DATA QUALITY Flashcards

(61 cards)

1
Q

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

A

Error

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2
Q

can be classified as systematic
error or indeterminate error

A

Error

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3
Q

Systematic Errors
- also known as the

A

determinate errors.

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4
Q

errors that are reproducible and can be
discovered and corrected.

A

Systematic Errors

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5
Q

Systematic Errors Can be further classified into:

A

Instrumental Error
- Method Error
- Personal Error

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6
Q

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

A

Instrumental Error

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7
Q

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

A

method Errors

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8
Q

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

A

Personal errors

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9
Q

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

A

Random Errors

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10
Q

Random Errors also known as the

A

indeterminate errors .

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11
Q

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

A

Random Errors

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12
Q

A plot of indeterminate error would show a

A

normal frequency curve

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13
Q

Minimization of Errors

A

Proper calibration of the glass ware, pipettes,
burettes, weights, balances, instruments, etc.
* By running the blank with the sample. The blank
solution is defined as the solution by omitting
the sample addition. The blank and the sample
solutions are carried simultaneously to obtain
the accurate results.
* By running the parallel determinations.
* Correctly recording and computing data results

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14
Q

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

A

Validation

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15
Q

pertains to agreement of an
experimental results with true value

A

Accuracy

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16
Q

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

A

Precision

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17
Q

In a normal distribution,
__% of the values should
fall within one standard
deviation in either side of
the mean

A

68%

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18
Q

In a normal distribution,
68% of the values should
fall within ____ standard
deviation in either side of
the mean

A

ONE

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19
Q

And __% should fall within
two standard deviations of
the mean

A

95

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20
Q

And 95% should fall within
___ standard deviations of
the mean

A

2

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21
Q

So, standard deviation
should be a ____
percentage of the mean.

A

SMALL

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22
Q

measure of central tendency

A

Mean

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23
Q

difference between largest/smallest
observations in a set of data

A

Range

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24
Q

measures the difference of the
actual values with the mean value

A

Average Deviation

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25
determined by dividing the average deviation by the mean
Relative average deviation
26
sum of squares difference of the actual values with the mean value/total number of samples
Variance
27
Square root of variance
Standard Deviation
28
Is used to measure precision of a data set.
Relative Standard Deviation (%RSD)
29
is a measure of the accuracy of the method.
Percentage Relative Error (E)
30
is the process by which it is established, by laboratory studies, that the performance characteristics of the procedure meet the requirements for the intended analytical applications.
Validation
31
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.
validation
32
Purpose of Validation
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
33
TYPES OF ANALYTICAL PROCEDURES TO BE VALIDATED
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.
34
VALIDATION PARAMETERS
* Accuracy * Precision * Range * Specificity * Linearity * Ruggedness
35
is the closeness of test results obtained by that procedure to the true value.
ACCURACY
36
Determined by application of the analytical procedure to an analyte of known purity
ACCURACY
37
Accuracy should be assessed using a minimum of ____ determinations over a minimum of three concentration levels, covering the specified range.
9
38
Accuracy should be assessed using a minimum of nine determinations over a minimum of ____ concentration levels, covering the specified range.
3
39
It is the degree of agreement among individual test results when the procedure is applied repeatedly to multiple samplings of a homogeneous sample.
PRECISION
40
Precision may be a measure of either the degree of ______ OR _____ of the analytical procedure under normal operating conditions .
reproducibility or of repeatability
41
3 Levels of Precision
1, Repeatability 2. Intermediate Precision 3. Reproducibility
42
expresses the precision under the same operating conditions over a short interval of time.
Repeatability
43
Repeatability is also termed
intra-assay precision.
44
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.
Intermediate precision
45
expresses the precision between laboratories. The objective of reproducibility is to verify that the method will provide the same results in different laboratories
Reproducibility
46
the 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
SPECIFICITY
47
In case of identification tests, the method should be able to discriminate between compounds of closely related structures which are likely to be present.
SPECIFICITY
48
It is the lowest amount of analyte in a sample that can be detected, but not necessarily quantitated, under the stated experimental conditions.
DETECTION LIMIT
49
Its usually expressed as the concentration of analyte (e.g., percentage, parts per billion) in the sample
DETECTION LIMIT
50
The detection limit is a characteristic of
limit tests
51
It is the lowest amount of analyte in a sample that can be determined with acceptable precision and accuracy under the stated experimental conditions
QUANTITATION LIMIT
52
is a 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
QUANTITATION LIMIT
53
Its 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
54
refers to the linearity of the relationship of concentration and assay measurement.
LINEARITY
55
it is the 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
RANGE
56
It’s 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
ROBUSTNESS
57
Refers to the degree of reproducibility of test results under a variety of conditions such as q Different laboratories q Different Analysts q Different Instruments q Different Days
RUGGEDNESS
58
Analytical methods for quantitation of major components of bulk drug substances
Category I:
59
Analytical methods for determination of impurities in bulk drug substances
Category II:
60
Analytical methods for determination of performance characteristics
Category III:
61
Identification tests.
Category IV: