PHAN LEC D3: DATA QUALITY

Error

defined as a deviation from the absolute value or from the true average of a large number of results.

systematic error or

indeterminate error

Error can be classified as ____

Systematic Errors

Classes of Errors:

errors that are REPRODUCIBLE and can be DISCOVERED and CORRECTED.

determinate errors

Systematic Errors also known as

Gross Error

Classes of Error:

takes into account human oversight and other mistakes while reading, recording, and readings.

easily recognized since they involve a major breakdown in the analytical process such as:

• samples being spilt,

• wrong dilutions being prepared

• instruments breaking down or being used in the wrong way

Instrumental Error

Method Error

Personal Error

Types of Systematic Error (3)

Instrumental Error

Types of Systematic Error:

-failure to calibrate, degradation of parts in the instrument, power fluctuations, variation in temperature

Method Errors

Types of Systematic Error:

errors due to no ideal physical or chemical behaviour, completeness and speed of reaction, interfering side reactions, sampling problems.

Personal errors

Types of Systematic Error:

occur where measurements require judgment, result from prejudice, color acuity problems, negligence to follow proper procedures

Random Errors

Classes of Errors:

observed by the same analyst when the successive measurements are made with the same identical conditions.

*acceptable error

indeterminate errors

Random Errors also known as

random error

appear as slight variations in successive measurements due to causes that the analyst can not control.

Random error

*May progress to determinate error

• Proper calibration of the glass ware, pipettes, burettes, weights, balances, instruments, etc.

• By running the blank with the sample.

• By running the parallel determinations.

• Correctly recording and computing data results

• By Validation

Minimization of Errors (5)

blank solution

defined as the solution by omitting the sample addition.

The blank and the sample solutions are carried simultaneously to obtain the accurate results.

Validation

Minimizing error:

is establishing DOCUMENTED EVIDENCE which provides a high degree of assurance that a specific process, method, system, activity or equipment CONSISTENTLY produce a product meeting its predetermined specifications

1. Accuracy

2. Precision

Measure of Data Quality (2)

Accuracy

pertains to agreement of an experimental results with true value

Precision

is the measure of reproducibility of data within a series of results.

Accurate but not precise

If repeated measurements are all close to the true value but spread out from each other, the results are:

Neither accurate nor precise

If measurements are neither close to each other nor to the true value, the results are:

Precise but not accurate

A weighing scale consistently gives a weight of 100.0 g for a 95.0 g standard. The scale is:

Precise but not accurate

If a target is hit in a tight cluster but far from the bullseye, the measurements are:

accurate and precise

Results should be ___ and ___

68%

In a normal distribution, ____ of the values should fall within ONE standard deviation in either side of the mean

95%

__ should fall within TWO standard deviations of the mean

mean

standard deviation should be a small percentage of the ____.

Mean

Data Treatment:

measure of central tendency

Range

Data Treatment:

difference between largest/smallest observations in a set of data

Average Deviation

Data Treatment:

measures the difference of the actual values with the mean value

Relative average deviation

Data Treatment:

determined by dividing the average deviation by the mean

Variance

Data Treatment:

sum of squares difference of the actual values with the mean value/total number of samples

Standard Deviation

Data Treatment:

square root of variance

Relative Standard Deviation (%RSD)

- Is used to measure precision of a data set.

• SD/ Mean x 100

Percentage Relative Error (E)

is a measure of the accuracy of the method.

Validation of Analytical Methods

process by which it is established, by laboratory studies, that the performance characteristics of the procedure meet the requirements for the intended analytical applications.

Method validation

provides an assurance of reliability during normal use, and is sometime referred to as "the process for providing documented evidence that the method does what it is intended to do.

• For identification of sources and quantitation of potential error

• To determine if method is acceptable for intended use.

• To satisfy FDA requirements

• To ensure the consistency of the output

Purpose of Validation (4)

1. Identification tests

2. Quantitative tests for impurities content.

3. Limit tests for the control of impurities .

4. Quantitative tests of the active moiety in samples of drug substance.

TYPES OF ANALYTICAL PROCEDURES TO BE VALIDATED (4)

1. Accuracy

2. Precision

3. Range

4. Specificity

5. Linearity

6. Ruggedness

VALIDATION PARAMETERS

Accuracy

____ of analytical procedure is the

closeness of test results obtained by

that procedure to the true value.

Accuracy

Determined by application of the analytical procedure to an analyte of known purity (e.g. A Reference Standard).

Accuracy

should be assessed using a minimum of NINE determinations over a minimum of THREE concentration levels, covering specified range.

i.e 3 conc and 3 replicates of each conc

PRECISION

degree of agreement among individual test results when the procedure is applied repeatedly to multiple samplings of a homogeneous sample.

Precision

may be a MEASURE of either the degree of reproducibility or of REPEATABILITY of the analytical procedure under normal operating conditions.

1. Repeatability

2. Intermediate precision

3. Reproducibility

3 Levels of Precision

Repeatability

expresses the precision under the SAME OPERATING CONDITIONS over a short interval of time.

intra-assay precision

Repeatability is also termed ___.

Intermediate precision

expresses variations within LABORATORIES, such as different days, different analysts, different equipment, and so forth.

- to verify that in the same laboratory the method will provide the SAME RESULTS once the development phase is over.

Reproducibility

expresses the precision between laboratories.

The objective of this is to verify that the method will provide the SAME RESULTS IN DIFFERENT LABORATORIES

SPECIFICITY

ability to measure accurately and

specifically the analyte of interest in the presence of other components that may be expected to be present in the sample matrix

In case of identification tests, the method should be able to discriminate between compounds of closely related structures which are likely to be present.

DETECTION LIMIT

lowest amount of analyte in sample that can be detected, but not necessarily quantitated, under the stated experimental conditions.

usually expressed as the concentration of analyte (e.g., percentage, parts per billion) in the sample

limit tests

detection limit is a characteristic of __

QUANTITATION LIMIT

lowest amount of analyte in a sample that can be determined with acceptable precision and accuracy under the stated experimental conditions.

quantitation limit

is characteristic of quantitative assays for low levels of compounds in sample matrices, such as impurities in bulk drug substances and degradation products in finished pharmaceuticals.

LINEARITY

ability to elicit test results that are directly, or by a well-defined mathematical transformation, proportional to the concentration of analyte in samples within a given range.

linearity

refers to the linearity of the relationship of concentration and assay measurement.

LINEARITY

> By Visual Inspection of plot of signals vs. analyte concentration

> By Appropriate statistical methods

• Linear Regression (y = mx + b)

• Correlation Coefficient, y-intercept (b), slope (m)

> Acceptance criteria: Linear regression rz > 0.95

> Requires a minimum of 5 concentration levels

RANGE

interval from the upper to the lower concentration (amounts) of analyte in the sample for which it has been demonstrated that the analytical procedure has a suitable level of precision, accuracy and linearity

ROBUSTNESS

the measure of its capacity to remain unaffected by small but deliberate variations in procedural parameters listed in the procedure documentation and provides an indication of its suitability during normal usage.

RUGGEDNESS

Refers to the degree of reproducibility of test results under a variety of conditions

Different laboratories

Different Analysts

Different Instruments

Different Days

Ruggedness (4)

Category I: quantitation of major components

Category II: determination of impurities

Category III: determination of performance characteristics

Category IV: Identification tests.

Data Elements Required for

Validation: (4)