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Titel: Fast Methods for Drug Approval: Research Perspectives for Pandemic Preparedness
VerfasserIn: Abdin, Ahmad Yaman
De Pretis, Francesco
Landes, Jürgen
Sprache: Englisch
Titel: International Journal of Environmental Research and Public Health
Bandnummer: 20
Heft: 3
Verlag/Plattform: MDPI
Erscheinungsjahr: 2023
Freie Schlagwörter: computer-generated evidence
decision making
drug approval
evidence synthesis
pandemic
pandemic preparedness
real world evidence
risk attitudes
DDC-Sachgruppe: 500 Naturwissenschaften
Dokumenttyp: Journalartikel / Zeitschriftenartikel
Abstract: Public heath emergencies such as the outbreak of novel infectious diseases represent a major challenge for drug regulatory bodies, practitioners, and scientific communities. In such critical situations drug regulators and public health practitioners base their decisions on evidence generated and synthesised by scientists. The urgency and novelty of the situation create high levels of uncertainty concerning the safety and effectiveness of drugs. One key tool to mitigate such emergencies is pandemic preparedness. There seems to be, however, a lack of scholarly work on methodology for assessments of new or existing drugs during a pandemic. Issues related to risk attitudes, evidence production and evidence synthesis for drug approval require closer attention. This manuscript, therefore, engages in a conceptual analysis of relevant issues of drug assessment during a pandemic. To this end, we rely in our analysis on recent discussions in the philosophy of science and the philosophy of medicine. Important unanswered foundational questions are identified and possible ways to answer them are considered. Similar problems often have similar solutions, hence studying similar situations can provide important clues. We consider drug assessments of orphan drugs and drug assessments during endemics as similar to drug assessment during a pandemic. Furthermore, other scientific fields which cannot carry out controlled experiments may guide the methodology to draw defeasible causal inferences from imperfect data. Future contributions on methodologies for addressing the issues raised here will indeed have great potential to improve pandemic preparedness.
DOI der Erstveröffentlichung: 10.3390/ijerph20032404
URL der Erstveröffentlichung: https://doi.org/10.3390/ijerph20032404
Link zu diesem Datensatz: urn:nbn:de:bsz:291--ds-389989
hdl:20.500.11880/35173
http://dx.doi.org/10.22028/D291-38998
ISSN: 1660-4601
Datum des Eintrags: 13-Feb-2023
Fakultät: NT - Naturwissenschaftlich- Technische Fakultät
Fachrichtung: NT - Pharmazie
Professur: NT - Prof. Dr. Claus Jacob
Sammlung:SciDok - Der Wissenschaftsserver der Universität des Saarlandes

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