Pharmaceutical analysis: Measurement and data reliability Flashcards

1
Q

What are the steps in drug analysis (5)

A
  1. Take representative sample
    2, Extract analyte(s) from interfering matrix
  2. separate analytes
  3. identify, detect and quantify analytes
  4. determine reliability/validity of results
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2
Q

What does a ‘representative sample’ represent?

A

represents a large portion of batch. taking sample from different places within the sample to ensure its homogeneously mixed

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3
Q

What is an analyte?

A

What we want to detect - drug/metal etc

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4
Q

What step must be taken to test if it is highly susceptible to impurities?

A

purification

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5
Q

What is data validity?

A

Determine through stats, comparison with standards and/or another method.

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6
Q

How can you present data?

A
  • Group it: frequency table/histogram/bar chart
  • Only one parameter changed: line graph
  • More than one parameter changed: scatter graph
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7
Q

Are analytical measures exact?

A

NO

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8
Q

What can you assume about the last digit quotes in a measured value?

A

That it is uncertain

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9
Q

If a value of weight is 44.2239672g and the accuracy of the balance is +/- 0.1mg, what is the final weight?

A
  1. 2240g

0. 1mg = 0.0001g

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10
Q

When adding and subtracting, what number of decimal places should you round off to?

A

The SAME number of decimal places as the value having the FEWEST decimal places;

100 + 28.621 = 129

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11
Q

When multiplying and dividing, what number of significant figures should you round off to?

A

The same number of sf as the value with the least.

2.1 x 11.31 = 24

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12
Q

When is zero significant?

A

Zeroes between non-zero digits are significant:
4.06ml (3 sig fig)
zeros to the left of first non-zero digits are not significant: 0.014 g has 2 significant figures
zeroes to the right of a decimal point in a number are significant: 0.0130 mL has 3 significant figures
Zero at the end of a number without decimal point may or may not be significant: 4600 calories may be 2, 3, 4 significant figures.

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13
Q

When taking measurement on a SCALED instrument, how should you read the value?

A

Go ONE more figure than you can actually read. e.g. when measuring thirty ml of solvent, the accuracy is only 30.00ml

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14
Q

What 3 types of errors is the validity of analytical measurement affected by?

A
  1. Indeterminate (random) error: evaluate with statistics - affects precision more than accuracy
  2. Determinate (systematic) error: evaluate with standards - affects accuracy more than precision
  3. Gross error: big mistake, like spilling everything on the floor, sample evaporated etc
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15
Q

What is the difference between accuracy and precision?

A

Accuracy is how close a value is to its true value. An example is how close an arrow gets to the bull’s-eye centre.
Precision is how repeatable a measurement is. An example is how close a second arrow is to the first one (regardless of whether either is near the mark).

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16
Q

How is precision expressed?

A

Standard deviation
RSD = (s/x)100
x=average value

Precision is better expressed as a % of the mean value so units become unimportant

17
Q

How is accuracy expressed?

A

By calculating absolute error: Xi - Xt (observed value - true value)

Relative error:
Er = (Xi-Xt)/Xt x 100

18
Q

What are the origins of systematic error? (3)

A
  1. Instrumental
    - calibration: apparatus (cylinders, dispensers)
    - equipment (balances, pH meter)
  2. Method
    - reagents (unstable)
    - reactions (incomplete)
  3. Personal error
    - e.g. eye sight (colour, height etc
19
Q

What is null hypothesis?

A

assumes no bias can be used to verify the type of error.

20
Q

When should you reject or accept null hypothesis?

A

Reject if: value is bigger - evidence of systematic error

Accept if: value is smaller - evidence of random error

21
Q

What is the t-test?

A

The t- test (Student’s t) is used to calculate the confidence intervals of a measurement when the population standard deviation is not know. Which is usually the case with limited number of data points.
The t-test is also used to compare two averages.
The t-test corrects for the uncertainty of the sample standard deviation (s) caused by taking a small number of samples.

22
Q

How do we compare different methods?

A

Repeat each method 5 times and calculate mean and standard deviation.
Can you verify to 99% confidence level that mean values do not significantly differ?

23
Q

What test can help to detect gross error?

A

Q test using Q distribution table to compare values

24
Q

What is method validation?

A

The process of demonstrating that analytical procedures are suitable for their intended use and that they support the identity, strength, quality, purity and potency of the drug substances and drug products

25
Q

What is significant about biological assays?

A

More difficult to validate