The Science of Supply: Applying Diffusion Models to Predict and Prevent Drug Shortages
Open Access DepositedThis praxis investigates the persistent issue of drug shortages, focusing specifically on shortages driven by supply and demand imbalances in the pharmaceutical industry. The research analyzes factors that lead to these imbalances, such as demand surges for drugs with multiple approved indications and complex supply chain dynamics. This study’s purpose is to develop strategies that use predictive analytics to prevent drug shortages, improve pharmacoeconomic outcomes, and enhance patient care through better supply chain management. The praxis proposes a predictive model designed to accurately forecast pharmaceutical supply needs that is refined and validated by incorporated historical units sold data. The research employs various diffusion models—such as the Bass and Gompertz—to capture the dynamics of drug adoption and market penetration. This ensures the predictive model's relevance across different scenarios and market conditions. Ultimately, the praxis aims to contribute to the pharmaceutical industry by providing insights into managing supply chain vulnerabilities and developing robust forecasting tools that help anticipate and mitigate potential drug shortages.
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