Periodic Reporting for period 4 - COMBINE (Collaboration for Prevention and Treatmentof MDR Bacterial Infections)
Reporting period: 2022-11-01 to 2023-10-31
The SIGs have been setup to get the most of ongoing research within the AMR Accelerator and to facilitate cross-project panel discussion on topics of interest to all. In Period 4, COMBINE has hosted and moderated 13 SIG meetings or which 3 in person. These include the following SIG’s: a) Machine Learning SIG; b) Animal Models SIG and c) Science Communication SIG. These SIG’s create communities of experts and practice from the whole AMR Accelerator and will results in tangible outcomes, including publications and White Papers.
Achieving effective management of scientific data: COMBINE has developed a robust data management process and will continue to improve on this process. The software developed within COMBINE will support a wide range of data formats, from simple office documents and chemical structures to preclinical and clinical data sets, while retaining compatibility with all common operating systems. To facilitate data management, a cloud based electronic lab notebook system has been introduced by COMBINE for collection, analysis, storage and management of results at AMR Accelerator partner sites. This is complemented by a central data repository for sharing, aggregating, integrating and analysing data. Documentation covering data governance, quality, access, and analysis procedures has been developed and shared with the projects within the Accelerator. During period 4, COMBINE has continued to support data management across the AMR Accelerator, streamlining data governance in the projects and oversees the implementation of FAIR processes and software tools to support the day-to-day operation of individual AMR Accelerator projects. In particular, in Period 4, COMBINE has performed data set maturity analyses for eight consortia to identify FAIR status and specific actions needed to elevate the towards the general goal of community compatible resources (DSM level 3). Further development of Knowledge graphs to integrate external (PibChem, ChEMBL, Uni Queensland) data sets with internal MIC results. The GRIT software has been rolled out to internal project teams and is being used to capture production data from WP5 in-vivo model studies.
Managing the communication: COMBINE works to strengthen the interaction between AMR Accelerator participants and AMR stakeholders across the EU and globally. COMBINE has established a strong AMR Accelerator identity, with project logos and an engaging and informative joint website. In Period 4 of the project, COMBINE started implemented the mid-term updates made in the communications strategy and plan. The project has promoted the AMR Accelerator to the external scientific community and the general public, using social media profiles on Twitter (now X), LinkedIn and YouTube, maintaining and updating the AMR Accelerator website, producing communication materials (including videos, brochures, flyers, slide decks and poster templates) to inform about the AMR Accelerator programme and raise awareness of project activities, and continuing to publish editions of an AMR Accelerator external newsletter. Based on a SWOT analysis from the cross-project meeting in March 2023 and input from all 9 projects, we are writing a joint opinion paper on the benefits and challenges faced within the AMR Accelerator.
Improving clinical trials and standardising an animal infection model: In terms of the scientific goals of the project, COMBINE has progressed towards the capability building objectives of the project. With the aim to identify promising strategies to improve translation from preclinical models to successful clinical trials for products against AMR infections, common problems in the preclinical (including animal infection models) and clinical development of vaccines and antibiotics have been collected. In Period 4, COMBINE has successfully acquired individual participant level data from two development programs and initiated the re-analysis of such data. Moreover, we are using information from additional sources (published literature, EMA Scientific Advice letters) to integrate and expand our knowledge about possible pitfalls and mitigation strategies in translation and clinical trials. The developed infection model protocol has been successfully implemented in three different labs using sharable bacterial strains, deposited in a public biorepository. The collaboration with some of the main actors in the field of animal infection models was further established.
Network: A knowledge base and interpersonal network will develop between AMR Accelerator participants and AMR stakeholders across the EU and globally, which will be important for future contacts and potential collaborations in the AMR community. COMBINE will be instrumental in ensuring that these ties will remain.
Improving clinical trials and standardising animal models: COMBINE will contribute to improve design of clinical trials and develop more predictive and reliable infection models for preclinical studies, to accelerate antibacterial drug and vaccine development.