Calculating a Severity Score of an Adverse Drug Event Using Machine Learning on the FAERS Database

An Adverse Drug Event (ADE) is a medical injury that can result from a prescription or over the counter drug that causes an allergic reaction, overdose, reaction with other drugs or is the result of a medication error. Vulnerable populations such as children and the elderly are most susceptible to ADEs. This lack of standardized data has kept FAERS from fulfilling its full potential as a pharmacovigilance tool and its limitations have been the subject of numerous studies. Our motivation is to improve drug safety by creating a new type of pharmacovigilence system that 1. Performs data cleaning and standardization of FAERS data, 2. Computes a drug reaction severity score for each ADE based on the reported indications and coded using a modified Hartwig Severity scale, 3. Models the data to A) empirically identify drug-interaction events and their relative strength of event in specific symptom-related incidents and to B) identify drug-disease event severity for specific indications such as hypertension, stroke and cardiac failure, 4. Computes a predicted severity score for the models using machine learning algorithms 5. Evaluates the accuracy of the predicted severity score versus actual severity on a holdout dataset, and 6. Builds a predictive clinical tool for physicians that can interact with a patient’s EHR and identify adverse reaction potential at the point of prescription. We propose a global data-driven approach with the TylerADE System. This system uses advanced machine-learning techniques to sift through data and uncover potentially unknown drug events. This research has the potential to 1) improve the efficiency of pharmacological research by identifying potentially unknown n-drug events that merit further study; 2) create a risk score of potential medication events that physicians can use in a clinical setting; and 3) improve patient safety

Making Homes in Un-Homelike Places among Young People in Vancouver: Implications for Homelessness Prevention

This article explores the experiences of young people navigating an evolving system of housing and homelessness services in Vancouver, Canada. Despite recent shifts toward Housing First policies and calls for prevention-oriented initiatives, many young people continue to rely on temporary emergency accommodations. Amid a surge in youth homelessness and unstable housing in Vancouver, our study examines young people’s “homing” strategies across time and place and temporary and more permanent living environments. We draw from an ongoing ethnographic study that began in 2021 and has involved over 70 interviews and 100 h of fieldwork with 54 young people aged 19 to 29. Our findings emphasize that feeling at home extends beyond having a roof over one’s head for an extended period of time. A focus on homing strategies—that is, the day-to-day practices, routines, and forms of sociality that generate a sense of stability and care even in un-homelike places—highlights how young people can be better supported in making themselves at home in the places where they live, potentially preventing returns to street-based homelessness. This study contributes insights to youth homelessness prevention policies, urging a strengths-based approach that aligns with young people’s needs, priorities, and desires for homemaking