# BME100 f2014:Group27 L6

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 Jonathan Almendras Patrick Conely Krystal Corrette Aaron Dodell Adam Samuel Yakut Umar

## PCR Lab E

Abstract: Overview of the Original Diagnosis System

The diagnosis system overall yielded inconclusive results for our class. The probability of a positive final test conclusion given a positive PCR reaction is 87% and the probability of a negative final test conclusion given a negative PCR reaction is 77%. The probability that a patient will develop the disease given a positive final test conclusion is 30%, and the probability that a patient will not develop the disease given a negative final test conclusion is 46%. Particularly of concern are the last two calculation results; these show unacceptably low correlations between the PCR test and the development of disease.

To maximize the accuracy and precision of the PCR test, we would have to minimize error through improved experimental design.

Sources of error potentially include contamination of the PCR reaction or any of the primers in a relatively non-sterile environment. To minimize error, we could have performed the experiment under a hood to minimize contamination via pathogens in the air or in other parts of the lab.

However, the largest source of error is likely the mechanism of the PCR reaction itself. The inconclusive results suggest that the positive and negative controls may have been faulty, which would have affected the final test conclusions. The quality of controls may have been a source of error; to rule this out, we would have to run further tests.

Calculation 1: What is the probability that a patient will get a positive final test conclusion, given a positive PCR reaction?

 Variable Description Numerical Values A Positive Final Test Conclusion 0.48 B Positive PCR Reaction 0.49 P(BlA) Probability of a positive PCR reaction (B) given a positive final test conclusion (A) 0.89 P(AlB) Probability of positive final test conclusion (A) given a positive PCR reaction (B) 0.87

There is an 87% chance that if a subject has the disease it will be detected by the PCR test. This is very reliable, but could definitely be improved.

Calculation 2: What is the probability that a patient will get a negative final test conclusion, given a negative diagnostic signal?

 Variable Description Numerical Values A Negative Final Test Conclusion 0.39 B Negative Diagnostic Signal 0.39 P(BlA) Probability of a negative diagnostic signal (B) given a negative final test conclusion (A) 0.77 P(AlB) Probability of negative final test conclusion (A) given a negative diagnostic signal (B) 0.77

There is a 77% chance that if the subject has no disease it will be detected as such by the PCR test. This is reliable, but could definitely be improved.

Calculation 3: What is the probability that a patient will develop the disease, given a positive final test conclusion?

 Variable Description Numerical Values A Development of Disease 0.34 B Positive Final Test Conclusion 0.48 P(BlA) Probability of a positive final test conclusion (B) given development of disease (A) 0.43 P(AlB) Probability of development of disease (A) given a positive final test conclusion (B) 0.30

There is a 30% chance that the patient will develop the disease given a positive final test conclusion. This is not reliable, and suggests a lack of correlation between the PCR test and disease development.

Calculation 4: What is the probability that a patient will not develop the disease, given a negative final test conclusion?

 Variable Description Numerical Values A Negative Disease Development 0.66 B Negative final test conclusion 0.39 P(BlA) Probability of a negative final test conclusion (B) given negative disease development (A) 0.27 P(AlB) Probability of negative disease development (A) given a negative final test conclusion (B) 0.46

There is a 46% chance that a patient will not develop the disease given a negative final test conclusion, which is also inconclusive and suggests a lack of correlation between the PCR test and the disease development.

Which calculation describes the sensitivity of the system regarding the ability to detect the disease SNP? : 1
Which calculation describes the sensitivity of the system regarding the ability to predict the disease? : 3
Which calculation describes the specificity of the system regarding the ability to detect the disease SNP? : 2
Which calculation describes the specificity of the system regarding the ability to predict the disease? : 4

Using Bayesian statistics we can see that overall the PCR is reliable in detecting a disease inside of a patient. However the PCR test severely lacks the ability to predict if the patient will have the disease in the future. Sources of error could include the fact that these patients all have different lives and different factors that may enhance or detract the possibility of contracting the disease. Thus more factors must be taken into account in order to predict the disease. The PCR test may stand up very well as a detection device, but a prediction device must be designed, as the PCR can hardly predict.

## PCR Lab F

Section 1: Computer-Aided Design

1. Which Open PCR parts does each of the 3-D files represent?

- Open PCR Body represents the main body of the PCR machine.

- Open PCR Assembly represents the component which allows for the tubes to be inserted.

- Open PCR Heating: represents the heating component that allows the PCR to be run in the proper cycles.

- Open PCR Lid: represents the lid (top portion) enclosing the machine.

- Open PCR Electronics: represents the hardware component that allows it to be programmable.

- Open PCR Miscellaneous represents the box containing the machine.

Section 2: Your Plan to Design a New Diagnostic System

Part 1: Assess the original design

Consumables:

1. Strength: They are relatively cheap and are convenient. They also ensure that the experiment is not contaminated with other substances because they are not reused, so there is no need to worry about how well it has been cleaned.

2. Weakness: They are wasteful because many may need to be used for a single experiment; for example, we had to use a large amount of the plastic pipettor tips.

OpenPCR Machine:

1. Strength: Reliable, accurate, easy to use with minimal need to input information.

2. Weakness: It is a relatively large machine which takes up space in laboratories and the PCR reaction takes a long time (at least a few hours).

Flourimeter system:

1. Strength: It is convenient and relatively small for its function.

2. Weakness: Since you have to take the images and interpret the data, it requires a time-consuming, inaccurate process with a lot of room for error (especially for beginners).

Part 2: Design a New System

Our Brand Name: The Perfect Package

Note: The TinkerCAD website was down for maintenance from early evening on November 25th until today, December 2nd. We were not able to complete the 3D prototype until the evening of December 2nd when the site's function was restored. We hope that the tardiness of that edit can be waived because of the site's technical difficulties.

Consumables:

We want to package the tubes, tips, micropipettor, PCR mix and primers in a manner tha requires less steps for the user. First of all, we want to package the PCR mix and primers in plastic pipet tips with removable caps on either end instead of tubes. That way, you can attach the tip to the micropipettor, remove the cap, and simply expel the substance into the desired tube. It eliminates the need for the original tubes which were only used for storage. The caps would seal well and avoid any leakage.

Additionally, we would try to eliminate the need for excess consumables by including a container of universal solvent in our product’s consumables kit. We would also include a list of pre-approved substances (such as standard primers) which the chemical would neutralize/“kill” to make the tip able to be used again without cross-contamination.

Hardware - PCR Machine:

We will redesign the PCR machine to be as compact as possible. This will help our customers make the best use of their limited lab space, especially in labs that can be crowded with materials.

Our PCR machine will not need to be linked to a computer; it will have an LED screen on the front from which the user can control the machine. This screen will have a variety of features, and when the PCR is running, will display which step it is at along with temperature and time remaining. This will make it easier and more portable to use.

Our target market of researchers and college students will both benefit from this feature. Additionally, to appeal to the student demographic of our market, we will include some more education-based features. Although we understood the basic processes, it would have been beneficial to know exactly what was happening inside the machine during each step. We will include a feature which, when selected, will have an education screen pop up on the screen. The system will show a detailed description of the specific step the reaction is undergoing, as well as an animation to aid understanding.

This will help students understand in real-time what is happening when they are doing these experiments.

Hardware - Fluorometer:

We will redesign the fluorometer to have an automatic measuring system. The major weakness we noticed was the inaccuracy/imprecision that comes along with capturing our own images and performing the analysis ourselves. The slightest change in distance from the drop or image quality could cause error in the results. Because of this, we will make a fluorometer which contains a small enclosed camera beneath where the glass plate with the drop should be placed. An image can be taken with a button on the side of the machine (after the button is pressed, there will be a five second delay so that the box flap can be closed).

The fluorometer will also contain the ImageJ system so that the image can automatically be analyzed. After the image is taken and the analysis is done, the information and the image can be wirelessly saved to a computer.