COMBINE delivers capacity building and support for the AMR Accelerator
COMBINE conducts research and develops tools, resources and infrastructures to strengthen European capacity for antibiotic development. In addition, COMBINE provides coordination and support for the IMI-funded AMR Accelerator umbrella programme, bringing nine projects together in a joint mission to accelerate the development of new medicines to treat or prevent resistant bacterial infections.
How does COMBINE build capacity for AMR research?
COMBINE develops and provides tools and resources that drive innovation in antibiotic research and development, supports drug discovery through machine learning models, FAIR data management tools, and a pneumonia infection model with validated and virulent bacterial strains and pharmacokinetic and pharmacodynamic (PK/PD) data. By the end of the project, COMBINE will share their model-based translational approaches to the AMR community, and publish findings on predictors of vaccine response and the main clinical trial challenges for vaccines and monoclonal antibodies against ESCAPE pathogens. Together, these efforts will inform future clinical trial design and support development of safe and effective medicines to address the growing challenge of AMR.
Together, the COMBINE Pneumonia Model, the IMI COMBINE Preclinical Bacterial Strain Repository, FAIR data management tools and the AMR-KG machine-learning (ML) model provide tools and resources that support antibiotic development. The knowledge developed across the project supports European capacity for AMR research, training a new generation of AMR experts engaged in the fight against drug resistance.
How does COMBINE support the AMR Accelerator?
COMBINE enables effective collaboration across the AMR Accelerator by providing a coordination framework, structures for FAIR data management, and communication support. Scientific Interest Groups create synergies across projects in the development of animal models, machine learning, and science communication.
COMBINE provides collaborative spaces through:
(1) Annual cross-project meetings, where projects join forces to drive collaboration and discuss sustainability; (2) Regular coordination committee meetings, creating a space for project leaders and coordinators to meet and align plans and strategies;(3) Regular meetings to discuss FAIR data management, where COMBINE supports FAIR data assessments and provides guidance; (4) Communication support structures, where communication champions from all projects collaborate to maximise the AMR Accelerator’s visibility and legacy.
Tools and resources from COMBINE
Access COMBINE resources
COMBINE resources are linked from this page. They have also been integrated into the AMR Accelerator results catalogues, published in scientific journals, and disseminated through the COMBINE Zenodo community.
COMBINE publications in scientific journals
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Stojkov, I., Marchioro, L., Bekeredjian-Ding, I., & Hofner, B. Pooled analyses of Clostridioides difficile vaccine trials identify baseline predictors for vaccine response. Scientific Reports. 2026 doi.org/10.1038/s41598-026-42375-5
- Hansen JU, Arrazuria R, Hoover JL, Kerscher B, Huseby DL, Sordello S, Gribbon P, Gadiya Y, Berlin Lv, Witt G, Tassi N, Rosenborg F, Cao S, Bekeredjian-Ding I, Lindahl O, Hughes D, Friberg LE, Vingsbo Lundberg C. The COMBINE pneumonia model: a multicenter study to standardize a mouse pneumonia model with Pseudomonas aeruginosa and Klebsiella pneumoniae for antibiotic development. Microbiol Spectr. 2026 Jan 14:e0346425. doi: 10.1128/spectrum.03464-25. Epub ahead of print. PMID: 41532788.
- Vera-Yunca D, Matias C, Vingsbo Lundberg C, Friberg LE. Model-based translation of the PKPD-relationship for linezolid and vancomycin on methicillin-resistant Staphylococcus aureus : from in vitro time–kill experiments to a mouse pneumonia model. Journal of Antimicrobial Chemotherapy, Volume 80, Issue 7, July 2025, Pages 1860–1868, doi:10.1093/jac/dkaf140
- Gadiya Y, Genilloud O, Bilitewski U, et al. Predicting Antimicrobial Class Specificity of Small Molecules Using Machine Learning. Journal of Chemical Information and Modeling. 2025:65(5);2413-2416. doi:10.1021/ACS.JCIM.4C02347
- Fernow J, Olliver M, Couet W, et al. The AMR Accelerator: from individual organizations to efficient antibiotic development partnerships. Nature Reviews Drug Discovery 24, 1-2(2025). doi:10.1038/d41573-024-00138-9. Green Open Access available through DiVA.
- Arrazuria R, Kerscher B, Huber KE, et al. Expert workshop summary: Advancing toward a standardized murine model to evaluate treatments for antimicrobial resistance lung infections. Frontiers in Microbiology. 2022;13:988725. doi:10.3389/fmicb.2022.988725
- Arrazuria R, Kerscher B, Huber KE, et al. Variability of murine bacterial pneumonia models used to evaluate antimicrobial agents. Frontiers in Microbiology. 2022;13:988728. doi:10.3389/fmicb.2022.988728
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Bekeredjian-Ding I. Challenges for Clinical Development of Vaccines for Prevention of Hospital-Acquired Bacterial Infections. Frontiers in Immunology. 2020;11:533705. doi:10.3389/FIMMU.2020.01755
Biorepositories and data
- Data for study “A Multicenter Study to Standardize a Mouse Pneumonia Model with Pseudomonas aeruginosa and Klebsiella pneumoniae for Antibiotic Development”. Available for download from Zenodo. doi:10.5281/zenodo.15124940
- Data Survey that collects relevant project and data set information to set up a Data Management Plan that can serve as an input for Lab Data Template development.
- Lab Data Templates facilitate the collection of AMR research data (in vivo and in vitro) in several sub-tables. The Excel format is compatible with upload procedures into the data repository ‘grit’ and serves as input for a knowledge graph workflow.
- Data Dictionary is connected to the Lab Data Templates and ensures harmonized data entries. In addition, the dictionaries collect metadata beyond the content of the Lab Data Template (e.g. bacterial strain information or compound information) and link to ontologies where possible.
- FAIR assessments have been used as a primer for improving the template. This report is generated using the FAIR-DSM model.
- The IMI COMBINE Preclinical Bacterial Strain Repository (PBSR) is hosted by the Paul-Ehrlich-Institute (PEI) and contains bacterial pathogens evaluated in the COMBINE pneumonia infection model as reference strains for preclinical efficacy studies. The following strains are deposited with DSMZ and can be ordered from them.
Poster presentations
- Hansen JU, Mak WY, Vera-Yunca D, Tassi N, Kerscher B, Hoover JL, Sordello S, Vingsbo Lundberg C, Friberg LE. Advancing the COMBINE pneumonia model: PK/PD evaluation of meropenem and levofloxacin against standardized K. pneumoniae and P. aeruginosa strains in two independent laboratories. Poster presented at: ESCMID Global 2026, Munich, Germany, 17-21 April 2026. Zenodo. 2026. doi:10.5281/zenodo.22643609
- Vingsbo Lundberg C, Vera-Yunca D, Arrazuria R, Kerscher B, Hoover JL, Tassi N, Sordello S, Bekeredjian-Ding I, Hughes D, Friberg LE, Hansen JU. (2026). The COMBINE Pneumonia Model: Multicenter Confirmation of Virulence (Version v1). 10th AMR Conference: Novel Antimicrobials and AMR Diagnostics (AMR Conference), Basel, Switzerland. Zenodo. https://doi.org/10.5281/zenodo.19604414
- von Berlin, L., Gadiya, Y., Fernow, J., Deroose, F., & Gribbon, P. (2026). Tackling the Gram-Negative Permeability Barrier Through Collaborative Data-Driven Prediction (Version v1). 10th AMR Conference: Novel Antimicrobials and AMR Diagnostics (AMR Conference), Basel, Switzerland. Zenodo. https://doi.org/10.5281/zenodo.19221951
- Matias, C. S., Vera-Yunca, D., Friberg, L. E., Vingsbo Lundberg, C. (2025) Development of a Murine Pneumonia Model with Methicillin-resistant Staphylococcus aureus (MRSA) to Evaluate Antibiotic Treatments, presented at the ESCMID Global 2025, Vienna, Austria. doi: 10.5281/zenodo.1766873
- Stojkov, I., Hofner, B. (2025) Exploring the Association Between Study Characteristics and Post-Vaccine Immunogenicity for C. diff: Data-Driven Analyses of Two Vaccine Trials, presented at the 9th AMR Conference, Basel, Switzerland doi:10.5281/zenodo.17661462
- Fernow, J., Robijns, C., Vingsbo-Lundberg, C., Deroose, F., Sjöquist, M. (2024) Communicating about animal research in antibiotics drug development, presented at the Uppsala Antibiotic Days, Sweden. doi:10.5281/zenodo.17433406
- Vera-Yunca, D., Friberg, L. E. (2024) Assessing clinical outcomes of nosocomial pneumonia patients with a pharmacometric multistate model, presented at the thirty-second PAGE Meeting, Rome, Italy 2024. doi:10.5281/zenodo.17660403
- Vera-Yunca, D., Friberg, L. E. (2024) A multistate model for the analysis of clinical outcomes in nosocomial pneumonia patients, presented at the thirty-second PAGE Meeting, Rome, Italy 2024.
- Gadiya, Y., Zaliani, A., Gribbon, P. (2024) Prediction of anti-bacterial class specificity of compounds using machine learning, presented at the 8th AMR Conference, Basel, Switzerland. doi:10.5281/zenodo.17650768
- Kerscher, B., Arrazuria, R., Vingsbo Lundberg, C., Hansen, J. U., Hoover, J. L., Sordello, S., Gribbon, P., Hughes, D., Friberg, L. E., Bekeredjian-Ding, I. (2024) The COMBINE Preclinical Bacterial Strain Repository (PBSR): a new resource for preclinical lung infection models to assess antibiotic efficacy, presented at the 8th AMR Conference, Basel, Switzerland. doi:10.5281/zenodo.17650328
- Stojkov, I., Marchioro, L., Hue Kästel, P. K., Kerscher, B., Hofner, B., Bekeredjian-Ding, I. (2024) Exploring challenges in vaccine development for ESCAPE pathogens: a study of regulatory interactions between developers and regulators, presented at the 8th AMR Conference, Basel, Switzerland. doi:10.5281/zenodo.17649976
- Vingsbo Lundberg, C., Hansen, J. U., Vera, D., Arrazuria, R., Kerscher, B., Hoover, J. L., Sordello, S., Bekeredjian-Ding, I., Hugues, D., Friberg, L. E. (2024) A standard protocol for the murine pneumonia model to investigate antibiotic treatment effect of MDR bacteria infections, presented at the 2024 Gordon Research Conference on Innovative Approaches in Antibacterial Research and Development to Fight the Antibiotic Resistance Crisis, Ventura, United States. doi:10.5281/zenodo.17647969
- Vingsbo Lundberg, C., Hansen, J. U., Vera, D., Arrazuria, R., Kerscher, B., Hoover, J. L., Sordello, S., Bekeredjian-Ding, I., Hughes, D., Friberg, L. E. (2023) Evaluation of a standard protocol for the murine pneumonia model to investigate antibiotic treatment effect of infections with MDR Gram negative bacteria, presented at the 2023 Joint ESCMID/ASM Conference, Boston, US. doi:10.5281/zenodo.17423535
- Stojkov, I., Marchioro, L., Hue Kästel, P. K., Hofner, B., Bekeredjian-Ding, I. (2023) Assessing regulatory communications in vaccine development against emerging pathogens: A pilot study, presented at the 2023 Fraunhofer CIMD Summer School, Leipzig, Germany. doi:10.5281/zenodo.17422964
- Vera-Yunca, D., Friberg, L. E. (2023) A translational semi-mechanistic pharmacokinetic-pharmacodynamic framework to design animal studies: Application to linezolid and vancomycin, presented at 31st PAGE Meeting 2023, Palexco A Coruña, Spain. doi:10.5281/zenodo.17415432
- Hansen, J. U., Arrazuria, R., Kerscher, B., Hoover, J. L., Vingsbo Lungberg, C., Sordello, S., Aranzana-Climent, V., Bekeredjian-Ding, I., Hughes, D., Gribbon, P., Friberg, L. E. (2022) A standard protocol for the murine pneumonia model to evaluate treatments for AMR lung infections, presented at the 2022 ESCMID/ASM Joint Conference, Dublin, Ireland, and at the 7th AMR Conference, Basel, Switzerland. doi:10.5281/zenodo.17669828
- Marchioro, L., Huber, K. E., Hofner, B., Kerscher, B., Arrazuria, R., Bekeredjian-Ding, I. (2022) Recurring problems and mitigation strategies in the development of monoclonal antibodies against AMR pathogens: a report from the COMBINE expert workshop, presented at the 2022 ESCMID/ASM Joint Conference, Dublin, Ireland. doi:10.5281/zenodo.17415153
- Gadiya, Y., Arrazuria, R., Hansen, J. U., Welter, D., Xu, F., Rocca-Serra, P., Juty, N., Gribbon, P. (2022) BPO: the Bioassay Protocol Ontology, a semantic approach to elevate reusability of AMR-related drug discovery data, presented at the 2022 ESCMID/ASM Joint Conference, Dublin, Ireland. doi:10.5281/zenodo.17395047
- Vingsbo Lundberg, C., Arrazuria, R., Kerscher, B., Huber, K. E., Hoover, J. L., Hansen, J. U., Sordello, S., Renard, S., Aranzana-Climent, V., Hughes, D., Gribbon, P., Friberg, L. E., Bekeredjian-Ding, I. (2022) A standardized murine pneumonia model to evaluate antibiotic treatments, presented at the Gordon Research Conference on Disruptive Antibiotics and Non-Antibiotic Therapies to Combat Drug-Resistant Bacterial Infections, Lucca, Italy. doi:10.5281/zenodo.17377733
- Marchioro, L., Huber, K. E., Hofner, B., Kerscher, B., Arrazuria, R., Bekeredjian-Ding, I. (2022) Recurring issues in the development of vaccines against AMR infections: results from the COMBINE vaccine expert workshop, presented at the 6th AMR Conference, Basel, Switzerland. doi:10.5281/zenodo.17377487
All COMBINE tools & resources
IMI COMBINE Preclinical Bacterial Strain Repository
The IMI COMBINE Preclinical Bacterial Strain Repository consists of well-characterised and virulent strains of Gram-negative bacteria Klebsiella pneumoniae and Pseudomonas aeruginosa. The repository is part of a collection of reference materials hosted on the website of the Paul-Ehrlich-Institut, the German Federal Institute for Vaccines and Biomedicines. The strains have been deposited to the German Collection of Microorganisms and Cell Cultures (DSMZ), where they can be ordered for distribution.
- K. pneumoniae reference candidate DSM 30104
- K. pneumoniae reference candidate DSM 116098
- K. pneumoniae reference candidate DSM 116099
- K. pneumoniae reference candidate DSM 116109
- P. aeruginosa reference candidate DSM 50071
- P. aeruginosa reference candidate DSM 116114
- P. aeruginosa reference candidate DSM 116116
The strains have been characterised and successfully evaluated in the COMBINE pneumonia model and offers a resource for the reproducible and comparable evaluation of the efficacy of new antibiotics.
COMBINE Pneumonia Model
The COMBINE pneumonia model is a standardised, reproducible and well-characterised mouse model to evaluate the efficacy of new small molecule antibiotics. The protocol has been developed based on an extensive literature review and stakeholder discussions. The model standardises key methodological procedures that can influence study outcomes, such as bacterial isolates used; sex and breed of mice, immunosuppression procedures, and inoculation techniques.
The COMBINE pneumonia model has been published in the ASM Journal “Microbiology Spectrum”. It was developed using a consensus lung infection protocol, where researchers at Statens Serum Institut (SSI) in Denmark, GSK in the USA and the Paul-Ehrlich-Institut in Germany tested Klebsiella pneumoniae and Pseudomonas aeruginosa isolates against predefined virulence criteria and followed up by independent sites to confirm virulence with minimal variability in bacterial growth. A total of 7 isolates is now validated in the model and are available through the German Collection of Microorganisms and Cell Cultures GmbH (DSMZ) through the IMI COMBINE Preclinical Bacterial Strain Repository (PBSR).
Read the publication on the COMBINE pneumonia model: The COMBINE pneumonia model: a multicenter study to standardize a mouse pneumonia model with Pseudomonas aeruginosa and Klebsiella pneumoniae for antibiotic development
Learn more about the literature review on which the COMBINE pneumonia model is based on: Variability of murine bacterial pneumonia models used to evaluate antimicrobial agents
Here you find the summary of the stakeholder discussion: Expert workshop summary: Advancing toward a standardized murine model to evaluate treatments for antimicrobial resistance lung infections
Bioassay Protocol Ontology (BPO)
A new bioassay protocol ontology enables the conversion of unstructured bioassay protocol data into structured, machine-readable formats that promote reusability and allow an accurate description of in vivo efficacy study metadata for antibiotic agents.
To enhance the reproducibility and usability of bioassays in antimicrobial resistance (AMR) associated antibacterial drug discovery and development, there is an increasing need for standardisation of bioassay metadata into machine-readable formats. Such a standardisation process requires mapping bioassay data to standard ontologies and can be performed at the study result output and protocol levels. At the result output level, general ontologies such as the BioAssay Ontology (BAO) already exist, but antibacterial drug discovery and AMR-specific ontologies that can aid in the standardisation process at the protocol level are missing.
The development of BPO is a first attempt to standardise and organise information within in-vivo AMR-related drug discovery bioassay protocol data in a structured manner. BPO will allow researchers to capture information regarding experimental details such as the type of mouse model, the bacterial strain, and the sex and growth phases of mouse and bacteria respectively from the protocol.
Find out more and download the ontology from GitHub
FAIR Data Templates
A tailored application of a “FAIRification framework” facilitating the practical implementation of FAIR principles. By showcasing the feasibility and benefits of transitioning to FAIR data practices, this work aims to encourage broader adoption and integration of FAIR principles within a research lab setting. Tools for standardisation of data sets to allow for FAIR working and data reuse.
Machine Learning Model to Identify New Antibiotics (AntiMicrobial-KG)
Advanced computational methods and machine learning could help reduce the high costs and complexity of antibiotic drug discovery. The COMBINE project has developed an Antimicrobial Knowledge Graph with models that can scan compound libraries to identify new antimicrobial compounds. The database and a machine learning model built using the knowledge are now published in the Journal of Chemical Information and Modeling. The model is trained on the AntiMicrobial-KG database, representing an aggregation of public bioassay datasets in a FAIR-compliant format. It has generated the largest training set hitherto used for ML applied to antimicrobial activity. However, both model and code can be trained on external datasets that drug developers already have access to, and to expand the applicability and confidence of model predictions for research and development.
The AntiMicrobial-KG was developed within the framework of the Innovative Medicines Initiative (IMI) AMR Accelerator program’s Scientific Interest Group on Machine Learning, coordinated by the COMBINE project. The AntiMicrobial-KG is a repository for collecting and visualizing public in-vitro antimicrobial assays. Utilizing this data, the AMR Accelerator projects have built ML models to efficiently scan compound libraries to identify compounds with the potential to exhibit antimicrobial activity. Using Random Forest and XGBoost algorithms, Antimicrobial-KG has developed classification models on four classes of microorganisms (i.e. gram-positive, gram-negative, acid-fast, and fungi) that outperform existing models. The ML model was tested on the EU-OPENSCREEN screening library to demonstrate its applicability in a laboratory setting. Antimicrobial-KG uses Python scripts for model training, exploratory analysis, and KG generation, available from GitHub. The data collected with the AntiMicrobial-KG and models are available on Zenodo. The AntiMicrobial-KG website at SciLifeLab allows users to search the database and use the pre-trained models for compound activity prediction.
Explore the experimentally validated antibacterial chemicals on the AMR-KG Database.
Read more about the source code and data repository on GitHub.
Find out more about the ML-model: Predicting Antimicrobial Class Specificity of Small Molecules Using Machine Learning
Recommendations
Recurring issues and mitigation strategies for the (clinical) development of vaccines and monoclonal antibodies against ESKAPE infections.
Coming in 2026.
Coordination and Support Office
Anders Karlén
Uppsala University
Coordinator
Tim Miles
GlaxoSmithKline
Project Lead
Marie Olliver
Uppsala University
Alliance Manager
Anna Lobell
Uppsala University
Finance Manager
Frédéric Peyrane
BEAM Alliance
Outreach Manager
Martin Reich
Knowbio GmbH
Communication Manager
Frederik Deroose
Connecting Pharma
Chair of Scientific Interest Groups
Sophie Lagrange
Evotec
Alignment Coordinator
Rogerio Martins
Evotec
Data Manager
Philip Gribbon
Fraunhofer ITMP
Data Manager
Josepine Fernow
Uppsala University
Communication Strategist
Diarmaid Hughes
Uppsala University
Scientific Advisor
Benjamin Hofner
Paul-Ehrlich-Institut
Clinical trials
Igor Stojkov
Paul-Ehrlich-Institut
Clinical trials
Lena Friberg
Uppsala University
Animal models
Jennifer Hoover
GlaxoSmithKline
Animal models
Project consortium
About BEAM Alliance
Since its inception in 2016, the BEAM Alliance (Biotech companies from Europe innovating in Anti-Microbial resistance research) has succeeded in uniting European SMEs working in the field of AMR. The BEAM Alliance now represents over 60 European SMEs that are collectively developing over 140 new, diversified R&D projects focused upon prevention, diagnosis and cure of microbial infections. The goal of the BEAM Alliance is to promote and maintain awareness of SME-driven innovation in the field. The BEAM Alliance also supports policymakers in understanding economic business models around AMR, highlighting the specific needs of SMEs and incentives required to develop innovative diagnostics and treatments. Collaborating with the existing community of global stakeholders, the BEAM Alliance is actively working to curb the AMR threat in a sustainable manner.
About Knowbio GmbH
Knowbio is an independent media and communications company serving the European life sciences ecosystem. Based in Berlin, we cover and support innovation across biotech, pharma, bioeconomy and medtech through trusted journalism, smart formats, and meaningful industry connections.
Knowbio was previously known as BIOCOM Interrelations GmbH, a company with more than 40 years of history in European biotech media. In 2025, the company entered a new chapter under new ownership, with Joachim Eeckhout and Michael Kuhrt taking over as owners.
www.knowb.io
About Connecting Pharma
The management team at Connecting Pharma has in-depth experience in drug discovery. Before joining Connecting Pharma, the founder has built his career in Janssen Pharmaceutica (part of Johnson & Johnson) where he developed both scientific and managerial experience. He has been a key contributor in discovery programmes and is an inventor of multiple New Molecular Entities in the field of Anti-Infectives, Inflammation, Neuroscience and Oncology.
Connecting Pharma has a strong and strategic partnership with Scientist.com, the world’s largest online marketplace for medical research and is instrumentally involved in the development and implementation of the Scientist.com expansion strategy worldwide.
About Evotec
Evotec SE has built a strong, productive and successful business model serving as a partner to a variety of organisations (pharma and biotech companies, academic groups, foundations) to rapidly and efficiently advance assets from the discovery space to filing INDs (INDiGO) and on to early clinical development across multiple therapeutic areas. With the acquisition of Sanofi’s infectious diseases unit adding to the company’s already existing ID capacity, Evotec can serve as a key strategic partner for infectious diseases R&D. An internal team of the infectious diseases unit is dedicated to drug discovery and development, including in vitro and in vivo pharmacology, chemistry, development, and project management. Evotec will contribute to the enabling platforms by providing medicinal chemistry and design, in vitro and in vivo microbiological efficacy data, safety and ADME data. It will analyse PK/PD relationships, decipher modes of action, carry out CMC and fermentation and support clinical studies and modelling.
About Fraunhofer ITMP
The Fraunhofer-Gesellschaft is the leading organisation for applied research in Europe. Its research activities are conducted by 69 institutes and it employs a staff of 24,000; with an annual research budget of 2.1 billion euros. Fraunhofer Institute for Translational Medicine and Pharmacology ITMP is participant in COMBINE and contributes their cross-domain expertise in drug discovery and life science informatics. The Fraunhofer Institute ITMP, with 520 employees, conducts research in the field of applied life sciences from a molecular level to entire ecosystems.
Within ITMP, the Translational Medicine department develops new approaches for the diagnosis and treatment of diseases that are inadequately understood or controlled. The Department is involved in identification, functional characterization and validation of targets which play a role in human health, disease and toxicity.
About grit42
We’re grit42 from Copenhagen and we’ve been fixing data workflows since the Space Odyssey. Our core expertise is digital laboratory infrastructure, enabled by our scientific data management platform with user-friendly day-to-day lab workflows, as well as handling compound and sample logistics. By streamlining data across all the different pre-clinical drug discovery phases and integrating with all kinds of equipment, we facilitate structured and tagged quality data. In addition, the platform also features direct comparisons of data across experiments, links the data to other types of data, and it enables you to apply advanced analytics, including artificial intelligence (AI).
About GSK
GSK is a science-led global healthcare company that researches and develops a broad range of innovative products. The R&D organization within the company has extensive expertise in designing, executing, analyzing and reporting clinical trials in many therapeutic areas, including infectious diseases. GSK is committed to reporting the results of clinical research that evaluate medicines and vaccines, irrespective of whether the outcomes are perceived to be positive or negative. GSK is an active member of several collaborations focused on developing new treatments for TB, including multi-drug resistant forms of the infection. In 2012, GSK Tres Cantos joined the TB Drug Accelerator Program – a partnership with several pharmaceutical and public-sector research institutions and the Bill & Melinda Gates Foundation, aiming to speed up the discovery of new medicines by collaborating on early stage research.
About Janssen
At Janssen, we’re creating a future where disease is a thing of the past. We’re the Pharmaceutical Companies of Johnson & Johnson, working tirelessly to make that future a reality for patients everywhere by fighting sickness with science, improving access with ingenuity, and healing hopelessness with heart. We focus on areas of medicine where we can make the biggest difference: Cardiovascular & Metabolism, Immunology, Infectious Diseases & Vaccines, Neuroscience, Oncology, and Pulmonary Hypertension. We have a longstanding commitment to develop and responsibly deploy innovative technologies and treatments to combat the growing threat of antimicrobial resistance (AMR) on multiple fronts. Follow us at @JanssenGlobal.
About Paul-Ehrlich-Institut (PEI)
The Paul-Ehrlich-Institut, the Federal Institute for Vaccines and Biomedicines, in Langen near Frankfurt/Main, is a senior federal authority reporting to the Federal Ministry of Health (Bundesministerium für Gesundheit, BMG). It is responsible for the research, assessment, and marketing authorisation of biomedicines for human use and immunological veterinary medicinal products. Its remit also includes the authorisation of clinical trials and pharmacovigilance, i.e. recording and evaluation of potential adverse effects. Other duties of the institute include official batch control, scientific advice and inspections. In-house experimental research in the field of biomedicines and life science form an indispensable basis for the manifold tasks performed at the institute. The Paul-Ehrlich-Institut, with its roughly 800 members of staff, also has advisory functions nationally (federal government, federal states (Länder)), and internationally (World Health Organisation, European Medicines Agency, European Commission, Council of Europe etc.).
About Statens Serum Institut (SSI)
Statens Serum Institut (SSI) is under the auspices of the Danish Ministry of Health. Our main duty is to ensure preparedness against infectious diseases and biological threats as well as control of congenital disorders. SSI has state-of-the-art laboratories and animal facilities and has extensive experience of designing, planning and execution of in vivo efficacy evaluation of antimicrobial compounds.
About Uppsala University
Uppsala University is the Nordic region’s oldest university – founded in 1477 – and is ranked among the top 100 universities in the world. There are more than 40,000 students here and they are seen, heard and make their mark everywhere. The University’s nearly 5,000 researchers and teachers conduct world-leading research and offer a seemingly endless number of courses.
Among the University’s alumni there are 15 Nobel Prize laureates, of which 8 received their prizes for discoveries made during their time at Uppsala University. Carl Linnaeus, Anders Celsius and Olof Rudbeck the Elder are a few examples of prominent scientists in Uppsala University’s history.
| This project has received funding from the Innovative Medicines Initiative 2 Joint Undertaking under Grant Agreement No 853967. This Joint Undertaking receives support from the European Union’s Horizon 2020 research and innovation programme and EFPIA companies’ in kind contribution. https://www.imi.europa.eu/ |
