The sampler brings the sample mixture into the mobile phase stream which carries it into the column. The pumps deliver the desired flow and composition of the mobile phase through the column.
The detector generates a signal proportional to the amount of sample component emerging from the column, hence allowing for quantitative analysis of the sample components. A digital microprocessor and user software control the HPLC instrument and provide data analysis. Some models of mechanical pumps in a HPLC instrument can mix multiple solvents together in ratios changing in time, generating a composition gradient in the mobile phase.
Most HPLC instruments also have a column oven that allows for adjusting the temperature at which the separation is performed.
The sample mixture to be separated and analyzed is introduced, in a discrete small volume typically microliters , into the stream of mobile phase percolating through the column. The components of the sample move through the column at different velocities, which are a function of specific physical interactions with the adsorbent also called stationary phase. The velocity of each component depends on its chemical nature, on the nature of the stationary phase column and on the composition of the mobile phase.
The time at which a specific analyte elutes emerges from the column is called its retention time. The retention time measured under particular conditions is an identifying characteristic of a given analyte.
Many different types of columns are available, filled with adsorbents varying in particle size, and in the nature of their surface "surface chemistry".
The use of smaller particle size packing materials requires the use of higher operational pressure "backpressure" and typically improves chromatographic resolution the degree of peak separation between consecutive analytes emerging from the column. Sorbent particles may be hydrophobic or polar in nature. Common mobile phases used include any miscible combination of water with various organic solvents the most common are acetonitrile and methanol.
Some HPLC techniques use water-free mobile phases see normal-phase chromatography below. The aqueous component of the mobile phase may contain acids such as formic, phosphoric or trifluoroacetic acid or salts to assist in the separation of the sample components. The composition of the mobile phase may be kept constant "isocratic elution mode" or varied "gradient elution mode" during the chromatographic analysis.
Isocratic elution is typically effective in the separation of sample components that are very different in their affinity for the stationary phase. In gradient elution the composition of the mobile phase is varied typically from low to high eluting strength. Periods of constant mobile phase composition may be part of any gradient profile. The chosen composition of the mobile phase also called eluent depends on the intensity of interactions between various sample components "analytes" and stationary phase e.
Depending on their affinity for the stationary and mobile phases analytes partition between the two during the separation process taking place in the column. This partitioning process is similar to that which occurs during a liquid—liquid extraction but is continuous, not step-wise.
The choice of mobile phase components, additives such as salts or acids and gradient conditions depends on the nature of the column and sample components. Often a series of trial runs is performed with the sample in order to find the HPLC method which gives adequate separation. Prior to HPLC scientists used standard liquid chromatographic techniques.
Liquid chromatographic systems were largely inefficient due to the flow rate of solvents being dependent on gravity. Separations took many hours, and sometimes days to complete. Gas chromatography GC at the time was more powerful than liquid chromatography LC , however, it was believed that gas phase separation and analysis of very polar high molecular weight biopolymers was impossible. Early developmental research began to improve LC particles, and the invention of Zipax, a superficially porous particle, was promising for HPLC technology.
The s brought about many developments in hardware and instrumentation. Araujo and Janagap have discussed in detail the principles of Doehlert uniform shell designs aka Doehlert designs and their purpose in chromatography. Along with it, they have concluded that Doehlert uniform shell designs are generally used for determining the optimal combination of the factors that have the strongest influence on selected single or multiple experimental responses although the chromatographic system is influenced by more than 50 factors Van Leeuwen et al.
Doehlert designs should not be used for more than three factors as this would lead to a high number of experiments and complications in predictions Araujo and Janagap Recently Hibbert suggested in his review that Doehlert designs are becoming more popular due to greater efficiency in optimizing chromatographic conditions.
Some other designs with unprecedented and mysterious status in pharmaceutical and thereby in the chromatographic analysis are supersaturated designs, nested designs or nested analysis of variance ANOVA and split-plot designs. The application of supersaturated designs in pharmaceutical analysis is not very common.
Being recently developed designs although, these may be used as screening designs. A supersaturated design when applied for multiple factor effects of main factors is confounded and cannot be estimated unconfounded anymore Dejaegher and Vander Heyden A supersaturated design may be constructed as a two-level, multi-level or mixed-level design, any of which can be applied thereafter depending on experiments Dejaegher and Vander Heyden Nested design or nested ANOVA Vander Heyden and Massart as referred before in only by Dejaegher and Vander Heyden is proved to be useful during ICH robustness and ruggedness testing to determine the influence of factors at several levels.
Split-plot EDs are uncommon in chemistry and hence in the chromatographic analysis Cornell The use of such designs involves performing a block of experiments to investigate a system usually followed by an identical replicate block to measure experimental errors Bortoloti et al.
Split-plot designs normally involve a large number of factors. Figure 2 depicts the dominance of various designs employed in the literature for HPLC as a recent trend. The data were generated based on scifinder search for the years and CCD can be seen as the design of choice and employed in most of the publications involving the use of DoE during HPLC determination of pharmaceutical drugs and drug products.
Based on the existing research articles in the literature, the various types of EDs applied in chromatography till date can be classified arbitrarily for the sake of better understanding of their applicability into screening designs, response surface designs and mixture designs. These three types are again divided into subtypes.
The various types and associated subtypes of designs employed in the betterment of chromatography are represented in Figure 3. Arbitrary classification for various types of EDs used in the literature for chromatographic studies.
Preliminary investigations need to be carried out in the same way as that of the regular protocol for the liquid chromatographic method development and validation, while aspiring for application of ED during chromatographic analyses, which includes steps such as selection of initial HPLC conditions and optimization of the mobile phase.
Factors related to the chromatographic analytical procedure can be considered as operational factors or environmental factors. Operational factors are based upon the operating procedure during chromatographic analysis, whereas the environmental factors are not necessarily specified explicitly in the analytical method. The selected factors can be quantitative continuous , qualitative discrete or mixture factors Vander Heyden et al. Such 50 factors or independent variables have been mentioned in the previous literature which are supposed to influence HPLC methods and related analyses Van Leeuwen et al.
Mixtures of solvents are often used in analytical methods. If one component of a mixture is found to be important, this means in practice that the mixture composition as a whole is important. Because it is not possible to control only one of the components of a mixture, the composition of the mixture as a whole should be more strictly controlled Vander Heyden et al.
Moreover, the list continues further if the analysis is supported by pre-column or post-column derivatization Fabre et al. These factors are related to the sample preparation step sample weight, internal standard concentration, sonication time, the volume of extraction solvent, the age of the solutions, etc.
Typical factors are, for example, the flow rate and mobile-phase composition buffer pH and concentration, the smallest component in the solvent mix, additive concentration, etc. As the changes in level values are small, limited numbers of factors are expected to affect the results. Due to the time constraints and practical limitations, the number of factors is limited up to eight and it is important to perform experiments over a limited period of time to obtain reliable results Fabre Selection of factors during the development and validation of the HPLC method may vary depending upon the step of analytical determination; for example, the proportion of organic phase and flow rate are usually responsible for RS and peak shape.
Although the wavelength maximum is usually considered for analytical method development, the drugs depicting absorbance at more than one wavelength create a choice for the selection of suitable wavelength. Studies involving determination of two analytes at a time required to a have a common wavelength at which the detection of both drugs can be carried out effectively. Hence, the effect of wavelength selected on chromatographic analysis can be taken into consideration, and one wavelength can be preferred depending on whether it is a critical factor and the effects, positive or negative, it is depicting on the responses to be measured Ribeiro et al.
Examples of quantitative factors are the pH of a solution, the temperature or the concentration of a solution, for qualitative factors the batch of a reagent or the manufacturer of a chromatographic column and for mixture factors the fraction of organic modifier in a mobile phase.
The selected factors should represent those that are most likely to be changed when a method is transferred between laboratories, analysts or instruments and that potentially could influence the response s of the method Vander Heyden et al. As referred earlier several variables may influence the response of the system studied, and it is practically impossible to recognize and control the small contributions from each one.
Hence, it is necessary to select those variables with major effects. Screening designs should be carried out to determine which of the several experimental variables and their interactions present more significant effects. Full or fractional two-level factorial designs may be used for this objective principally because they are efficient and economical Lundstedt et al. Factors to be studied may be obvious from the nature of the system. Ruggedness tests in method validation will have had the factors for the study prescribed in the protocol Hibbert and Gooding If it is known that a factor has a great effect of the separation perhaps column temperature , there is no point in discovering this information in a screening design.
It can be included immediately in the factors for optimization. Discrete-valued factors such as column type might be studied separately rather than as part of a design. Thus mobile-phase composition, flow rates and gradients might be optimized for a C8 column and then for a C18 column Hibbert The variations encountered in different laboratories due to the use of different instruments, stationary phases, environmental conditions, analysts, etc.
It should be kept in mind that a two-level factorial design implies a linear relationship between the factor and the response, which is not always verified. This is because the method has already been optimized and the nominal level for one or several factors may be close to the optimum, yielding a non-linear response between the two extreme levels tested apart from this value Fabre The main effect of wavelength will not be disclosed by comparing the two extreme levels if the two wavelengths are situated on each side of the maximum absorbance wavelength.
The comparison of the responses at low and high levels without running experiments at the nominal level center point should not be the rule Caporal-Gautier et al. The factor levels are usually defined symmetrically around the nominal level prescribed in the operating procedure.
The interval chosen between the extreme levels represents the somewhat exaggerated limits between which the factors are expected to vary when a method is transferred. However, selection of the levels can also be based on the precision or the uncertainty with which a factor can be set and reset Morgan Recently, as quoted by Hibbert , the choice of factor levels in a design is most important, possibly more than the design itself.
Obtaining information using only a small number of factor levels is the strength of DoE, but also a potential weakness. Each level must be appropriate and lead to useful information. Values too close together do not allow sufficient variation in the response to be observed, and in this case, RSM will have a plateau. However, points that are at the extremes of a reasonable range will give poor responses that might not differ from each other, that is, RSM will depict a maximum response Hibbert Not all combinations of factor levels may be practical.
Sometimes the improper selection of levels leads to the depiction of maxima in RSM at the edges and the saddle. A clarification for the less applicability of the principle of uncertainty while selecting factor levels and justification of the need of a simple alternative for the same has been stated effectively by Vander Heyden et al.
Coded variables are used to represent EDs. The reasons he has stated for this practice is mathematical but also a practical use is that designs can be written independently of the particular factors under study. For designs where there are more than two levels, the values indicate the relative magnitude of the levels.
Note that this can only be done for continuous variables that can be set as predefined values Hibbert Various factors were chosen while the applications of design procedures during different purposes of pharmaceutical HPLC analyses are as represented in Figure 4.
Readers interested in gaining in-depth knowledge about the factors, selection of factors and specific references for the use of particular factor in analysis can refer the cross-citations of an article published by Dejaegher and Vander Heyden Various factors chosen while the application of design procedures during pharmaceutical HPLC analyses. The effect of selected factors has to be measured in terms of response which is in turn more essential to understand the chromatographic process.
This creates the main goal of optimization of responses in analytical chemistry with frequent objectives of maximizing sensitivity, minimization of the limit of detection. Another concern associated with HPLC is its relation to trade and optimum separation is desired with considerations such as time, cost, required measurement uncertainty and the ultimate applicability of analytical information.
Measurement of multiple responses at a time can be considered as a most important advantage of DoE and models developed that arrive at the desired overall optimum without extra experiments Hibbert Chromatographic responses as stated earlier can be quantitative responses such as peak areas, peak heights and qualitative chromatographic or electrophoretic parameters plate count, symmetry factor, RS and retention or migration times which are typically assessed during analysis Fabre Both qualitative and quantitative responses are taken into consideration in chromatographic analysis depending on the purpose Li et al.
According to experiments performed earlier, various responses can be selected as stated earlier. For a separation method, one should also consider one or more parameters describing the quality of the separation, such as, for example, the RS or the relative retention.
The evaluation of these separation parameters may also lead to the establishment of system suitability test SST limits as required by the ICH. When determining SST limits, other responses such as capacity factors or retention times, asymmetry factors USP tailing and a number of theoretical plates can also be studied Vander Heyden et al.
In conclusion, choosing a response during the application of DoE in chromatography depends on the purpose of analysis; the response may be simply drug content as a quantitative response or retention time as qualitative response while purpose is just the identification of some chemical components as stated by Destandau et al. The use of RS of the critical pair i. The thing to be remembered is that the success of getting the right chromatographic condition by DoE depends on the selection of responses Kumar et al.
Analytical researchers often deal with the predicaments of choosing an approach for ED for research. The decision taken is mostly based on the things which are known about the system, needs to be known, the available resources, situations and knowledge of specific EDs.
Although several situations in chromatographic research can be addressed with common design solutions, researchers lacking a strong background in statistical design must have to go through scattered literature sources.
As it is not possible for all researchers to get acquainted with the knowledge of all the available designs as well as to become the expertise to discriminate among potential EDs, it is usually difficult to decide abruptly about the type of design to be chosen. Even many of researchers do not always have access to experts in the field of ED who can recognize the characteristics of a problem that relate to the selection of a design.
Hence, the application of apparently refined statistical methods to the analysis of data acquired from poor selection of EDs may lead to unnoticed erroneous conclusions about the results Mark The oldest literature available for the selection of design which we came across during our literature search was by Olivero , who investigated problem-solving ability of an expert in the domain of ED for chemical research and embedded in a custom-written computer program named DXPERT.
The work led to the development of a computerized tool to help researchers in the preliminary evaluation of various ED classes for a given project. The tool is intended to provide advice in a way similar to an expert in the field, integrating knowledge and experience.
It should efficiently gather information about the project, use the information to rank the EDs according to suitability and provide help to the researcher. The scope of the software is the selection of appropriate ED types and does not include setting specific experimental parameters once an approach has been selected Olivero, Seshadri, and Deming Despite the use of the computer program the general criteria for the selection of a design have been discussed by Debrus et al.
When too many factors seem to affect the response i. In this category, a well-known design which has been applied in chromatography is the PBD Debrus et al.
The second category corresponds to optimization designs i. The EDs in this class are mainly full factorial i. The combined efforts will lead to the better understanding and hence the proper application of EDs as per the requirements. The main research goals of any analytical investigation are to optimize the desired response and to understand the underlying process.
After choosing an appropriate design for the chromatographic and thereby analytical investigation, various pre-chromatographic requirements need to be fulfilled as usual. For the evaluation of the critical chromatographic parameters, a mixed standard solution is needed; for an assay, standard and test solutions are prepared and need to be injected in the sequence as specified in the procedure accordingly Olivero, Seshadri, and Deming Replicate injections should be preferred, except if the time is restricted, to estimate the order of experiments; it has been stated that randomization is not necessary when one is primarily concerned with using screening designs with one observation per run Wheeler ; however, it is the opinion of the author from the literature review that the different experiments should preferably be carried out in a random order selected from a table of random order or generated by software to take into account uncontrolled factors likely to introduce a bias into the responses.
Randomization is essential if a center point is used. Quantitative peak areas, peak heights and qualitative chromatographic responses plate count, symmetry factor, RS and retention or migration times are typically measured during the tests Araujo and Brereton a. All the associated software packages today or manual statistical analysis past uses ANOVA to fit the data to select a model and to evaluate the two-factor interaction effects usually practical in chromatography Gilmour The statistical analysis of the selected responses and associated interpretation can be categorized as qualitative and quantitative Figure 5 , while for further convenience it can again be divided as numerical, graphical and calculations of percent errors sometimes.
Ways of statistical analyses and interpretations applied in the literature for chromatographic experimental designs. RSM was developed by Box and collaborators in the 50th century Bruns, Scarminio, and de Barros Neto , which led to the generation of response surface plots or curves. Response surface plots can be used to optimize a single response at ease, but when one needs to optimize multiple responses two to five responses or should not be very large in number at a time, it can be done by simply visual observation of the various response surfaces obtained for a particular single response respectively and overlapping them to find out the experimental region which is supposed to satisfy all the responses to be studied Sivertsen et al.
Qualitative interpretation of the chromatographic data can be done mostly using a response surface plot or curve. A response surface is a visualization for the predicted model equation usually quadratic.
The plot can be visualized for three or more variables only if one of the variables is set to a constant value; depending on the factors selected and the response to be optimized or studied, a response surface may vary as depicted in Figure 6 by Bezerra et al.
The figure states the role of response surface plots generated for a quadratic model during optimization of factors. The optimum response shown by the maximum point in the response surface can be within the experimental region as in Figure 6 A and B, while if there is a plateau for one of the variables, then the variation of that variable does not affect the system Figure 6 B.
Displacement in the initial design is needed if the maximum optimum point is outside the experimental region Figure 6 C. The overall performance characteristics of a column remain constant when this ratio is kept constant: the same maximum resolving power and the same shortest analysis time can be achieved.
Other subjects discussed are elevated temperature, column diameter, high-speed analysis, and monolithic columns. In the section on column chemistry, the silica-based stationary phases are described in great detail, including new developments such as waterwettable stationary phases and packings with embedded polar groups. An overview of commonly applied surface chemistries of packings used in reversed-phase applications is included. A separate discussion is dedicated to hybrid packings and zirconia-based packings.
Because the long-term reproducibility of an assay is of utmost importance in the pharmaceutical industry, the brief review of the reproducibility of stationary phases should be of great interest to the readers. As many modern chemical entities are polar compounds, hydrophilic interaction chromatography may be a suitable technique for these compounds.
Finally, a synopsis of what is currently understood about column selectivity in reversed-phase HPLC is provided. Non-robust SP procedures, poor techniques, or incomplete extraction are the major causes of out-of-trend and out-ofspecification results. The common SP techniques have been reviewed with a strong focus on tablets or capsules, as they are the primary products of the pharmaceutical industry. Detailed descriptions of SP methods for assays and impurity testing are provided with selected case studies of single- and multi-component products.
While SP techniques are well documented, few references address the specific requirements for drug product preparations, which tend to use the simple "dilute and shoot" approach.
More elaborate SP is often needed for complex sample matrices e. Both novices and experienced analysts can learn the usefulness of sample preparation techniques for the solid dosage forms. The "best practices" are described in the dilute and shoot approach, and the "tricks of the trade" in grinding, mixing, sonication, dilution, and filtration of drug products. Selected case studies of sample preparation for assays and impurity testing are used to illustrate the strategies, trade-offs, and potential pitfalls encountered during method development.
From the array, two orthogonal methods are selected to support subsequent stages of pharmaceutical development. One of these methods is optimized to separate all known related substances and excipients, using chromatographic optimization software such as DryLab. The other method is used to analyze pivotal lots of drug substance and drug product formulations to assure that the primary method continues to be viable for the separation of all relevant components.
Following finalization of drug substance synthetic routes and drug product formulation, the focus shifts to the development of robust and transferable methods for post-approval support at quality control units. It is important to remember during the final stage of method development that achievement of separation conditions is only one of the necessary parameters for successful method implementation.
Extensive studies to measure robustness and quantitative method performance are conducted to assure that the method performs as intended in quality control laboratories. It should be emphasized that successful method development requires extensive cooperation between the development laboratory and the receiving quality control laboratories.
Validation is a process required by law, and the concept is described by regulatory agencies in the guidance documents. The analyst performing method validation is responsible for interpreting the 6 S. AHUJA guidance into acceptable practices. Compounds that can be chromatographed at the same time as the target compound and do not interfere with the determination of the target compound.
Note that the compound cannot necessarily be extracted from the biological matrix in question although it may be. It is common practice, during the validation of a method for the analysis of a drug in biological fluids, to run a variety of other drugs so as to demonstrate interference or non-interference with the extracted drug.
However, these other drugs are generally analyzed as solutions in solvents rather than in biological fluids. Methods in which the drugs are analyzed as solutions in solvents are generally not listed in the monographs. However, these procedures can be found using the "simultaneous" feature of the database. In these instances, the chromatographic procedure will be valid, but the extraction procedure from the biological fluid may not necessarily be valid for this drug.
However, in a number of cases, the matrix is associated with various key words that can be used to narrow the search. For example, the term "formulations" has the key words tablets, creams, ointments, and injections associated with it.
Thus, to find references applicable to tablets, search first for formulations under the matrix heading and then tablets under the key word heading. Note that the term "bulk" is used instead of "raw materials. Matrix Term bile blood bulk CSF dialysate formulations microsomal incubations milk perfusate reaction mixtures saliva solutions tissue urine Associated Key Word plasma, serum, whole blood capsules, injections, tablets, creams, ointment, etc. Solutions containing compounds should be protected from light and silanized glassware should be used, unless you have good reason to believe that these precautions are not necessary.
A number of excellent texts12"14 discuss good working practices and procedures in HPLC and these should be consulted. Details of solution preparation are generally not given. It should be remembered that the preparation of a dilute aqueous solution of a relatively water-insoluble compound can frequently be made by dissolving the compound in a small volume of a water-miscible organic solvent and diluting this solution with water.
It is also assumed that safe working practices are observed. In particular, organic solvents should only be evaporated in a properly functioning chemical fume hood, correct protective equipment should be worn when dealing with potentially hazardous chemical or biological materials, and waste solutions should be disposed of in accordance with all applicable regulations.
A number of solvents used in HPLC are particularly hazardous. For example, benzene is a human carcinogen;15 chloroform,16 dichloromethane,17 dioxane,18 and carbon tetrachloride19 are carcinogenic in experimental animals; and DMF20 and MTBE21'22 may be carcinogenic. Organic solvents are, in general, flammable and toxic by inhalation, ingestion, and skin absorption. Sodium azide is carcinogenic and toxic and liberates explosive, volatile, toxic hydrazoic acid with acid.
Sodium azide can form explosive heavy metal azides, e. Merck Shandon MetaChem E. Merck E. Many other companies supply these pieces of equipment. Asahi Chemical Industry Co. Baker Varian Associates, Inc.
Waters Associates, Inc. Daicel Chemical Industries, Ltd. Whatman Chemical Separation Co. Advanced Separation Technologies, Inc. Alltech Associates, Inc. Merck Shandon Scientific, Ltd. GL Sciences Inc. Merck Varian Associates, Inc. Rainin Instrument Co. Applied Biosystems Waters Associates, Inc. Perkin-Elmer Waters Associates, Inc. Analtech Supelco, Inc. Beckman Instruments, Inc. Phenomenex, Inc. The top drugs. American Druggist Feb. Helrich, K.
Budavari, S. Lednicer, D. Snyder, L. Lawrence, J. Lewis, R. Reference 15, pp. Reference 15, p. Belpoggi, R; Soffritti, M. Methyl-tertiary-butyl ether MTBE -a gasoline additive—causes testicular and lympho-haematopoietic cancers in rats.
Health , 11, Mehlman, M. Dangerous and cancer-causing properties of products and chemicals in the oil refining and petrochemical industry: Part XV. Lunn, G. Gilomen, K. Detoxification of acetonitrile—water wastes from liquid chromatography.
Improved resolution of proteins is accomplished with a new core-shell particle morphology which minimizes protein band broadening that occurs during diffusion in and out of the core-shell particle. Effective chiral separations have become increasingly important to the pharmaceutical and biopharmaceutical industries.
The rapid introduction of optically active medicinal drugs, along with increasing government regulation, necessitates that rapid, sensitive, and reliable stereochemical methods be devised for their analysis.
Chiral chromatography is by far the most powerful and sensitive analytical technique for resolving enantiomers. The Significance of String Professor of Anthropology Bruce Hardy makes headlines for his study on the cognitive abilities of Neanderthals. Mind of a Writer A senior English major talks with her advisor about his philosophy on creative writing and teaching. When pump refills, this energy is released and a smooth pressure pulsation result. Their use is recommended in ion-exchange chromatography using buffered aqueous phase.
Septum injector b. Stop flow septum less injection c. Rheodyne injectors Micro volume sampling valve operation of a Sampling loop. Few Analytical columns Length — cm Internal diameter — 6 mm or more.