PharmaBlock - A Reliable and Intelligent Platform for Pharmaceutical Data Analytics

Abstract

Recently, blockchain technology was introduced to the public to provide a secure environment that is an immutable, consensus-based and transparent system in the finance technology world. However, blockchain is also being applied to other fields where trust and transparency are needed. The need for the reliable sharing of pharmaceutical information between various stakeholders is essential. The usage of blockchain technology adds traceability and visibility to supply chains such as pharmaceutical supply chains and provides all information from end to end. Currently, data is either stored and managed by large manufacturers and pharmacy retailers using their own centralized system. Several existing approaches and methods that allow pharmaceutical information to be stored and shared between the healthcare provider and other stakeholders in a centralized manner have been discussed in the literature. These methods are not very useful in terms of data utility. Blockchain technology offers a distributed framework that can positively affect the process of assembling and sharing pharmaceutical information between the relevant stakeholders, such as the U.S Food and Drugs Administration (FDA), manufacturers, distributors, pharmacy retailers and researchers. In this research, we propose the PharmaBlock blockchain framework as the base of the data flow of pharmaceutical supply chain information to create transparent drug transaction data. To identify the shortcomings of the existing approaches in the area of the pharmaceutical supply chain, we conducted a systematic literature review (SLR) to deeply understand the problems and the solutions that are being used to overcome such challenges. By applying the SLR approach, 16 relevant studies were identified and systematically reviewed in this thesis. In the current literature, there is no model that uses artificial intelligence techniques to store pharmaceutical supply chain information on-the-fly to make decisions and control entities end-to-end. In this research, we investigate the use of AI methods to address the aforementioned research issues and make decisions intelligently. The intelligence built into PharmaBlock provides automated and reliable mechanisms to perform the following: • classify the stored data to allocate and give different accessibility levels for data • alert pharmacies to accelerate the process of selling nearly expired drugs • determine an optimal selling price for a drug in a decentralized marketplace • determine future drugs demand to reduce wastage. The thesis concludes with possible solutions to the identified research questions and the time frames for addressing these issues.