.g., 1¨C2 mo), then select higher temperatures. There must be degradation for determination of shelf life.

b.Place a sufficient amount of reagent in the final containers, at the selected temperatures, for specified time periods. This will depend on the estimated rate of degradation. The volume/amount will depend on test method requirements, but there should be enough to allow testing to run duplicate assays for each point of a minimum three-point assay curve. Higher temperatures should be sampled more frequently than lower. The following protocols are suggested: 37¡ãC once every 5 d; 45¡ãC once every 4 d; 50¡ãC once every 3 d; 60¡ãC once every 2 d; and, 80¡ãC once every day.

c.Samples should be cooled on removal from elevated temperatures and analyzed promptly.

d.Measurements can be made on any critical components.

e.Data plotted against day number should give an approximate straight line using semilog graph paper. Conventionally, the slope is measured. However, the measure of the length of time for activity (potency) to drop by 90% of the original value, or any other appropriate criterion, can be selected and determined from the graph. The real situation requires an estimation of the maximum allowable drop in activity that would not affect the functioning of the product and thus the assay performance.

f. From such a set of data, one can predict the time required to reach 90% potency at the desired temperature. The logarithms of the t90 values are related linearly to the reciprocal of the absolute temperature.

g. A semilog plot of t90 values (ordinate) and 1/T in Kelvins (abscissa) should give a straight line. From this, the predicted shelf life at the desired storage temperature can be calculated.

Based on the experiences of the author in ref. 8, here are some guidelines to approximate the shelf life of a product at a desired temperature.

1. One month at 50¡ãC is equivalent to 1 yr at room temperature.

2, Two months at 50¡ãC is equivalent to 2 yr at room temperature.

3.Three months at 37¡ãC is equivalent to 1 yr at room temperature.

4.Six months at 37¡ãC is equivalent to 2 yr at 4¡ãC.

5.Seven days at 37¡ãC is equivalent to 1 yr at 4¡ãC

6.Three days at 37¡ãC is equivalent to 3-6 months at 4¡ãC.

5¡ª Literature

Further information on the various aspects of validation can be obtained in refs. 10 and 11. In addition, an excellent review of advanced methods for test validation and interpretation in veterinary medicine is available in ref. 12.

6¡ª Statistics

This section reviews some statistical terms and principles. The purpose of ELISA is to measure quantities or compare antigens or antibodies through

Page 336

measuring the level of binding or inhibition of binding of some labeled material. Statistical analyzes are applicable to both the assay itself, through examination of the variation inherent under different conditions and to the data generated and its relevance to the problem investigated. Thus, statistical analysis is inherent in ELISA development, for continuous use (monitoring performance), and to analyze the results for specific samples (e.g., whether a sample falls into a positive or negative population). Statistics also assess results in terms of confidence in the values obtained.

It is vital to understand that statistical examination should never be regarded as the last thing to do when faced with data. Consideration of what statistical methods are to be used must be made during the planning stages, so that data can be immediately assessed, particularly since computer software is often used. A key is to ask, How can anyone prove anything associated with an assay? Proof statistically is, by definition, a measure of the probability of an event. The stronger the measure of the statistical probability, the more true the measure is.

6.1¡ª Populations

A major use of ELISA is to obtain data from sample analysis and assess whether a particular sample is positive (contains a particular analyte) or negative (does not contain analyte). This requires both the examination of the specific assay parameters (assessing sensitivity and specificity) and the defining of a specific population in terms of data obtained and with reference to other data from other tests. The establishment of a population statistic requires that the data be obtained and analyzed. The analysis determines the type of distribution of data, and hence any sample value can be assessed with reference to all data in that population. The amount of data obtained to establish a population affects the certainty of any result, as does where the samples were taken from to establish the population (sampling/survey statistics).

6.2¡ª

Basic Terms

These are a few basic terms:

1.The mean is the arithmetic mean of a set of data.

2.The median defines a value or interval range of values in the middle of a set of values in a population.

3.The mode defines the value or interval range that is most frequent in any population.

These are illustrated in Fig. 6 as a plot of the data shown in Table 3. These are OD results from the analysis of a supposedly negative population of samples. The interval has been selected as 0.02 OD units represented on the x-axis, and the numbers of samples in any defined interval are plotted on the y-axis.

Page 337

Fig. 6.

Frequency histogram of data in Table 3.

Table 3

Data from Analysis of Samples

	Number
OD interval	(frequency)
0.00¨C0.02	1
0.02¨C0.04	2
0.04¨C0.06	5
0.06¨C0.08	9
0.08¨C0.10	21
0.10¨C0.12	18
0.12¨C0.14	12
0.14¨C0.16	9
0.16¨C0.18	7
0.18¨C0.20	4
0.20¨C0.22	2
0.22¨C0.24	2
0.24¨C0.26	0

Figure 6 represents actual data for 77 results taken from a population of samples. We can see that there is a peak where most of the data are placed from intervals about 0.08¨C0.16. Lower numbers are observed on either side of this.

Page 338

Fig. 7.

Frequency histogram of data in Table 3 with normal distribution plotted and the mean, median, and mode highlighted.

The mean, median and mode can be described for this data as shown in Fig. 7. The data is shown as a distribution curve and these can be defined mathematically according to which distribution they fit. Some distribution curves are shown in Fig. 8. The statistics involving normal distribution curves are illustrated in Fig. 9.

6.2.1¡ª

Normal Distribution

When the distribution is symmetrical, it is referred to statistically as a Gaussian or normal distribution. In a perfect case, the mean, mode, and median are identical. Although this perfect situation is never achieved in practice, most situations for ELISA regard distributions as normal. The normal distribution can be described in mathematical terms with regard to the mean (X) and the SD of the observed values. The use of sampling techniques and the examination of distribution in samples attempts to determine the true mean (u) and variance (S2) of the entire population from which the samples are taken. The breakdown in the statistical considerations of a normal distribution are shown in Fig. 9. The key here is that whatever the measured values, a certain percentage of the sample is always contained within the SD values. One SD on either side of the mean contains 68% of all values under the curve of that distribution. In the

Page 339