Fast Methods for Drug Approval: Research Perspectives for Pandemic Preparedness

Int J Environ Res Public Health. 2023 Jan 29;20(3):2404. doi: 10.3390/ijerph20032404.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Disease Outbreaks
  • Drug Approval
  • Emergencies*
  • Humans
  • Pandemics* / prevention & control
  • Public Health

Grants and funding

Ahmad Yaman Abdin received funding from the Saarland University and the Landesforschungsförderungsprogramm of the State of Saarland (Grant No: WT/2—LFFP 16/01), Francesco De Pretis acknowledges funding from the European Research Consortium for Informatics and Mathematics. Jürgen Landes gratefully acknowledges NextGenerationEU funding for the project “Practical Reasoning for Human-Centred Artificial Intelligence”.