In 2016 there were roughly 77,000 PrEP users in the United States, while over 1.2 million Americans were identified as “high-risk” for HIV infection. The reasons for this discrepancy are vast; however, potential reasons that have been identified are stigma, ineffective or poorly targeted marketing, access, and cost, amongst other factors. This pilot project seeks to understand the ways in which people and companies talk about PrEP on social media to glean deeper insights on methods to increase PrEP use. The increased use of social media gives researchers, clinicians, policymakers, and health organizations the opportunity to have access to real time data and potentially influence awareness of PrEP. This inductive exploratory study uses natural language processing (NLP) and content analysis to examine the ways in which people are using social media to talk about PrEP. An R script was utilized to crawl Twitter the Twitter API based on keywords related to PrEP and HIV, plus all lemmatized variations related to the word pair. Data cleaning was then performed to remove tweets that were not in English, tweets that had been retweeted, as well as removing any identifying information. The resulting data frame was then used both qualitatively and quantitatively for analysis. Qualitative analysis involved a comprehensive reading of tweets, development of a category dictionary, and identification of themes that would help to train an algorithm to automatically process and count tweets based on its category. The quantitative process involved further cleaning and removing of stop-words to develop a Ngram frequency cloud as well as development of a process to automatically categorize the different types of tweets based on the type of tweet (advertisement, question about PrEP, comment on cost or availability, criticism of manufacturer, etc.). This processes resulted in identification of 587 unique HIV related PrEP tweets. Qualitative insights from this reduced dataset indicated that there are preventative concerns related to access and cost which may be preventing high-risk individuals from getting PrEP. Algorithmic sorting and categorization processes also identified concerns about targeted marketing, specifically the lack of campaigns focusing on transgender, female, and minority communities. Our bootstrap method of training and testing resulted in a process that had an 80% likelihood of identifying, analyzing, and classifying HIV related PrEP tweets. Once classified, 40% of tweets were advertising and messaging, the rest were concerns about cost (31%), requests for info/ways to pay for PrEP (20%), as well as other non-classified comments. There are a number of different conversations about HIV/PrEP awareness happening on Twitter. However, access and cost were consistently the most common themes being discussed. Currently, a 30-day supply of PrEP costs between $0-$1600, in the US, which may be creating a substantial barrier to further reducing HIV rates. Additionally, Improving online marketing strategies of PrEP could increase awareness and use by offering targeted information as well as identification of local resources to those interested or in need.