Analytical Aspect of Quality Control and Quality assurance

1. Analytical Aspect of Quality Control and Quality assurance For pharmacy students By Dr. Abdalla Ahmed El shanawany Professor of Medicinal Chemistry Vice Dean of Faculty of Pharmacy Zagazig University 2010

2. Chapter 1: Drug registration and assessment 1.1. Summary of particulars 1.2. Chemical and pharmaceutical documentation 1.3. Reports of Experimental and biological studies 1.4. Report on Clinical Studies 1.5. Company profile • Chapter 2: The Analytical Problem 2.1. Sampling/Sample Handling 2.2. Experimental errors 2.3. Choice of methods of an analysis 2.4. Statistics of data analysis 2.5. Validation of analytical procedure

3. Chapter 3: Drug stability and degradation product • 3.1. Chemical purity and its control • 3.2. International pharmacopoeia and official monograph • 3.3. Radiopharmaceutical • 3.4. Stability indicating assay • Chapter 4: Function group analysis • 4.1. Classical analysis • 4.2. Instrumental analysis • 4.2.1. Spectral methods • 4.2.2. Electro analytical methods • Chapter 5: Automation in pharmaceutical analysis • 5.1. Flow injection analysis • 5.2. HPLC • 5.3. Gas chromatography. • 5.4. Mass spectroscopy

4. Chapter 6: Determination of active ingredients in different dosage forms and in biological fluids 6.1. Determination of active ingredients in tablets 6.2. Determination of active ingredients in capsules • . 6.3. Determination of active ingredients in semisolid 6.4. Determination of active ingredients in eye drops 6 5. Determination of active ingredients in injection 6.6. Determination of active ingredients in Suppositories. • 6.7. Determination of active ingredients in aerosols inhalation • 6.8. Radioimmunoassay • Chapter 7: Quality assurance of pharmaceuticals • 7.1. Good Manufacturing Practice G.M.P • 7.2. National and international organization • 7.3. Departments in pharmaceutical companies • 7.4. ISO and BSI

5. Intended Learning Outcomes of Course (lLOs) A -Knowledge and Understanding • Chemical QC/QA is only a part and aspect of total QC/QA that should go hand in hand with physical and biological aspects and all aspects should work in perfect synchronization within process control, validation and other aspects of G.M.Ps. • That organization of data and documentation coupled with a working knowledge of relevant statistical methods is mandatory B- Intellectual Skills • Should be able to choose and develop suitable analytical methodology to suit the purpose at hand so as to face various QC/QA settings e.g.; raw material/ single component/partially degraded dosage forms/ multicomponent dosage forms . • -Given the chemical structure of the ingredients selection of analytical procedures should be based on a hybrid methodology basis.

6. C- Professional and Practical Skills - To be able to apply previously known analytical methods to the area of drug analysis D- General and Transferable Skills - Work effectively as part of a team to collect data and/or to produce reports and presentations. - The capability to analyze and find an effective solution for a given complex problem.

7. Drug registration and assessment • Any pharmaceutical product before it is made available to the market needs evaluation and registration. • Product licenses are required for the manufacture of all medicine, for sale and supply for import and export. Also animal test and clinical trial certificate are required. • All licenses and certificates are issued by the appropriate licensing authority which is department of health and social security, medicines division. • A guideline to provide manufacturers with information concerning documentation to be submitted for approval and registration of pharmaceutical products for human use is presented.

8. Application form for drug registration • 1. Summary of particulars General information relating applicant, the license, and the product • description and name of the product, dosage form, and suggested trade name physical properties of active constituent recommended clinical use, dose, route of administration, place of manufacture, sale, OTC or by prescription and supply

9. 2. Chemical and pharmaceutical documentation • 2.1. Chemical Data on active ingredient • Nonproprietary or generic name, molecular formula, chemical name, structure, physicochemical properties, synthesis, stability studies, analytical specifications and test methods, key raw materials, key intermediates, degradation profile, including analytic procedures used in the detection and determination of byproducts.

10. 2.2. Formulation Report (dosage forms) • Data on Composition • Complete qualitative and quantitative composition of the finished product, including quality specifications (requirements) and control methods. Active ingredient(s) present in the form of salts or hydrates shall be described quantitatively by their total mass and by the mass of the active moiety or moieties of the molecule. • Data on Packaging Materials (Container and Closures) • Detailed information is required about the packaging material, which comes in to such contact with the drug Package labeling includes package leaflet, label on the immediate container, and outer wrapper or carton. • The package leaflet should consist of factual and scientific information consistent with the application. A leaflet must bear adequate information for use.

11. 2.3. Analytical Report • The manufacturer should submit: • Quality specifications (requirements) and analytical procedures for the dosage form • 2.4. Stability Report • The stability report should consist of stability data sheet and a summary. The tests for stability at each sampling period should be related to the formulation and to the storage condition and the study should include tests.

12. 3. Reports of Experimental and biological studies. (Pre clinical studies) • 3.1. Animal Pharmacology • The manufacturer should furnish a summary of the observations and conclusions Showing the animal species, number of animals, doses, information route of administration, concise description of the methodology, results, conclusions and an overall evaluation of the pharmacodynamic and pharmacokinetics properties of the drug based on the findings in laboratory animals or in invitro systems. • 3.2. Pharmacodynamics • Studies providing the primary basis for clinical trials of the drug, mechanism of action, minimum effective dose emphasizing adequate description of dose-effect relationships that produce pharmacological responses in each species of animal investigated.

13. 3.3. Pharmacokinetics • Pharmacokinetics Studies concerning absorption, distribution, metabolism, enzyme induction, enzyme inhibition, and excretion. • 3.4. Toxicological Data • Summary of toxicological studies preferably should be presented in tables which indicate species, number, sex, age, weight and strain of animals, information on dosage formulation, route(s) of administration, treatment regimen duration of treatment, parameters evaluated, significant observations and conclusions. • 3.5. Microbiology (for anti-microbial agents only) • Summaries of all microbiologic studies, including methods used together with a discussion and evaluation of the results. Cumulative MICtables are highly desirable.Under each of the following headings, detailed description and analysis based on the available completed microbiologic studies should be provided.

14. 4. Report on Clinical Studies • Drug clinical trials shall be conducted in institutions legally certified for drug clinical trials. If a clinical trial has to be conducted by an institution not yet certified, a special approval by the State Food and Drug Administration should be obtained. The investigator responsible for a drug clinical trial shall, in accordance with the relevant provisions, timely report adverse events occurred in the process of the clinical trial to the State Food and Drug Administration. • 4.1. Clinical Pharmacology: • Pharmacodynamics • Intended drug effect, methodology, number of volunteers, age groups, healthy and sick, optimal dose Studies of single and multiple dose, And the effect of drugs on various organic functions, mechanism of action, studies on the relationship of between dose of drug and response in patient, drug interaction studies, etc.

15. Pharmacokinetics • Studies on the absorption, distribution plasma concentration, protein binding, half- life, biotransformation, kinetics, elimination of the drug and also report on metabolic studies. Physicochemical properties which may act on absorption and distribution should be stated. The methods of assay or determination should be specified. • Reports on combined preparations, in addition to details on their individual components, should also give information on the pharmacological properties of the particular combination that is being considered. • 4.2. Bioavailability Report • Bioequivalence report is required for those oral dosage forms of drugs which are known to pose bioavailability problem, where systemic absorption is a requirement for their efficacy.

16. 4.3. Clinical Trials • The summary should concisely set out the clinical properties of the drug. Special emphasis should be put on that documentation which lends support to the cited indications. • It should provide information on patient population number of patients, dosage formulation, doses, methods, etc; and also give an overall discussion and evaluation of the safety, efficacy, dosages, adverse reactions and contraindications of the drug based on the findings of available completed clinical trials, and conclusion providing a discussion of the benefits and risks of the drug under the conditions of use recommended. • The conclusion should at least consider the following points: • comparison of the expected clinical benefits with possible adverse effects, and assessment and comparison of the benefit/risk ratio of the drug in relation to related drugs or others used as standards in controlled clinical trials, etc.

17. 5. Company profile • Documents to be supplied by the manufacturer. • 5.1. Back ground information • The manufacturer should submit background information about the company indicating, Year of establishment, Development since establishment, , Total working force, Ownership, • 5.2. Production Unit • The manufacturer should submit information on the production unit and should also indicate whether the company has the following; • GMP procedure, Master file and batch production record system • Product specifications, Standard operation manual, List of pharmaceuticals produced by the manufacturer (specify those which are the manufacturer's innovation). • 5.3. Quality Control Unit • The manufacturer should state: • A. Whether it performs, Raw & packaging materials Q.C, • In-process Q.C., and Finished product Q.C. • B. The types of Q.C. tests performed; physicochemical tests, Sterility • test , Pyrogen test, acute toxicity test, Biological • assay, Microbiological assay etc. • C. Whether it has Good laboratory Practice (GLP) Procedure. • D. The major Q.C. Instruments available. • E. Qualification and experience of Q.C. personnel

18. 5.4. Supply system • The manufacturer should give information on its supply system indicating whether it has at least the following: • Cold storage facilities, Separate stores for raw materials, packaging materials, labels etc., Separate room for weighing raw materials, Quarantine for raw materials, finished products, etc,, procedure for supplies control. • 5.5. Research and Development Unit (R and D) • The manufacturer should give detailed information on at least the following major points: • The year R and D was initiated. • Qualification of the personnel engaged in R and D activities • Major research areas and achievements attained. • Affiliation with other institutes (if there is any) • 5.6. Product Registration and marketing Experience of the manufacturer • The manufacturer should submit full information on its marketing experience and Registration status of its products indicating: • List of countries to which it exports most of its products. • List of countries in which its products are registered

19. Chapter 2: Analytical problem 2.1 Sampling/Sample Handling 2.2 Experimental errors 2.3 Choice of methods of an analysis 2.4 Statistics of data analysis 2.5 Validation Of analytical procedure. • There are three basic activities involved in solving an analytical problem: 1. Collection of the applicable sample 2. Preparation of the sample for analysis 3. Analysis using appropriate methods.

20. 2.1 Sampling/Sample Handling • Sample is a representative portion selected from the bulk. • One of the most common causes of differing analytical results can be traced back to non representative ness of different samples. • It is easy to anticipate that this could occur during the conduct of a multi-lab study, and it is the responsibility of the study director to ensure sample homogeneity. • When a significant difference in results occurs between laboratories that have analyzed supposedly the same sample, a serious problem may arise Involving questions of competence and credibility. Many of thesesituations can be avoided if samples are collected according to a rationalplan that gives some assurance that the sample delivered to thelaboratory represents the composition of the parent lot. • For example when the U.S. Environmental Protection Agency conducted studies during remediation projects to determine the sources of variation in the sampling and analytical procedures, and found that the amount of variation from sampling was approximately 80% of the total variation while the amount of variation from the analytical procedures was 20%. The important point in this example is to show that sampling error can play a very significant part in the overall error in the analytical system.

21. Analytical sample • Analytical sample is a small portion selected from the sample. • The best analysis can give misleading information if the test portion analyzed does not represent the sample or the lot from which it was taken. Distortions introduced at this point will carry through the analysis and adversely affect the final results and the conclusions drawn from them. • A homogenous material, such as a liquid solution, readily yields a representative sample. • Heterogeneous materials, such as powdered materials and granules always exhibit segregation of the particles during handling .and exhibit a range of particle size, and the flow properties of the powder depend upon the particle size distribution

22. Two techniques for obtaining good sample from powderedmaterial: • Long pile method The gross sample is arranged in long pile, and then separated into two equal piles using a shovel and throwing alternative shovels to opposite sides. One half is discarded and the other again separated in the same manner until the required sample size is obtained. • 2. Coning and quartering • The powder is deposited on a flat surface by shovel, and then the cone is flattened and divided into four equal parts by forming two perpendicular diameters. The material from two diagonally opposed quarters is combined and formed into another cone, that material in the other two quarters being set aside .the coning and quartering process is continued until a sample of the requisite size is obtained.

23. When the populations consist of discrete units, such as drums of solvent, package of ampoules, bottles, etc., there are two general sampling approaches • Random sampling The units are numbered serially .all numbered have an equal number of digits. Then numbers are selected in some random manner from the random table, and the corresponding units are taken for the sample. It is an effective way to obtain unbiased, representative samples, but it is apt to be laborious and time consuming. • Systematic sampling A more widely used time saving technique in which every nth unit is selected to constitute the sample. The selection of n is of course critical, as the interval between selected units must not correspond to any periodicity in the population. It is biased to some extent.

24. Sample size • The n plan should be used only when the bulk is homogenous and the sample can be withdrawn from any part of the container n= √N • where n is the sample size, N is the quantity to be sampled • The p plan • For homogenous and the sample for identity P= 0.4√ N • The r plan For heterogonous and vegetable drug as raw materials r= 1.5√ N, where r is the sample size. N is the quantity to be sampled • There are generally two choices specify the manner in which an analytical sample should be taken. • 1. Preparation of a composite laboratory sample (if multiple units are submitted for analysis) • 2. Examination of individual units. • A composite laboratory sample is one in which the individual units, or Representative portions of units are mixed to form a uniform mixture. Portions are then taken from the composite for analysis Compositing can Best be used when homogeneity is not a significant problem concern. • Compositing saves analytical time and in some types of contract testing it May be the procedure specified.

25. Compositing is not the procedure of choice when there is a chance that an individual unit that constitutes a public health or safety threat will not be detected (there are some exceptions) or where a unit at or outside tolerance will not be detected because of matrix dilution. • Multiple unitlaboratory sampling is indicated when the possible range of Values among individual units are considered significant or it is desirable to establish the variability of the lot. • However, the reliability of the result generally increases with the square root of the number of samples analyzed. For this reason, analyses of multiple samples always are preferred over single samples since single samples give no information on the homogeneity of the lot that was samples

26. Sample Preparation for Analysis • Every type of material that is to be prepared for analysis presents its own practical difficulties. The requirements for suitable sample preparation are dictated by the consistency and the chemical characteristics of the analyte and the matrix, and by the distribution of the analyte in the sample. Even seemingly homogeneous materials such as liquids may be subject to Sedimentation or stratification. • Single phase liquids can generally be mixed, stirred, shaken, • Dry particulate materials can be reduced in volume by use of a splitter, A variety of implements and machines are available for sample disintegration, such as mills, grinders and cutters. Care in their use is necessary to prevent loss of dust or change in composition through the partial separation of components. In particular, care must be taken to prevent dust or related substances as carry over, from contaminating the laboratory space and any subsequent samples that are ground, and of course, the grinding equipment must be meticulously cleaned between samples. Screening can be used to improve the efficiency of particle size reduction, followed by mixing to attain homogeneity.

27. Glass containers and laboratory apparatus can adsorb certain materials and may require surface treatment. • Plastic containers can retain contaminants, such as animal hairs, while the rest of the sample is transferred with apparent ease. In other words, validation of a method of analysis includes, most certainly, validation of the method of sample preparation and storage. • Loss or gain of moisture during manipulation can be a problem. Loss can be minimized by keeping samples covered with plastic or aluminum foil. A cold product can be protected from gaining moisture by allowing the sample to come to room temperature before preparation begins. • When volatile organic constituents are present in samples, sample manipulation may not be possible, or may be severely restricted, in order to prevent their loss.

28. Experimental Errors • Random (in determinant) and systematic (determinant) errors • The term error as used here refers to the numerical difference between a measured value and the true value. For example, the % composition of a standard sample certified by the national Bureau of standards may be treated as correct in evaluating a new analytical method; differences between the standard values and the results obtained by the new method are then treated as error in the latter. • One can attempt to minimize errors but cannot eliminate them completely • Random errors small fluctuations introduced in nearly all analyses. Arise from variation of external conditions over which the observer has no control For example, repeated measurements of the same property often differ even if they are performed on a single instrument that is calibrated and operated properly.

29. Systematic errors Systematic errors cause the results to vary from the correct value in a predictable manner and can often be identified and corrected. An example of a systematic error is improper calibration of an instrument. The measurement lacks accuracy. It is even possible that repeated measurements with this broken instrument will give reproducible results (high precision), but every one of them will deviate from the true value (low accuracy). • Systematic errors have been classified as personal, instrumental and methodic • 1. personal errors: Are those due to the carelessness of the observer and include such things as misreading a burette or overshooting the end point, or loss in weight during washing and filtration, and mathematic error in calculations. • 2. Instrumental error: Error due to the instruments themselves and include the use of uncalibrated equipments e.g. Weights, burettes, pipette, flasks. • 3. Methodic: Errors are those inherent in the method itself, incomplete reaction or side reaction, instability of the reaction product or impurities in the reagents.

30. Minimization of the errors • 1-Calibration of the equipment and application of correction factor. All of the equipments should be corrected and appropriate correction factor applied. • 2-Use of blank experiments Carrying out a separate determination without the sample under the same experimental condition to overcome the effect of impurities introduced through reagents, solvents and vessels. • 3. Standard addition method • A known amount of the constituent being determined (standard) is added to the sample which is then analyzed for the total amount of the constituent present. The difference between the analytical results for the sample with and without the added standard gives the recovery of the amount of added constituent. • 4. Use of internal standard It is used in HPLC and GC; fixed amount of the suitable standard is added with different amount of the sample to minimize the error during introduction of the sample.

31. Choice of methods of an analysis The pharmacist who has need for analytical data usually finds himself faced with an array of methods which could be used to provide the desired information. Unfortunately, there are no generally applicable rules that can be applied; the choice of method is thus a matter of judgment. Such judgment is difficult, and the ability to make it will come only with experience. • Factors plays an important role in the selection of the analytical methods of analysis. • 1-Concentration range of the sample to be determined. if for example the element present to the extent of a few ppm as impurities or degradation products it is not suitable to use volumetric or gravimetric methods and use other sensitive methods as HPLC or spectrophotometry. On other hand if the analyte is a major component of the sample the classical method may be preferable. • 2-Degree of accuracy and precision required The accuracy and precision required are of vital importance in the choice of an analytical method and its performance, especially in small and vital substances as hormones. • 3- Different components which are present in the sample The chemical structure of these substances should be known because they may interfere with the method, since the analysis is based on reactions or properties share by several compounds, in this case prior separation or selective method should be used.

32. 4-Physical and chemical properties of the substance The analyst should know the state of the substance at ordinary conditions and whether losses by volatility, and whether or not the sample is hygroscopic or efflorescent and what sort of treatment is sufficient to decompose or dissolve the sample without loss of the analyte. 5-Number of the sample to be analyzed If there are many considerable times can be expended in calibrating instruments, preparing reagents, assembling equipments, the cost of these operations can be spread over the large number of analyses. On other hand, if a few samples are to be analyzed, a longer and more tedious procedure involving a minimum of these preparatory operations may actually prove to be the wiser choice from the economic standpoint. 6-Availability of the instruments and equipments. plays an important role in the selection of the analytical method.

33. Testing the procedure Once a procedure for an analysis has been selected, the problem usually arises as to whether the method can be employed directly without testing. The answer depends upon a number of considerations. If the procedure chosen has been the subject of a single or a few literature references Or a major modification of a standard procedure is undertaken Or an attempt is made to apply it to a type of sample different from that for which it was designed; a preliminary laboratory test is advisable • What are the means by which a new method or a modification of an existing method can be tested for reliability? • 1-Analysis of standard sample The best technique for evaluating an analytical method involves the analysis of one or more standard samples whose composition with respect to the compound of interest is reliably known. For this technique to be of value, it is essential that the standards closely resemble the sample to be analyzed with respect to both the concentration range of the analyte and the overall composition. Standard may be purchased from sources such as national Bureau of standards. Or synthesized from weighed quantities of pure compounds.

34. Analysis by other methods The result of an analytical method can sometimes be evaluated by comparison with some entirely different method. It should be based on chemical principles that differ considerably from that one under examination. Comparable result from the two methods, serve as presumptive evidence that both are yielding satisfactory results; no significant difference between the two methods. • Standard addition to the sample Standard addition method, in addition to being used to analyze the sample itself, the proposed procedure is tested against portions of the sample to which known amounts of the analyte have been added. The effectiveness of the method can be established by evaluating the extent of recovery of the added quantity. The standard addition method may reveal errors arising from the method of treating the sample or from the presence of the other compounds

35. Rejection of Data • Sometimes a person performing measurements is faced with one result in a set of replicate s which seems to be out of line with others, and he then must decide whether to exclude this result from further consideration. • For example, after making only five measurements of our drug, you obtain the following results (in grams): 8.148 8.145 8.156 8.149 8.177 • The last measurement seems a bit off, and you may be tempted to throw it out of the set. However, you must never throw out a result from a data set unless you have a statistical reason to do so. • Statistically speaking, we are asking the question: does the measurement of 8.177 grams belong to the same normal distribution as the other four measurements? • . If we had a very large data set, then we could calculate x ± 2sx , and then determine if the measurement in question falls outside the confidence interval. However, our data set is very small (N < 10), so that the standard deviation alone is not a good criterion for rejection. • Statisticians have devised many rejection tests for the detection of non-random errors. We will describe only one - the Q test - which works well in cases where 3 < N < 10.

36. In order to test the value of 8.177 grams, we must calculate the so-called Qcalc value for this observation. • Q calc  absolute value of the gap between the suspect value and the value closest to it / range of values • To calculate Qcalc in our example, we display the data in increasing order of numerical value, and then identify the suspect value and the value that is closest to it: 8.145 8.148 8.149 8.156 8.177 Then, Q calc = 8 .177 - 8.156 / 8. 177 - 8 .145 = 0 .66 We now compare this Q calc with a critical value Q c. If Q calc > Q c, then the observation may be rejected. If Q calc < Q c, then we must keep the observation. The Qc value depends on the confidence level and the number of observations in your set. A partial list follows: N Q c (90% confidence) 3 0.94 4 0.76 5 0.64 6 0.56 7 0.51 8 0.47 9 0.44 10 0.41 Returning to our example, where N = 5, we see that Q calc = 0.66 is indeed greater than QC = 0.64. Hence, we are justified in rejecting the observation. However, you must indicate in your report that the Q test was used at a 90 % confidence interval.

37. Testing for significance Suppose that a sample is analyzed by two different methods, each repeated several times and the mean values obtained are different. Is the difference between the two values significant? We use null hypothesis which states that the two means are identical and the student, s t test gives a yes or no answer to the correctness of the null hypothesis with a certain confidence. Procedure: • Suppose a sample has been analyzed by two different methods; yielding means X-1 ,and x- 2 and standard deviation s1 and s2 ; n1, and n2 are the number of the individual results obtained by the two methods. • First calculate t • x1- - x-2 • t =------------------ • Sp√ 1/n1 + 1/n2 • Where • (n1-1) s12 + (n2 -1) s22 • Sp (pooled sd) = √ ------------------------ n1 +n2 -2 • sec., find t tabulated at degree of freedom n1+n2 -2 and at the desired probability if the t value in the table less than the calculated t , the null hypothesis incorrect and there is significant difference between the two means.

38. F test (variance ratio) • To decide whether the difference between s1 and s2 is significant • F = S12/ S22 F > 1 The larger s in the numerator • Example Aspirin sample was analyzed by two different methods and the following results were given Method 2 method 1 X-2 72.34 x-1 72.44 S2 0.1 s1 0.12 n2 5 n1 4 Answer t tabulated at degree of freedom n1 +n2 – 2 = 7 2.365 Sp = 0.109 • t calculated = 1.36 • The null hypothesis is correct and the difference is not significant

39. Validation Of the analytical procedure • Validation of an analytical method is the process by which it is established, by laboratory studies that the performance characteristic of the method meet the requirements for the intended analytical applications. • Validation implies one is able to document that a process is correct or is suited for its intended use. The difference between validation and verification is that validation is ensuring "you built the right product" and verification is ensuring "you built the product right Verification is usually an internal quality process of determining compliance with a regulation, standard, or specification • The parameters that should be considered during the validation of analyticalprocedures:

40. 1. Specificity is the ability to measure accurately and specifically the analyte in the presence of components that may be expected to be present in the sample matrix. • An investigation of specificity should be conducted during the validation of identification tests, the determination of impurities and the assay. The procedures used to demonstrate specificity will depend on the intended objective of the analytical procedure • 1.1. Identification • Suitable identification tests should be able to discriminate between compounds of closely related structures which are likely to be present. The discrimination of a procedure may be confirmed by obtaining positive results (perhaps by comparison with a known reference material) from samples containing the analyte, coupled with negative results from samples which do not contain the analyte. In addition, the identification test may be applied to materials structurally similar to or closely related to the analyte to confirm that a positive response is not obtained. • 1.2. Assay and Impurity Test(s). • Critical separations in chromatography should be investigated at an appropriate level. For critical separations, specificity can be demonstrated by the resolution of the two components which elute closest to each other.

41. 1.2.1 Impurities are available • For the assay, this should involve demonstration of the discrimination of the analyte in the presence of impurities and/or excipients; practically, this can be done by spiking pure substances with appropriate levels of impurities and/or excipients and demonstrating that the assay result is unaffected by the presence of these materials (by comparison with the assay result obtained on unspiked samples). • For the impurity test, the discrimination may be established by spiking drug substance or drug product with appropriate levels of impurities and demonstrating the separation of these impurities individually and/or from other components in the sample matrix. • 1.2.2 Impurities are not available specificity may be demonstrated by comparing the test results of samples containing impurities or degradation products to a second well-characterized procedure e.g.: pharmacopoeias method or other validated analytical procedure. Peak purity tests may be useful to show that the analyte chromatographic peak is not Attributable to more than one component (e.g., diode array, mass spectrometry).

42. 2. Linearity • It may be demonstrated directly on the drug substance (by dilution of a standard stock solution) and/or separate weightings' of synthetic mixtures of the drug product components, using the proposed procedure. • Linearity should be evaluated by visual inspection of a plot of signals as a function of analyte concentration or content. If there is a linear relationship, test results should be evaluated by appropriate statistical methods, for example, by calculation of a regression line by the method of least squares. In some cases, to obtain linearity between assays and sample concentrations, the test data may need to be subjected to a mathematical transformation prior to the regression analysis. • Y = mX + b where Y is test result, m slope, X concentration, b intercept • m= Σxy - Σx Σy/n Σ x2 - (Σ x)2 /n • b= y- - mx- σx • Correlation coefficient (r) = m ---- σy • r equal 1 or nearly 1

43. For the establishment of linearity, a minimum of 5 concentrations is recommended. Chromatogram of different concentration of norfloxacin from 0.1 – 0.8 mg% and the same concentration of salicylic acid 2 mg % at 274 nm

44. A calibration curve plot showing limit of detection (LOD), limit of quantification (LOQ), dynamic range, and limit of linearity (LOL).

45. 3. Range • The range of an analytical method is the interval between the upper and lower levels of the analyte which could be determined with an acceptable degree of linearity, accuracy and precision. • The following minimum specified ranges should be considered: for the assay of a drug substance or a finished (drug) product: normally from 80 to 120 percent of the test concentration; for content uniformity, covering a minimum of 70 to 130 percent of the test concentration, unless a wider more appropriate range, based on the nature of the dosage form (e.g., metered dose inhalers), is justified; for dissolution testing: +/-20 % over the specified range; e.g., if the specifications for a controlled released product cover a region from 20%, after 1 hour, up to 90%, after 24 hours, the validated range would be 0-110% of the label claim. • For the determination of an impurity: from the reporting level of an impurity 1 to 120% of the specification

46. 4. ACCURACY Accuracy is the degree of agreement between the experimental result and the true value. or most probable value. It expresses the correctness of the result. • Accuracy should be established across the specified range of the analytical procedure. • Measures to express accuracy • A. Absolute error (d) • The difference between the analytical result and the true value • d= x-µ where x observed value, µ true value • Absolute error has no significance when separated from true or observed value .so we use relative errors. • Example • Atomic absorption analysis of As+3 and pb+2 in a sample yield the following results • As+3 = 600 µg.ml-1 d = 5 µg. ml-1 • pb+2 = 9 µg.ml-1 d = 0.3 µg.ml-1 • From absolute error As+3 results is less accurate than pb+2 results but is not true as we see from relative error. • B.Relative error (E rel) • E rel = d/µ .100 • E rel As+3 = 5/600 x100 =0.83% E rel pb+2 = 0.3/9 x100 = 3.3 % • From the aforementioned, it is obvious that As+3 results is more accurate, although it has larger absolute error. • C. Recovery % (Relative accuracy) • = x/µ .100 = amount found/ amount claimed or calculated .100

47. Several methods of determining accuracy are available: • For Drug Substance • a) Application of an analytical procedure to an analyte of known purity (e.g. reference material); Comparison of the results of the proposed analytical procedure with those of a second well-characterized procedure, the accuracy of which is stated and/or defined. • For Drug Product • a) Application of the analytical procedure to synthetic mixtures of the drug product components to which known quantities of the drug substance to be analyzed have been added; • b) In cases where it is impossible to obtain samples of all drug product components, it may be acceptable either to add known quantities of the analyte to the drug product or to compare the results obtained from a second, well characterized procedure, the accuracy of which is stated and/or defined For Impurities (Quantization) • Accuracy should be assessed on samples (drug substance/drug product) spiked with known amounts of impurities. • In cases where it is impossible to obtain samples of certain impurities and/or degradation products, it is considered acceptable to compare results obtained by an independent procedure. It should be clear how the individual or total impurities are to be determined e.g., weight/weight or area percent, in all cases with respect to the major analyte. • Accuracy should be assessed using a minimum of 9 determinations over a minimum of 3 concentration levels covering the specified range (e.g. 3 concentrations /3 replicates each of the total analytical procedure). • Accuracy should be reported as percent recovery by the assay of known added amount of analyte in the sample or as the difference between the mean and the accepted true value together with the confidence intervals.

48. Examples of Precision and Accuracy: Low AccuracyHigh Precision High AccuracyLow Precision High AccuracyHigh Precision

49. 5. PRECISION • Precision is the degree of agreement among a series of measurements of the same quantity; it is a measure of the reproducibility of results rather than their correctness • Measures to express precision • standard deviation (s) • Is calculated by using equation 1, where Σ represents summation, xi represents each of the individual analytical results, a; is the average of the results, and N is the number of replicate assays. • The standard deviation is a popular estimate of the error in an analysis because it has statistical significance whenever the results are normally distributed. Most analytical results exhibit normal (Gaussian) behavior, following the characteristic bell-shaped curve. If the results are normally distributed, 68.3 percent of the results can be expected to fall within the range of plus or minus one standard deviation of the mean as a result of random error.

50. Chromatogram of the same concentration of Norfloxacin; (a) 5 mg% and the same concentration of Salicylic acid, (d) 2 mg% id at 274 nm.