Smart Innovation
Antimicrobial resistance (AMR)
AMR develops when bacteria, fungi or viruses are exposed to antibiotics, antifungals or antivirals. As a result, the antimicrobials become ineffective and infections may persist. In addition, medical interventions including surgery, chemotherapy and stem cell therapy may become impossible.
AMR is considered the biggest global threat of Health and Food Safety.
AMR Insights
For Researchers and Entrepreneurs who wish to investigate, develop and commercialize novel vaccines, diagnostics and antimicrobials to prevent Antimicrobial resistance, AMR Insights offers selected, global information and data, specific education and extensive networking and partnering opportunities.
AMR Insights is for:
- Researchers at Universities and University Medical Centers
- Researchers at Research Institutes
- R&D professionals in Pharma, Biopharma and Diagnostics companies
- Entrepreneurs in start-up’s and spin off companies
- Innovators, Venture Capitalists.
Latest Topics
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18 April 2024Decision support systems for antibiotic prescription in hospitals: a survey with hospital managers on factors for implementation
This research examines the implementation factors of artificial intelligence-based decision support systems for antibiotic prescription in German hospitals. An online survey was conducted between December 2022 and May 2023, analyzing responses from 118 respondents. Results showed openness towards AI-based systems, but little self-perceived knowledge in this field. The study highlights the importance of user-friendliness, compatibility […]
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18 April 2024Crowdsourcing for mining new fungal sources for addressing the need for novel antibiotics against multidrug resistant pathogens
To address the health issue brought on by the emergence and dissemination of antimicrobial resistant (AMR) bacteria, including multidrug-resistant (MDR), extensively drug-resistant (XDR), and pan-drug-resistant (PDR) strains, there aren’t many new antibiotics available. Using both new and less common older techniques, bioprospecting fungus from less studied and severe settings may reveal potential antibiotics to treat […]
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17 April 2024Machine learning to predict antimicrobial resistance: future applications in clinical practice?
This review explores the use of machine learning (ML) in predicting antimicrobial resistance (AMR). The review included 36 studies, primarily based on hospital and outpatient data, with the majority conducted in high-resource settings. The studies focused on predicting drug resistance in infected patients, ML-assisted antibiotic prescription, and colonization with carbapenem-resistant bacteria. The most common inputs […]
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