Advancing Pharmacovigilance: An Analysis of the State-of-the-art and the Market Opportunities of Innovative Software for Automated Case Data Intake and Processing
dc.contributor.author | Braga de Melo, Paulo Humberto | |
dc.contributor.mentor | Martin, Andreas | |
dc.contributor.mentor | Pande, Charuta | |
dc.date.accessioned | 2024-12-03T19:39:10Z | |
dc.date.available | 2024-12-03T19:39:10Z | |
dc.date.issued | 2024 | |
dc.description.abstract | In the current global pharmaceutical landscape, specialized information systems such as Argus Safety, ArisGlobal, Veeva Safety, and RxLogix PVCM Tool play a crucial role in pharmacovigilance (PV). Despite their widespread adoption in pharmaceuticals, these systems have significant limitations, leading to repetitive manual tasks and high operational costs associated with PV case data intake and processing. These inefficiencies present market opportunities for new PV software businesses. By leveraging advanced automation, artificial intelligence, machine learning, and other modern technologies, new solutions can better address these operational challenges. This study examines the global market landscape of leading pharmacovigilance systems, critically assesses their shortcomings, and proposes innovative PV software designed to meet key market needs for case intake and case processing. | |
dc.identifier.uri | https://irf.fhnw.ch/handle/11654/49260 | |
dc.language.iso | en | |
dc.publisher | Hochschule für Wirtschaft FHNW | |
dc.spatial | Olten | |
dc.subject.ddc | 330 - Wirtschaft | |
dc.title | Advancing Pharmacovigilance: An Analysis of the State-of-the-art and the Market Opportunities of Innovative Software for Automated Case Data Intake and Processing | |
dc.type | 11 - Studentische Arbeit | |
dspace.entity.type | Publication | |
fhnw.InventedHere | Yes | |
fhnw.StudentsWorkType | Master | |
fhnw.affiliation.hochschule | Hochschule für Wirtschaft FHNW | de_CH |
fhnw.affiliation.institut | Master of Science | |
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relation.isMentorOfPublication | 6fa75258-21bd-4090-98cb-b2217a6f234d | |
relation.isMentorOfPublication.latestForDiscovery | 6a3865e7-85dc-41b5-afe3-c834c56fab4e |