1 Basic Laboratory Methods in a Regulated Environment CLASSROOM ACTIVITY: FRANCES KELSEY AND THALIDOMIDE IN THE UNITED STATES: A CASE STUDY RELATING TO PHARMACEUTICAL REGULATIONS Submitted by Madison Area Technical College Contact Person: Lisa Seidman, Lseidman@matcmadison.edu
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Basic Laboratory Methods in a Regulated EnvironmentBio-Link Courses-in-a-Box Basic Lab Methods Classroom Activities 2 NOTES TO THE INSTRUCTOR ... laboratory careers in biotechnology.
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• The number 21 is the CFR title 2. The broad subject area is Food and Drugs.3
• The number 211 is the part. Part 211 is entitled Current Good Manufacturing Practice for Finished
Pharmaceuticals.
• The number .67 refers to a particular section. This section is about Equipment cleaning and
maintenance.
• The (a) is the first paragraph or subsection within the section.
There are various ways to access the portions of the CFR relating to the manufacture of
pharmaceuticals by using the web: 4
The FDA web site includes a copy of 21CFR parts 210 and 211 at this address:
http://www.fda.gov/cder/dmpq/cgmpregs.htm. You will also find links to other useful regulatory
information at this site.
Another site that publishes come of the FDA regulations is a commercial site hosted by The GMP
Institute http://www.gmp1st.com/index.htm. This site includes the following useful items:
• You can purchase inexpensive booklets from the GMP Institute that contain the text of the GMP
regulations.
• You can also go to their web site to link to the cGMP regulation 21 CFR Parts 210 and 211 for the
drug industry.
• They also have links to the regulations for the medical device industry (21 CFR Part 820), the food
industry (21 CFR Part 110) and the blood products industry (21 CFR Part 606).
• This site also has an inclusive list of guidance documents from the FDA.
• The Preamble for the current Good Manufacturing Practices as published in the September 29,
1978 issue of the Federal Register, can also be found on their web site. The Preamble is an
interesting document that contains comments from the public relating to the GMP regulations and
the official response to those comments.
Footnotes: 1 This explanation of the CFR is based largely on information from the National Archives and Records
Administration web site. This government web site explains what the Federal Register is and provides
access to government documents (http://www.archives.gov/). 2 Each of the titles of the CFR is assigned to a specific agency. The following link is a list of Government
agencies and their relevant CFR Titles, Subchapters or Chapters.
( http://www.access.gpo.gov/nara/cfr/parallel/alphabetical_list.pdf ) 3 Title 21 contains three Chapters that relate to Food and Drugs. Often the Chapter and Subchapter are
not cited, but the citation in the example here is found under Chapter 1. The agency that is responsible
for compliance with Chapter 1 is The Food and Drug Administration (FDA). The other Chapters are
controlled by other federal agencies. Chapter 1 has seven subchapters and 1299 Parts. Subchapter C
covers regulations for General Drugs. Other Subchapters within this Chapter cover regulations for Food,
Food additives, and other products regulated by FDA.
4 Federal regulations are first published in the Federal Register (FR) by the executive departments and
agencies of the Federal Government. The Federal Register is a legal newspaper published every business
day by the National Archives and Records Administration (NARA). It contains Federal agency regulations;
proposed rules and notices; and Executive orders, proclamations and other Presidential documents. The
Federal Register informs citizens of their rights and obligations and provides access to a wide range of
Federal benefits and opportunities for funding. The CFR is kept up-to-date by the daily Federal Register.
For the most up-to-date information, these two publications must be used together to determine the
latest version of any given rule. When a Federal agency publishes a regulation in the Federal Register, that
regulation usually is an amendment to the existing CFR in the form of a change, an addition, or a removal.
Bio-Link Courses-in-a-Box M&M Quality Control Activity
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PURPOSE
This is a classroom activity that introduces statistical methods as a way to evaluate the variability in a
system. One of the key goals of any quality system is reducing variability in the product. In this exercise
you will learn some simple statistical procedures and how they are used to evaluate product variability.
You will practice:
1. Calculating standard deviation and interpreting its meaning.
2. Constructing and understanding frequency histograms.
3. Thinking about variability and its importance.
BACKGROUND
A. VARIABILITY
There is always variation in any system or process. When producing a product, such as a biotechnology
product, it is important to reduce that variability as much as possible. For example, if a company is selling
an enzyme that is supposed to have an activity of 200 Units/mg, then they want every lot of that enzyme
to have an activity of 200 Units/mg. They do not want the activity to sometimes be 182 Units/mg, or 222
Units/mg, or any values other than 200 Units/mg.
The first step in reducing the variability in a process is to be able to evaluate it. The field of statistics
provides us with techniques to analyze variability in a set of data. In this laboratory exercise, we will
discuss two simple statistical methods to analyze the variability in a product, standard deviation and
frequency histograms. The product that we will examine is M&Ms and the features of the product that
are of interest to us are the numbers of M&Ms per bag and the colors of the candies. The numbers of
M&Ms per bag and the colors of the candies are variables, that is, values that can vary from one individual
to another.
The standard deviation (SD) is a common mathematical measure of the variability of a set of
numerical data. Refer to your textbook to find out how to calculate SD. We will calculate SD in this
exercise to measure and report the variability in the number of M & Ms in packages.
B. USING HISTOGRAMS TO DISPLAY VARIABILITY
Graphs can be used to illustrate data. A frequency histogram is a type of graph that displays the
distribution of a set of data. For example, a frequency histogram might indicate how many field mice
there are of various sizes in a field or how many students got grades of As, Bs, Cs, and Ds in a course.
The first step in preparing a frequency histogram is to categorize the data into classes or types. For
example, for course grades, there are four classes or types: A, B, C, and D. These classes are then
plotted on the X axis of a graph. The number of individual in each class is plotted on the Y axis in the
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form of bars. The number of individuals in each class determines how high the bar will be, that is, how far
up the bar goes on the Y axis.
In practice, we distinguish between situations where classes are continuous and those where they are
discrete. For example, height and weight are continuous variables. A mouse might be 19 g or 20 g or any
weight in between. In contrast, course grades are discrete. A student may get an A or B, or perhaps an
A- or B+ if the instructor uses these grades, but there are no grades in between. When variables are
continuous, the bars are usually plotted so that they touch one another. When variables are discrete, the
bars are usually plotted so that they do not touch one another. In the case of the M & M data that you
will collect, the values will be discrete. There might be 40 M &Ms in a bag or 41, but (unless some are
broken) there cannot be any value in between. Similarly, the number of colors a candy might be is not
infinite; only certain colors are possible.
It is possible to construct a frequency histogram for any data set consisting of the values for a single
variable. The procedure for doing so is given in the box below followed by an example:
Box 1
CONSTRUCTING A FREQUENCY HISTOGRAM
1. Divide the range of the data into intervals, or classes. It is simplest to make each interval the same width. There is no set rule as to how many intervals should be chosen; this will vary depending on the data. (For example, length data could be divided into intervals of 0-9.9 cm, 10.0-19.9 cm, 20.0-29.9 cm, and so on.)
2. Count the number (frequency) of observations that are in each interval.
3. Prepare a frequency table showing each interval and the frequency with which values fell into that interval.
4. Label a graph with the intervals on the X axis and frequency on the Y axis.
5. Draw in bars where the height of a bar corresponds to the frequency with which a value occurred. Center the bars above the midpoint of the class interval.
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AN EXAMPLE OF PREPARING A HISTOGRAM
Consider these hypothetical values for the grades of 43 students:
A D A A B C A C B B A
C B A D C C B B B A B
C B B A D B B A C B B
B A B B C B A B A C
Step 1: Divide the data into classes. This is easy; there are four classes, A, B, C, and D.
Step 2: Count the number in each class.
Step 3: Arrange the values into a table:
FREQUENCY TABLE
VALUE (Grade) FREQUENCY
A 12
B 19
C 9
D 3
Steps 4 and 5: Prepare the graph. Frequency is on the Y
axis and the grade is on the X axis.
ACTIVITIES
1. Open your bag of M &Ms and pour them onto a paper plate or towel. Count and record:
a. The total number of M & Ms in your bag.
b. The number of M & Ms of each color.
2. Record your data on the blackboard.
3. Based only on your own data, construct a histogram of color versus frequency.
4. Based on the class’s data as a whole, construct a histogram of color versus frequency.
5. Discuss the two histograms.
a. Are the two histograms the same or different? Explain.
Class Grade Distribution
0
2
4
6
8
10
12
14
16
18
20
A B C D
Grade
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b. Based on your own histogram, are the colors of M & Ms evenly distributed? Based
on the entire class's data, are the colors evenly distributed?
c. What do you predict a histogram would look like if you checked hundreds of bags of
M & Ms?
6. Based on the data for the entire class, calculate the mean number of M & Ms per bag, and the standard
deviation of the number of M & Ms per bag.
7. Based on the data for the entire class, construct a frequency histogram for the number of M & Ms per
package.
8. Discuss the mean and the standard deviation.
a. What does the mean tell you?
b. What does the standard deviation tell you?
9. If you were to count the number of M & Ms in hundreds of bags, what do you think the
frequency histogram would look like? Draw your prediction.
10. Where do you think variability in the M & M packages comes from? Does the variability in
M&M color distribution and the number of M&Ms per bag affect the quality of the product?
11. Why is it important to be able to measure variability in a process?
12. In what situations does variability in a product affect its quality? Why is it important to
find methods to reduce variability in a process?
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NOTE TO THE INSTUCTOR:
According to the “M & M hotline” the ratios of colors in the 1990s was:
red 20 %
green 10 %
blue 10 %
yellow 20 %
brown 30 %
orange 10 %
This was based on surveys of consumer preferences for different colors. People thought that chocolate
should be brown. However, this ratio has changed over the years with bright colors becoming more
common as consumer preferences change.
Students sometimes predict that if a great number of bags were checked, the colors would eventually be
evenly distributed and all the bars on a frequency histogram would be the same height. This is not the