In the past decade, the volume, variety, and velocity of amassed data relevant to healthcare have reached staggering levels. This data has come in the form of numerous sources such as electronic health records, genome sequencing, pharmaceutical research. This recent rise of big data in healthcare has enabled the rise of new healthcare research methods. One of these emerging methods is known as drug repositioning (also commonly known as drug repurposing) and is the process of finding new clinical applications for existing FDA-approved drugs that have previously been approved for a different indication (Naveja et al., 2016). This process often leverages big data sources containing information about specific drugs and diseases and utilizes specialized algorithms and bioinformatics techniques to find unknown connections between certain drugs and diseases.
The traditional drug discovery process often amasses substantial costs, faces high attrition rates, progress at an extremely slow pace, and has no guarantee of receiving FDA approval by the end of the process. On average, the total cost and timeframe of drug discovery are $2.6 billion and at least 10 years (PhRMA, 2015). Alternatively, drug repositioning has become an increasingly attractive approach to pharmaceutical development and drug discovery because it has the potential to circumvent these obstacles by utilizing “de-risked” FDA-approved compounds, employing lower-cost computational research methods, and necessitating shorter development timelines (Pushpakom et al, 2019). Used effectively, drug repositioning can save a lot of money, time, and lives.
One potential application of drug repositioning research is in neurodegenerative diseases, which are diseases that primarily affect neurons in the brain. Many of these diseases manifest themselves through complex mechanisms that can impair memory, cognition, and movement. Huntington’s Disease (HD) is a fatal genetic progressive neurodegenerative disease that causes the progressive breakdown of neurons in the brain. This disease is caused by a trinucleotide repeat disorder known as a CAG repeat. This means that, due to a mutation in a person’s DNA, a set of code in the DNA erroneously repeats itself an excessive number of times. These mutations lead to the production of deformed, highly reactive proteins that can cause neuronal dysfunction, degeneration, and death. The number of repetitions varies from person to person, and longer repeat chains tend to cause the onset of HD to occur earlier in life. Symptoms include loss in motor function, personality and behavioral changes, decline in cognitive function, severe weight loss, and suicidal ideation (Heemskerk and Roos, 2012). One unique facet of the disease is that symptoms generally do not begin to appear until ages 30-50 and worsen over the course of a 10-25-year period. HD is also an autosomal dominant hereditary disease, meaning that any parent who is a carrier of the genetic disorder has a 50% chance or higher of passing the gene to his/her child. The high transmission rate, coupled with the prolonged symptoms of the disease, makes HD a devastating disease for families, as individuals are often unaware of their HD disease until after they have already had offspring. Currently, there are approximately 30,000 symptomatic HD patients and more than 200,000 individuals at risk for developing HD. The disease is also significantly more frequent in Western countries. There is no known cure for the disease, and the only focus of treatment is managing symptoms.
The goal of this Honors Thesis project is to utilize basic drug repositioning methods to develop a disease profile for HD and curate a set of drugs that can be tested and validated for HD treatment in future experiments.