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Intelliboost

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A Brisardik Pharmaceuticals Product Presentation by: David Brinser, Tiana Harris and Michele Hladik
Transcript
Page 1: Intelliboost

A Brisardik Pharmaceuticals Product

Presentation by: David Brinser, Tiana Harris

and Michele Hladik

Page 2: Intelliboost

About Brisardik

Established in 1987

Based in Columbus, Ohio

More than 500 physicians,

chemists, and lab assistants

Known for popular ADHD medications

and anti depressants

Creator of Intelliboost

Page 3: Intelliboost

Intelliboost

Taken once daily

Prescription

Gradually builds up

Strengthen and develops decision

making and processing functions

Could be sold in a variety of sizes

Study to determine if medication

works and is ready for sale

Page 4: Intelliboost

Study Participants

Randomly selected 60 adults

Customers and research volunteers

Intelligence testing

30 given Intelliboost, 30 placebos

Intelligence retesting

Page 5: Intelliboost

Data Collection

Participant IDs

Test scores recorded

Data sorted in several ways including:

All participants

Intelliboost recipients

Placebo recipients

Gender

Age

Improvements made

Page 6: Intelliboost

Patients Taking Intelliboost

Participant ID. Before After

1001 140 143 1002 110 110

1006 138 135 1007 141 142

1010 70 74 1011 119 122 1014 113 125

1015 78 78 1018 143 144

1019 125 130 1022 86 87 1023 126 127

1026 76 80

1027 127 128

1030 92 95

Participant ID. Before After

1031 117 117 1034 95 96 1035 147 148 1037 96 105 1043 74 74 1045 97 105 1046 129 135 1047 149 149 1048 94 105 1050 130 128 1051 99 110 1054 95 100 1055 112 112 1057 114 120 1060 96 106

Before After

Average 110.9333 114.3333

Page 7: Intelliboost

Patients Taking Placebo Participant

ID. Before After 1003 80 82 1004 97 103

1005 92 92 1008 90 95

1009 123 123 1012 142 138 1013 77 77

1016 134 132 1017 99 100

1020 81 85 1021 91 93 1024 144 142

1025 112 112

1028 98 98

1029 145 145

Participant ID. Before After

1032 84 84 1033 71 72 1036 79 79 1038 135 130 1040 116 116 1041 148 148 1044 110 112 1042 89 89 1039 93 93 1049 85 86 1052 111 111 1053 120 121 1056 90 94 1058 75 75 1059 121 121

Before After

Average 104.4 104.9333

Page 8: Intelliboost

Data by Age

Increased IQ with Intelliboost January March

18-27 3 1 28-37 4 2

38-47 5 3 48-57 4 1 58 & Older 1 0

Increased IQ with Placebo

January March

18-27 2 1

28-37 4 2 38-47 4 2

48-57 2 1 58 & Older 0 0

18-27 28-37 38-47 48-57 58 and older

Intelliboost 6 9 8 5 2 Placebo 5 8 9 6 2

Page 9: Intelliboost

Summary Output

All Data

The independent variable medicine/placebo

The dependent variable the IQ score

Scatter diagram

0

20

40

60

80

100

120

140

160

0 20 40 60 80 100 120 140 160

Aft

er

Before

All Participants Before/After

Page 10: Intelliboost

Linear Correlation

All Data

r = 0.991146 p = 0.000000

y=a+bx a=7.663276883 b=.9473999051 n=60 7.663276883+.9473999051(60)=64.5073

slope = 1.03691245

Coefficient of correlation-r=0.9911

Strong positive correlation

Represents a good model

The line fits the points well

r suggests there is a linear correlation

between IQ scores and the use of a

placebo or new medication

Page 11: Intelliboost

All Data Continued…

A few outliers based on the scatter diagram are (94,105),

(96,106), (97,103), (75,75), and (129, 135)

Using (129,135) and entering it into the regression line the

solution would be: 7.6633+.9474(129)=130

This predicted answer is close to the observed answer of 135.

This is not too far beyond the scope of available data.

The point with the largest residual is (94,105).

7.6633+.9474(94)=97

105-97=8 equaling the largest residual.

This point does not accurately represent the regression line.

Page 12: Intelliboost

Summary Output-Intelliboost

The independent variable the medicine

The dependent variable the IQ score

Scatter diagram

0

20

40

60

80

100

120

140

160

0 50 100 150 200

Aft

er

Before

Patients Taking Intelliboost

Series1

Linear (Series1)

Page 13: Intelliboost

Correlation - Intelliboost

Coefficient of correlation r=.9847

Strong positive correlation

This represents a good model

The line fits the points well

r suggests there is a linear correlation between

IQ scores and the use of the new medication

slope=1.025282845

p=0.0000

r=0.9847

r square=0.9696

y=a+bx

a=9.4258

b=0.9457

n=30

9.4258+.9457x

Page 14: Intelliboost

Intelliboost Continued…

A few outliers based on the scatter diagram are (113,125) and (99,110).

Using point (140,143) and entering it into the regression line:

y=9.4258+0.9457(140)=142 with a residual of 1.

The predicted answer is close to the observed answer of 143. This is not

too far beyond the scope of available data.

97% of participants saw a change in their IQ after taking the new medicine

y=9.4258+.9457(99)=103 with a residual difference of 7.

y=9.4258+.9457(113)=116 with a residual difference of 9.

This point has the largest residual value and does not accurately

represent the regression line.

Page 15: Intelliboost

Summary Output-Placebo

The independent variable the placebo

The dependent variable the IQ score

Scatter diagram

0

20

40

60

80

100

120

140

160

0 50 100 150 200

Aft

er

Before

Patients Taking New Placebo

Series1

Linear (Series1)

Page 16: Intelliboost

Correlation - Placebo

Coefficient of correlation r=0.9963

Strong positive correlation

This represents a good model

The line fits the points well

r suggests there is a linear correlation between

the IQ scores and the use of the placebo

slope=1.04585667

p=0.0000

r=0.9963

r square=0.9926

y=a+bx

a=5.8513

b=0.9491

n=30

5.8513+0.9491

Page 17: Intelliboost

Placebo Continued…

There are no outliers on the placebo scatter diagram

Using point (80,82) and entering it into the regression line:

y=5.8513+0.9491(80)=82

It has a residual of 0.

The predicted answer is exactly the same as the observed answer of

82. This is exactly within the scope of available data.

Using the point (97,103) and entering it into the regression line:

y=5.8513+.9491(97)=98 with a residual of 5.

This point has the largest residual value and does not accurately

represent the regression line.

Page 18: Intelliboost

ANOVA

Test criteria

Test results

Importance of the mean

Intelliboost ANOVA f= .33425

p=.5654

Placebo ANOVA f=.00809

p=.9286

Page 19: Intelliboost

Paired Test

Breakdown of test

Analyzing results

Validity of test

Intelliboost Paired Test

t= 4.55279

p=.00004387

x= 3.4

Sx=4.09035

n=30

Placebo Paired Test

t= 1.2867

p= .10418

x= -.5333

Sx= 2.2702

n= 30

Critical value for 29 deg of freedom is : 2.045

Page 20: Intelliboost

Final Recommendations

Move forward with Intelliboost.

Seek final approval from the United States

Food and Drug Administration

Begin marketing Intelliboost

Begin production and pharmaceutical

distribution of Intelliboost

Page 21: Intelliboost

Closing

Thank you!

Questions

Page 22: Intelliboost

Footnote

Note: Brisardik Pharmaceuticals and Intelliboost

were invented for the sake of this project. All data

was created for the project purposes only. Data

collection methods are designed to show how the

data would have been collected if the company,

drug and study were real.


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