MAKE THE PILL FIT THE ILL
Prescription drug side effects are the 4th leading cause of death in the U.S, according to the AMA.
I wondered why people respond differently to the same drugs, and found that genetic mutations affect a person’s response.
However, knowing the mutation only solves half the problem. Doctors need to know if their patients have particular mutations. They need to locate a base change in a 6 billion base genome.
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To address this problem, I innovated a type of computer algorithm, or problem solving procedure, that can find mutations in a genome.
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Research in this area could lead to groundbreaking medical innovations that would alleviate suffering by enabling personalized medicine, allowing doctors to create tailor-made treatments based on an individual’s unique genetic composition.
HOW IT WORKS
Doctors can use string searching algorithms to find mutations. String searching algorithms are computer programs that find a string of letters in a text. The genome is the text, and the mutation is the string.
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The problem with most existing string searching algorithms is that they are too slow. Speed is vital in emergency situations such as seizure or allergic shock when the correct drug must be prescribed immediately.
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To address this problem, I implemented the Reverse Factor algorithm and parallelized it, or coded it to run on multiple computer processors. This has not been done for this algorithm. How does parallelism make an algorithm faster?
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A parallel program divides the task of searching a genome by making multiple processors work together on a problem. This reduces the time needed to obtain the solution.
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Parallelizing the Reverse Factor algorithm accelerated the original by 400 percent, suggesting its feasibility. My results suggest that a string searching algorithm like mine can save lives by advancing the field of personalized medicine and enabling doctors to predict a patient’s response.