1.
Nijsingh, Niels, 1977, et al.
(author)
Managing pollution from antibiotics manufacturing: charting actors, incentives and disincentives
2019
In: Environmental health. - : Springer Science and Business Media LLC. - 1476-069X. ; 18
Journal article (peer-reviewed) abstract
Background Emissions of high concentrations of antibiotics from manufacturing sites select for resistant bacteria and may contribute to the emergence of new forms of resistance in pathogens. Many scientists, industry, policy makers and other stakeholders recognize such pollution as an unnecessary and unacceptable risk to global public health. An attempt to assess and reduce such discharges, however, quickly meets with complex realities that need to be understood to identify effective ways to move forward. This paper charts relevant key actor-types, their main stakes and interests, incentives that can motivate them to act to improve the situation, as well as disincentives that may undermine such motivation. Methods The actor types and their respective interests have been identified using research literature, publicly available documents, websites, and the knowledge of the authors. Results Thirty-three different actor-types were identified, representing e.g. commercial actors, public agencies, states and international institutions. These are in complex ways connected by interests that sometimes may conflict and sometimes pull in the same direction. Some actor types can act to create incentives and disincentives for others in this area. Conclusions The analysis demonstrates and clarifies the challenges in addressing industrial emissions of antibiotics, notably the complexity of the relations between different types of actors, their international dependency and the need for transparency. The analysis however also suggests possible ways of initiating incentive-chains to eventually improve the prospects of motivating industry to reduce emissions. High-resource consumer states, especially in multinational cooperation, hold a key position to initiate such chains.
2.
3.
Troein, Margareta, et al.
(author)
Läkemedel som hot
2018
In: AllmänMedicin. - 0281-3513. ; 39:4, s. 39-42
Journal article (other academic/artistic) abstract
Problemet med förfalskade läkemedel är stort globalt. Patienter med svårbedömdasymtom kan ha biverkningar av sådana. Läkare behöver vara mer medvetna om förekomsten av förfalskade läkemedel, och veta hur de ska handskas med problemet.
4.
Bergman, Erik, et al.
(author)
A natural language processing approach towards harmonisation of European medicinal product information
2022
In: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 17:10
Journal article (peer-reviewed) abstract
Product information (PI) is a vital part of any medicinal product approved for use within the European Union and consists of a summary of products characteristics (SmPC) for healthcare professionals and package leaflet (PL) for patients, together with the product packaging. In this study, based on the English corpus of the EMA product information documents for all centrally approved medicinal products within the EU, a BERT sentence embedding model was used together with clustering and dimensional reduction techniques to identify sentence similarity clusters that could be candidates for standardization. A total of 1258 medicinal products were included in the study. From these, a total of 783 K sentences were extracted from SmPC and PL documents which were aggregated into a total of 284 and 129 semantic similarity clusters, respectively. The spread distribution among clusters shows separation into different cluster types. Examples of clusters with low spread include those with identical word embeddings due to current standardization, such as section headings and standard phrases. Others show minor linguistic variations, while the group with the largest variability contains variable wording but with significant semantic overlap. The sentence clusters identified could serve as candidates for further standardization of the PI. Moving from free text human wording to auto-generated text elements based on multiple-choice input for appropriate parts of the package leaflet and summary of product characteristics, could reduce both time and complexity for applicants as well as regulators, and ultimately provide patients and prescribers with documents that are easier to understand and better adapted for search availabilities.
