Sample Preparation Composite and Replicate Strategy for Assay of

Nov 12, 2014 - In pharmaceutical analysis, the results of drug product assay testing are used to make decisions regarding the quality, efficacy, and s...
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Sample Preparation Composite and Replicate Strategy for Assay of Solid Oral Drug Products Brent Harrington,*,† Beverly Nickerson,*,‡ Michele Xuemei Guo,‡ Marc Barber,§ David Giamalva,⊥ Carlos Lee,‡ and Garry Scrivens§ †

Pfizer Worldwide Research and Development, Statistics, 558 Eastern Point Road, Groton, Connecticut 06340, United States Pfizer Worldwide Research and Development, Analytical Research and Development Department, 558 Eastern Point Road, Groton, Connecticut 06340, United States § Pfizer Worldwide Research and Development, Analytical Research and Development Department, 674 Ramsgate Road, Sandwich, Kent CT13 9NJ, United Kingdom ⊥ Pfizer Consumer Healthcare, Analytical Development, 1121 Sherwood Avenue, Richmond, Virginia 23220, United States ‡

ABSTRACT: In pharmaceutical analysis, the results of drug product assay testing are used to make decisions regarding the quality, efficacy, and stability of the drug product. In order to make sound risk-based decisions concerning drug product potency, an understanding of the uncertainty of the reportable assay value is required. Utilizing the most restrictive criteria in current regulatory documentation, a maximum variability attributed to method repeatability is defined for a drug product potency assay. A sampling strategy that reduces the repeatability component of the assay variability below this predefined maximum is demonstrated. The sampling strategy consists of determining the number of dosage units (k) to be prepared in a composite sample of which there may be a number of equivalent replicate (r) sample preparations. The variability, as measured by the standard error (SE), of a potency assay consists of several sources such as sample preparation and dosage unit variability. A sampling scheme that increases the number of sample preparations (r) and/or number of dosage units (k) per sample preparation will reduce the assay variability and thus decrease the uncertainty around decisions made concerning the potency of the drug product. A maximum allowable repeatability component of the standard error (SE) for the potency assay is derived using material in current regulatory documents. A table of solutions for the number of dosage units per sample preparation (r) and number of replicate sample preparations (k) is presented for any ratio of sample preparation and dosage unit variability.

A

dosage units in order to generate an assay value representative of the entire batch of product. The average value of the replicates is typically defined as the reportable value. Little or no guidance is given in regulatory documents to define the number of replicates and number of units in a composite that is appropriate for a given drug product. Australian Therapeutics Good Order 782 specifies that, for a tablet or capsule without a British Pharmacopeia monograph, the average content of each active ingredient in a pooled sample of not fewer than 20 dosage units should be used to determine the assay value for the active ingredient. This guidance however does not take into consideration product or method variability which could significantly impact the number of replicates and number of dosage units in a composite needed to obtain reliable results. A review of USP monographs3 reveals that the majority of the monographs for oral dosage forms require “not fewer than 20 dosage units” to be prepared in a composite sample for assay

nalytical test results are critical to the development and release of a commercial pharmaceutical product. Test results are used during all stages of drug development to make decisions, such as selecting and optimizing clinical and commercial formulations, optimizing manufacturing process parameters, and assessing and ensuring active pharmaceutical ingredient (API) and drug product strength (labeled active ingredient content), quality, and stability against regulatory specifications. In order to generate accurate, reliable analytical data, the analytical method must be appropriate for use. An understanding of the uncertainty of the reportable potency assay value (the measured active ingredient content of the drug product) is required in order to make risk-based decisions of the product potency assay measurement. It is this understanding that allows the team or company to communicate the risk in decisions concerning product potency. ICH Q6A1 specifies universal tests that are generally applicable to new drug products to ensure safety and efficacy. These tests include description, identification, assay, and impurities. Assay testing typically involves reporting the average value of replicate preparations of a composite of multiple © 2014 American Chemical Society

Received: September 22, 2014 Accepted: November 12, 2014 Published: November 12, 2014 11930

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Table 1. Compendial Analytical Validation Terms and Definitions term accuracy intermediate precision repeatability standard error (SE) uncertainty variability variance

definition The closeness of test results to the true value. The measure of closeness is sometimes termed “bias”, “trueness”, or “systematic error”. Variability within a laboratory that may include performing the procedure on different days, and/or with different analysts, etc. Precision of the analytical procedure use within a single laboratory over a short period of time using the same analyst with the same equipment. The square root of the variance divided by the number of individual results. The dispersion of values that could be reasonably attributed to the measurand. The precision of a measurement describes the uncertainty. The degree of agreement among individual test results; a measure of the dispersion among a number of measured values. Usually expressed as a statistic such as the standard deviation, variance, coefficient of variation, relative standard deviation, or the half width of a confidence interval. A numerical measure of variability denoted by σ2.

Table 2. Factors Affecting the Variability of an Assay Value method factors dosage unit factors (1) content uniformity

sample preparation (1) weighing; (2) extraction; (3) dilution; (4) solution stability; (5) environmental conditions during preparation

standard preparation (1) weighing; (2) extraction; (3) dilution; (4) solution stability; (5) environmental conditions during preparation

analysis (e.g., HPLC) (1) injection precision; (2) separation robustness; (3) detection; (4) integration; (5) environmental conditions during analysis

Table 2. These components comprise the standard error (SE) of the reportable potency assay and may be termed as the repeatability of the assay. Additional variance components enter into the totality of uncertainty of data generated by an assay method, such as analyst, instrument, laboratory, etc.7 These components must also be understood when making a decision of lot release, for example. An illustration of these method variance components is displayed through a uniformity of dosage units (UDU) experiment. As shown in eq 1, total variability of a typical uniformity of dosage units experiment consists of at least the following variance components, sample preparation, injection precision, standard preparation, dosage unit, etc., and may include other sources such as day and or analyst.

testing. A few of these monograph assay methods state to use “not less than 10 units.” Other monograph methods make no mention of the number of dosage units and only state to place a suitable number of tablets or capsules into a suitable volumetric flask to yield a specific concentration. There exists no consensus, nor does there appear to be a justified rationale for the number of dosage units selected in these methods. An appropriate number of units in the composite sample and number of sample replicates can be determined as a component of the variability minimization strategy of the assay result for a given batch. In cases where the dosage unit has high content variability, increasing the number of units in the composite sample preparation will reduce the variability in the assay result. Testing replicate sample preparations can reduce variability for cases where there is high assay variability due to the analytical method itself. It is important to understand the composition of the variability in potency assays in order to effectively determine an appropriate number of dosage units in the composite sample preparation and an appropriate number of sample replicates to generate the assay value for a given batch. In this work, a sampling strategy was developed for preparation of sample replicates and composites of assay test methods for solid oral drug products by chromatographic analysis. This strategy accounts for variability due to the analytical method and dosage form and uses the most restrictive compendia and regulatory requirements2,4−6 for potency assay sampling and variability to determine an appropriate sample strategy.

σUDU 2 = σsamplepreparation 2 + σinjection precision 2 + σstandard preparation 2 + σdosage unit 2 + ...

(1)

To minimize method uncertainty, it is important to focus on reducing the largest contributors to this total variability by understanding the method settings (sample agitation rate, injection volume, etc.) that minimize these contributors as illuminated through appropriately designed experiments. When these variance components can no longer be reduced from a mechanistic understanding, an additional strategy is to define a sampling scheme or replication strategy that minimizes those components. For example, standard and sample preparation variability, injection variability, and dosage unit variability all can be reduced through such a sampling scheme, since a potency assay may consist of multiple sample and/or standard preparations, injections, and/or dosage units per sample preparation. In this work, we focus on method variability and dosage unit variability due to the importance these variables have on measurement uncertainty. Equation 1 therefore can be rewritten as eq 1a. It is assumed that the contributions of injection repeatability and other system specific variability as well as the effect of the standard preparation scheme have been optimized in other experiments.7 In this paper, the term method refers to the variability composed of the system and sample preparation.

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METHODS Definition of Analytical Variability. Analytical variability or potency assay measurement variability is composed of several compositional sources. These sources of variability include the components of dosage unit and the analysis method which consists of sample preparation, standard preparation, and sample analysis. Analytical variability and other typical analytical validation terms used throughout this paper are defined in Table 1. In the development of an assay method for drug product, the variability of a single reportable assay value is composed of those variance components attributed to the individual analysis method and standard and sample preparations as detailed in 11931

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σUDU 2 = σmethod 2 + σdosage unit 2

Total Variability: Experimental Model, Uniformity of Dosage Units. In a uniformity of dosage (UDU) experiment, an individual dosage unit (dui) is prepared into an individual sample preparation (Si). Scheme 2 illustrates such an experimental run.

(1a)

Why Are We Concerned with Uniformity of Dosage Units in a Potency Assay? To determine a sampling scheme that minimizes, to an appropriate level, the contribution of the method and dosage unit components to the overall potency assay variability, consider a potency assay method experiment that produces a final reportable value (Y̅). A potency assay consists of a number of dosage units (duj) prepared into a sample (Si) of which there may be a number of replicate (r) sample preparations composited to form the reportable assay value. Scheme 1 illustrates such an experimental run.

Scheme 2. Illustration of the Samples Prepared to Determine Uniformity of Dosage Units

Scheme 1. Illustration of the Samples Prepared to Determine Assay Yi = μ + εi + ηi

i = 1 to r ;

j = 1 to k

var(Y ) = (σε 2 + ση 2)

(2)

(3a)

ση2

Equation 2 illustrates the signal representing the amount of an analyte (Y) with a true mean (μ) value and individual signals which vary about this mean according to the contribution of method (εi) and dosage unit (ηij) effects. The effects εi and ηij are assumed to be independent of one another and are effects from a random sample with population mean of 0 and variances σε2 and ση2, respectively. The variability of such an assay is then illustrated in eq 2a, where (Y̅) is the reportable value for the potency assay that consists of the average of r sample preparations each composed of k dosage units. ⎡1 1 ⎤ var(Y ̅ ) = ⎢ σε 2 + ση 2 ⎥ ⎣r rk ⎦

(3)

Equation 3 illustrates the signal (Y) representing the amount of an analyte with a true mean (μ) and individual signals which vary about this mean according to the contribution of method (εi) and dosage unit (ηi) effects. The effects εi and ηi are assumed to be independent of one another and are effects from a random sample with population mean of 0 and variances of σε2 and ση2, respectively. The variability of an UDU value is then as follows in eq 3a.8

Each sample preparation (Si) consists of a preparation of k dosage units that may be added as whole units or ground into powder and equivalently weighed. The analyte amount derived from the sample matrix calculation can be represented by eq 2.8 Yij = μ + εi + ηij

i = 1 to r

Note: can be composed of both potency and weight of dosage unit variability. As in the potency assay, the error attributed to method and dosage units is inseparable: a single measurement is made on each sample preparation that consists of a single dosage unit. To determine a sampling scheme (solving for r and k in eq 1a), an estimate for each individual component must be obtained. A general solution (If the UDU and potency assay method are the equivalent method, then a simple algebraic solution exists for the solution of method and dosage unit variance estimates. The viability of this technique is dependent upon the correctness of the potency assay variability estimate.) that works for any combination of UDU and potency assay method techniques is defined by obtaining independent variance component estimates. In the development of the potency assay method, there are several experiments that provide estimates of the method variability (σε2) alone. With an estimate of method variability (σε2), an estimate of the dosage unit variability (ση2) can be solved via subtraction in eq 1a. One possible resource for providing the estimate of method variability (σε2) is the accuracy assessment experiment during the method’s development and validation. This seems to be a logical choice since an accuracy assessment is usually executed early in the development of a method, hence providing the means to determine a sample composite strategy as early as the first uniformity of dosage unit experiment is completed. See Figure 1 for a flowchart of a possible sampling scheme executed workflow. At least one other strategy exists to estimate the method and dosage unit variance components; however, it requires two things. The first is that the UDU and potency assay method are equivalent. Second, some minimum number of potency assays is completed on the same homogeneous material of the UDU experiment such that the method variability is viable for calculations. Due to random chance, this might not always be

(2a)

The variability of the reportable potency assay value consists of a contribution from both method (σε2) and dosage unit variability (ση2). Because the reportable value (Y̅) is the only value observed (i.e., the individual dosage units are not observed since they are dissolved in the composite sample solution), the variability attributed to the potency assay cannot be decomposed into the error attributed to dosage units and method using observed potency assay values alone. That is, these variability components are inseparable. The variability estimates of the method (σε2) and dosage units (ση2) are required to determine the number of replicate sample preparations and dosage units per sample preparation in a sampling scheme: r and k in eq 2a. How do we obtain these estimates if they cannot be determined from the observed potency values alone? The answer is through uniformity of dosage unit and other method development experiments such as an accuracy assessment experiment.9,10 Uniformity of dosage unit experiments provides an estimate of total reportable potency assay value variability: method plus dosage unit as illustrated in eq 1a, above. The section below illustrates a typical uniformity of dosage experiment to see the variance contributions in these experiments. 11932

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spiked into pure formulation placebo or a mix of product excipients to more closely mimic a typical product sample preparation. Yi = μ + εi* + ηi*

i = 1 to r

(4)

Equation 4 illustrates the signal representing the amount of an analyte (Y) with a true mean (μ) and individual signals which vary about this mean according to the contribution of method (εi*) and measured spiked content (ηi*) effects. The effects εi* and ηi* are assumed to be independent of one another and are effects from a random sample with a population mean of 0 and variances of σε*2 and ση*2, respectively. The variability of potency assay results from an experiment described above is defined in eq 4a. var(Y ) = (σ ε*2 + σ η*2)

(4a)

ση*2

The estimate of in eq 3a represents the variability about measured concentrations that are exceedingly precise. It is logical, therefore, to assume that ση*2 is approximately zero. Then, the variance of the observed accuracy values (eq 4a) consist of only variance due to the concentration preparations (σε*2). This value is thought to be a good approximation to σε2 in eqs 2a and 3a as long as there exists no unrealized effect of the dosage unit manufacture that is not captured in this spiking experiment; i.e., σε*2 in eq 4a is not an exaggerated underestimate of σε2 in eqs 2a and 3a. Other experiments may be utilized to determine an estimate of the method variability (σε2); however, for most methods, a well-defined accuracy experiment is the most complete and efficient means for obtaining this estimate. Illustrating the Sampling Strategy. With estimates of σε*2 (from an accuracy experiment as defined above) and uniformity of dosage unit variability consisting of the sum of (σε2 + ση2), the effect of increasing the number of dosage units (k) and/or sample preparation replicates (r) can be determined through eq 2a. See the case study below for an example of all the data and calculations necessary to achieve this. Figure 2 displays the effect of increasing the number of dosage units (k) and sample preparation replicates (r) in eq 2a

Figure 1. Flowchart to determine sampling scheme.

the case; hence, the authors recommend the workflow illustrated in Figure 1. Experimental Model: Accuracy Assessment of Drug Product Assay. To evaluate the accuracy of an analytical method, spikes of known analyte amount (Spi) are prepared into an individual preparation (Ci), usually in replicates of three or more different concentrations. Scheme 3 illustrates such an experimental run. The preparation (Ci) may be an analyte

Figure 2. Effect of sample preparation estimates on the standard error of a drug potency assay.

Scheme 3. Illustration of the Sample Prepared for Determination of Accuracy

upon the variability of a potency assay as measured by the standard error of potency (sqrt of eq 2a). As the values of k and r increase, the variability of the potency assay is reduced. The amount of reduction is predicated upon the ratio of the components σε2 and ση2 to the total assay variability. The 11933

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Table 3. Sampling Scheme for Drug Product Potency Assaya

a

Note: The red star pertains to the case study discussed below.

stopping criteria, labeled “Target SE” in Figure 2, can be derived using the logic outlined in the Discussion section, below.

Table 4. Uniformity of Dosage Unit Results for Product A Capsules

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uniformity of dosage unit (UDU) experimental results

RESULTS A composites and replicates strategy was developed to determine the number of dosage units (k) in a sampling composite and the number of composite sample replicates (r) required on the basis of the composition of method and dosage unit variability. The variability of potency equation (eq 2a) demonstrates that assay variability (var.(Y̅)) consists of method variability (σε2) and dosage unit variability (ση2). A sampling scheme that increases the number of sample preparations (r) and/or number of dosage units (k) per sample preparation will reduce the assay variability as illustrated Figure 2. A table of solutions for (r) and (k) from eq 2a was calculated for several ratios of method and dosage unit variability. A simplified version for ease of use in standard practice is shown in Table 3 below. The number of units in the composite is rounded to increments of five for ease of method implementation in routine testing. Table 3 illustrates only a fraction of the entire solutions to eq 2a; however, it represents the vast working range for most products based on our experience and could be expanded to accommodate additional variance component ratios.

batch

average % label claim

standard deviation (SD) of n = 10 dosage units per batch

1 2 3 4 5 6 7 8 9 average

99.3 101.2 101.4 100.6 101.4 98.1 98.2 100.8 100.0 100.1

3.27 2.21 2.18 2.54 2.23 2.99 1.90 2.63 2.66 2.51

Table 5. Results of Accuracy Experiment for Product A Capsules % recovery replicate

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CASE STUDY The composites and replicates strategy was applied to a capsule formulation of product A, a product under development. As shown in Table 4, uniformity of dosage unit data was available for nine manufactured batches. Table 5 shows the results of accuracy experiments. The data in Tables 4 and 5 are used to calculate method and dosage unit variability as shown below. This information is then used to determine the appropriate sampling scheme from Table 3. Product A Capsules: (1) Calculate variance of UDU (σUDU2): (a) Overall %RSD for UDU from Table 4 = 2.51; (b) Variance of UDU = σUDU2 = (2.51 × 2.51) = 6.3. (2) Calculate variance of method (σmethod2): (a) Overall Method %RSD is 0.5% from

% of nominal concentration

1

2

3

mean (%RSD)

70 100 130

100.5 100.4 99.6

100.9 100.0 99.3

100.2 100.6 99.5

100.5 (0.3) 100.3 (0.2) 99.5 (0.1)

overall

100.1 (0.5)

Table 5. (b) Variance of method = σmethod2 = (0.5 × 0.5) = 0.25. (3) Estimate dosage unit variance (σdosage unit2): (a) Dosage unit variance is obtained by subtraction using eq 1a. σUDU 2 = σmethod 2 + σdosage unit 2 6.3 = 0.25 + σdosage unit 2 6.05 = σdosage unit 2 11934

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the number of sample replicates and dosage units in the composite sample preparations for a potency assay method was selected on the basis of regulatory criteria for uniformity of dosage units.2,4−6 To develop the most restrictive criterion, the standard error of the drug product assay should be minimized. As defined by eq 2a, the greater the number of dosage units prepared in a sample, the greater is the reduction in the variability of a potency assay. This is a square root relationship; therefore, a balance between number of dosage units (and hence impact on sample preparation efforts due to volumes and subdilutions required) and net gain is needed. The greatest number of dosage units defined in a regulatory document is k = 20 dosage units as recommended in TGO 78.2 A greater number of dosage units per sample preparation would further reduce the variability of the potency assay; however, the choice of k = 20 is the most conservative with respect to current regulatory guidance. Since there exist no known criterion for the number of sample preparation replicates (r) in regulatory guidance, we will maintain that r = 1. From USP ,7 we can determine a maximum variability of dosage units (variance of UDU) allowed utilizing the criterion contained in that document. As outlined in USP , for solid oral dosage forms, the acceptance value for uniformity of dosage units (AV) is calculated by the formula AV = |M − X̅ | + ks and must be less than 15, where the terms are defined below in Table 6.

(4) Estimate method variability and dosage unit variability as a percentage of total variability: σcomponent 2 (% total) = (σcomponent 2/σUDU 2) × 100 σmethod 2 (% UDU) = (0.25/6.3) × 100 = 4% σdosage unit 2 (% UDU) = (6.05/6.3) × 100 = 96%

(5) Determine sampling scheme (number of sample preparation replicates and number of dosage units per sample preparation): (a) Using the overall %RSD from Table 1 (2.5%) and the ratio of % sample preparation variability (4%) and % dosage unit variability (96%) from step 4 above, find the number of replicates and units from Table 3 (see star location). (b) Sampling scheme is 1 replicate of composite of 5 dosage units (k = 5, r = 1).

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RETROSPECTIVE ANALYSIS A retrospective evaluation of 26 in house immediate release and controlled release tablet and capsule drug products at different stages of development was performed using the approach described in this paper. On the basis of the sampling scheme in Table 3, 20 of the drug products require one replicate of a composite preparation containing either 5 or 10 units for assay testing. Three drug products were outside the bounds of Table 3 due to high method variability (e.g, greater than 30%), but these products had low UDU (%RSD) (e.g., 1.1% to 1.6%). Using the calculations described in this paper, it was determined that for these three products one replicate of a composite preparation containing either 5 or 10 units was suitable for assay testing. The remaining three products were outside the bounds of Table 3 due to high UDU (%RSD) (e.g, between 4.2% and 4.7%). Using the calculations described in this paper, it was determined that these three products required either one replicate of 10 units or two replicates of 10 units or more. On the basis of this retrospective analysis of 26 drug products, the majority of the products (>75%) were within the bounds of Table 3 and demonstrate that the sampling scheme proposed in Table 3 is suitable as tool for sample preparation method development. For products outside the bounds of Table 3, analysis can be performed specifically for these products to define the sampling scheme using the principles outlined in this manuscript. This approach also shows that the majority of the product (>85%) requires only one replicate of a composite preparation containing either 5 or 10 units.

Table 6. Definitions for Terms Used in Calculating the Acceptance Value (AV) variable

definition and condition

value

k

if n = 30, then k =

2.0

X̅

sample mean

∑i = 1 xi

S

sample standard deviation

M

if 98.5% ≤ X̅ ≤ 101.5%, then if X̅ < 98.5%, then if X̅ > 101.5%, then

n

n n

∑i = 1 (xi − X̅ )2 n−1 M = X̅ M = 98.5 M = 101.5

Table 7 illustrates the calculated maximum standard deviation of dosage units that would still pass USP < 905> Table 7. Maximum Observed Standard Deviation Allowed in USP Acceptance Value (AV) Criterion when n = 30 and Batch Mean is 95% or 105% Label Claim

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DISCUSSION A sampling scheme was developed as shown in Table 3 to determine an appropriate number of sample replicates and dosage units in the composite sample preparation for a potency assay. This sampling scheme is based on the sample preparation variability, dosage unit variability and product UDU (%RSD), and a criterion of SE of NMT 1.3. The basis for the criterion of the SE is discussed below. Criterion. In order to determine a table akin to the one illustrated in Table 3 above, a criterion for assessing the adequacy of potency assay variability must be established. This criterion should contain the most restrictive elements of current regulatory guidance in order to maximize the confidence in decisions made by such an assay. Establishing a Minimal Criterion for the Standard Error of a Drug Product Assay. The sampling strategy for

xbar = 95

98.5 < xbar < 101.5

xbar = 105

5.75

7.50

5.75

criterion of AV < 15. The values in Table 7 are derived by solving for the standard deviation term in the AV equation for n = 30 dosage units and a specified xbar (s = (AV − |M − X̅ |)/k). A batch mean of 95% (105%) label claim was chosen as this is a typical solid oral dosage form drug product release specification. Then, the most conservative (smallest value) criterion for SE of an assay can be computed as 5.75/sqrt(20) = 1.3, as illustrated in Table 8. The above illustrates the basic components germane to determine a criterion for the standard error of a potency assay. Criterion for the standard error of a potency assay other than 11935

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(8) Kutner, M. H.; Nachtsheim, C. J.; Neter, J.; Li, W. Applied Linear Statistical Models, 5th ed.; McGraw-Hill/Irwin: Boston, 1996. (9) ICH Q2(R1) Validation of Analytical Procedures: Text and Methodology; ICH: Geneva, 1994. (10) ICH Q2B Validation of Analytical Procedures: Methodology; ICH: Geneva, 1996.

Table 8. Maximum Standard Error of a Potency Assay Using Standard Deviation of 5.75% and k = 20 Dosage Units Per Preparation xbar = 95

98.5 < xbar < 101.5

xbar = 105

1.29

1.68

1.29

1.3 can be obtained utilizing probability assessments, of passing the USP , for example, in conjunction with company lot release standard practices and in concert with the organization’s risk and control strategies.

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CONCLUSION A sampling strategy for the number of sample replicates and dosage units in the composite sample preparation for a potency assay method was developed. This sampling strategy takes into account the sample preparation variability, dosage unit variability, and product UDU. It uses the criterion that the standard error is not more 1.3. A table of solutions for the number of sample replicates and the number of dosage units per sample preparation was derived for any scenario of an analytical method variability composition from such a criterion. The sampling scheme is demonstrated on a case study. The procedure illustrated allows a company to define a sampling strategy for drug product potency assay methods that conforms to an internally defined minimal risk-based standard and allows uncertainty to be communicated in regards to potency assay decisions. This work provides the assay method basis of variability understanding upon which additional components of method variability (e.g., instrument, analyst, environment, etc.) can now be determined through additional experimentation such as during the analytical method transfer exercise.

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AUTHOR INFORMATION

Corresponding Authors

*E-mail: brent.harrington@pfizer.com. *E-mail: beverly.nickerson@pfizer.com. Notes

The authors declare no competing financial interest.

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ACKNOWLEDGMENTS The authors would like to thank Debbie Krause, Kim Vukovinsky, and Loren Wrisley for their encouragement and support of this work.

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REFERENCES

(1) ICH Q6A Specifications: Test Procedures and Acceptance Criteria for New Drug Substances and New Drug Products: Chemical Substances; ICH: Geneva, 1999. (2) Therapeutic Goods Order No. 78 − Standard for Tablets and Capsules; Australian Government Department of Health and Ageing, Therapeutic Goods Administration: Woden, Australia, 2008. (3) USP 36-NF31 through Second Supplement; The United States Pharmocopeial Convention: Rockville, MD, 2013. (4) Uniformity of Dosage Units in USP 36-NF31 through Second Supplement; The United States Pharmocopeial Convention: Rockville, MD, 2013. (5) EP 2.9.40 Uniformity of Dosage Units in European Pharmacopoeia, Supplement 8.2 to the 8th ed; European Directorate for the Quality of Medicines & Healthcare: Strasbourg, France, 2014. (6) 6.02 Uniformity of Dosage Units, in Japanese Pharmacopoeia Supplement II, 16th ed.; The Ministry of Health, Labour and Welfare: Tokyo, 2014. (7) Ermer, J.; Agut, C. J. Chromatogr., A 2014, 1353, 71−77. 11936

dx.doi.org/10.1021/ac503551r | Anal. Chem. 2014, 86, 11930−11936