Fast Methods for Drug Approval: Research Perspectives for Pandemic Preparedness

Ahmad Yaman Abdin (), Francesco De Pretis and Jürgen Landes
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Ahmad Yaman Abdin: Division of Bioorganic Chemistry, School of Pharmacy, Saarland University, D-66123 Saarbrucken, Germany
Francesco De Pretis: Department of Communication and Economics, University of Modena and Reggio Emilia, 42121 Reggio Emilia, Italy
Jürgen Landes: Department of Philosophy “Piero Martinetti”, University of Milan, 20122 Milan, Italy

IJERPH, 2023, vol. 20, issue 3, 1-17

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.

Keywords: computer-generated evidence; decision making; drug approval; evidence synthesis; pandemic; pandemic preparedness; real world evidence; risk attitudes (search for similar items in EconPapers)
JEL-codes: I I1 I3 Q Q5 (search for similar items in EconPapers)
Date: 2023
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