White Paper | Draigon

19 November 2025

DRAIGON White Paper:

Revolutionising diagnostics: closing the gap in AMR detection with cutting-edge technologies

DRAIGON White Paper:

Introduction

Antimicrobial resistance (AMR) is unequivocally one of the most significant health threats of our time. The World Health Organization (WHO) has consistently emphasised this, and recent data highlights its impact. (1-3) The Global Research on Antimicrobial Resistance (GRAM) Project estimates that AMR directly caused 1.27 million deaths worldwide in 2019, with an additional 4.95 million deaths associated with bacterial resistance.(4) This underscores the scale of this unfolding public health catastrophe.

The impact of the AMR crisis is visible across the entire healthcare ecosystem. From infectious disease wards where clinicians face patients deteriorating from untreatable infections to microbiology laboratories where the underlying resistance patterns are identified. In both high-income and low- and middle-income countries, clinicians and microbiologists are routinely confronted with multidrug-resistant (MDR) organisms isolated not only from human clinical specimens but also from animal and environmental samples, reflecting the broader One Health dimension of the AMR challenge.(5,6) This growing resistance undermines the ability of clinicians to reduce morbidity and mortality in their communities. Critically, time remains a decisive factor: for every hour that appropriate antibiotic therapy is delayed, the risk of death from sepsis increases substantially, estimated at 7.6% per hour in key studies.(7,8)

If left unchecked, the GRAM Project forecasts that AMR will directly cause approximately 1.91 million deaths in 2050, with a broader 39 million attributable deaths between 2025 and 2050.(4) Many of us will still be alive to witness the consequences of the seeds being sown today. Peering into that future, we envision profoundly weakened healthcare systems, where the reality of untreatable infections limits our ability to practice modern medicine across all fields, from surgery and chemotherapy to critical care.

In such a future, even when effective antibiotics are available, doctors will face a critical challenge. They must quickly choose and give the right drug before the infection spreads out of control. If treatment is delayed, the infection, and sometimes the body’s own overactive immune response, can cause lasting and irreversible harm.

Efforts are underway to close the diagnostic gaps that remain a critical weakness in the global response to AMR. Here we reference The WHO Antimicrobial Resistance Diagnostic Initiative policy brief,1 which aims to elevate the role of diagnostics in the global response to AMR. The initiative supports countries in strengthening laboratory capacity and ensuring access to quality testing for various pathogens. It also establishes a baseline for measuring diagnostic implementation progress, which was subsequently endorsed in the political declaration made at the September 2024 United Nations General Assembly (UNGA) High-Level Meeting on AMR.

While policy commitments are essential, they too often fail to translate into meaningful change. The urgent priority must now be implementation, not more statements of intent, particularly on the frontlines of healthcare.

This paper presents the work of the DRAIGON project: a consortium of nine leading scientific and business partners seeking to drive the implementation of an innovative, diagnostics-driven approach. Such a tool is critical for strengthening the global response to resistant pathogens.

DRAIGON aims to demonstrate the clinical value of a rapid, Artificial Intelligence (AI)-powered, whole-genome sequencing (WGS) diagnostic tool for accurately identifying bacterial and fungal infections, especially MDR pathogens. The project aims to advance this tool to Technology Readiness Level 7 (TRL7), paving the way for regulatory approval and clinical use.
The DRAIGON project is grant-funded at €6.98 million over four years by the European Commission (EC), the UK Research and Innovation (UKRI) organisation, and Swiss national funds, highlighting the extensive international support for this initiative.

This funding underscores the significance of this project in addressing one of the most pressing health challenges of our time.

Figure 1. Framework for evaluating the value and impact of diagnostics beyond the individual patient. ICU, Intensive Care Unit; IPC, Infection Prevention and Control.

The economic case for diagnostics

Accurate, rapid diagnostics drive better patient care and clear hospital-level savings. By delivering earlier, targeted treatment, advanced tests help clinicians avoid the costly and potentially harmful effects of broad-spectrum therapy. To quantify this, the DRAIGON project is building a value framework (Figure 1) that centres on:

Diagnostic performance: Analytical accuracy (sensitivity, specificity) and on-demand access, as well as critical turnaround time from positive sample to actionable result
Pathway efficiency: Automation of DNA extraction, library preparation, and AI-driven analysis accelerated decision-making with reduced repeat or parallel tests
Therapy optimisation: Faster switching from empirical to targeted antibiotics, reducing side-effects, and resistance pressure
Short-term hospital-level gains: Reduced length of stay and isolation costs, improved bed turnover, and resource use
Long-term patient outcomes: Better quality of life, lower mortality risk, and slowed emergence of resistant strains

By validating this framework through health economic modelling and real-world data, DRAIGON will establish the financial case for adopting its automated WGS-based test in both high-income and resource-limited hospitals.

The current challenges in diagnosing antimicrobial resistance

Factors such as the overuse and misuse of antibiotics in human medicine and agriculture have accelerated AMR through the intrinsic mechanisms that many microbes possess to adapt and survive challenges in their environment. The lack of real-time data and rapid diagnostic tools in clinical settings further exacerbates the problem, delaying effective treatment and increasing the risk of transmission of resistant strains.

To date, diagnosing, treating, and containing infections requires laboratories to establish multiple, disparate methodologies for detecting MDR, accurately identifying and typing pathogens, and conducting rapid antimicrobial susceptibility/resistance testing.

This fragmented approach involves the use of multiple independent test and assay technologies that vary significantly in terms of capital equipment and consumable expenses, commitment of laboratory and storage space, calibration methods, and ease of use, as well as accuracy, sensitivity, and reproducibility.

What they all have in common is that no single diagnostic test can provide all information needed to diagnose, recommend treatment options, and contain MDR infections. This is even less so for a broadening range of pathogens. Effective treatment recommendations rely on diagnostics that not only identify the pathogen but also determine its susceptibility to available antimicrobials, enabling clinicians to prescribe the most effective therapy while minimising the risk of side effects, including resistance development.

Central to the mission of DRAIGON is a recognition of the importance of pioneering research and development in this field - recognising that when faced with the AMR challenge, existing technologies are simply not fit for purpose.

We face two fundamental challenges, which are becoming ever more critical:

1. We must have the capability and resources to precisely identify a MDR infection and determine its drug susceptibility profile

and

2. 2. We must be able to select and administer effective drugs from the armamentarium quickly and efficiently.

DRAIGON’s approach, therefore, underpins successful decision-making for individual patient care and disease surveillance as part of properly functioning advanced healthcare systems.

DRAIGON’s AI-powered WGS for accessible, rapid AMR diagnostics

Turning to next-generation technology, DRAIGON aims to harness the power of WGS coupled with AI-assisted bioinformatic data interpretation. These established technologies have the potential to sensitively detect and accurately identify MDR pathogens in a single, streamlined process, while determining their antimicrobial susceptibility profile. The work of the DRAIGON Consortium will initially focus on overcoming the technical and operational barriers that limit the widespread adoption of WGS in clinical settings. Alongside clinical application, this rapid, technology-integrated solution could also be deployed for outbreak alerts and cluster analysis, supporting public health surveillance (PHS) and infection prevention and control (IPC) efforts to counteract and prevent hospital-acquired infection (HAI) outbreaks and transmission events.

The primary innovation in the DRAIGON project lies in automating and standardising the workflow to reduce complexity, cost, and turnaround time (Figure 2).

This is structured through the following key stages:

Stage 1 – Optimisation of sample preparation from positive cultures
Once a pathogen is detected in a culture, the process of extracting high-quality DNA for sequencing begins. This is a critical step that impacts the final result. DRAIGON is developing and standardising protocols that:

Efficiently extract pathogen DNA from positive blood culture bottles previously inoculated either with infected synovial fluid or blood.
Optimise DNA extraction methods for different pathogens to ensure reliable performance.
Minimise host DNA carry-over, which can interfere with pathogen signals and compromise downstream genomic and susceptibility analyses.

Stage 2 – Automated library preparation with cloud-based analysis
In partnership with Camtech, DRAIGON is developing a compact device prototype that:

Automates the DNA purification and library preparation steps — traditionally the most labour-intensive and error-prone steps of the sample preparation workflow before sequencing.
Integrates with a long-read sequencer (Oxford Nanopore) and connects directly to a cloud-based platform (the DRAIGONome) for real-time AI-powered data analysis and reporting.

This semi-automated "culture-to-result" setup significantly reduces the hands-on time and technical barriers, making advanced WGS technology more scalable and deployable in clinical microbiology labs, including those in resource-constrained environments.

Figure 2. Improving AMR identification and antibiotic susceptibility turnaround time. AI, Artificial Intelligence; AST, Antimicrobial Susceptibility Testing; ID, Identification, WGS, Whole-Genome Sequencing.

Implementation and impact

The first two feasibility clinical utility studies under this initiative focus on blood stream infections (BSI) and periprosthetic joint infections (PJI), both of which present significant challenges in terms of treatment and management. BSI, which can lead to sepsis, can be life-threatening and require rapid diagnosis and intervention. Similarly, PJI, which occur around prosthetic joints, are notoriously difficult to treat due to the presence of biofilms and resistant microbes. By focusing on these two sample types, the DRAIGON project aims to demonstrate the effectiveness of its proposed solution while informing and engaging the broader scientific community.

The impact of this approach could be transformative. By enabling faster and more accurate identification of AMR pathogens, particularly in near-patient settings, healthcare providers can make more informed treatment decisions, thereby reducing the spread of resistance and improving patient outcomes. Moreover, the accessibility of automated WGS application technology in low- and middle-income countries (LMICs) could significantly enhance global AMR surveillance and response capabilities, thereby bridging the gap between high-resource and low-resource settings. Indeed, the DRAIGON consortium includes implementation partners from LMIC-designated sites, which will help stress-test the feasibility of this solution in resource-constrained settings.

The DRAIGON project will establish the clinical and economic value of this new approach, delivering fully integrated, validated, standardised sample processing and library workflows, combined with AI modelling, data interpretation and clinical reporting, alongside health economics studies to demonstrate clinical utility and cost-effectiveness10 (Figure 3).

The DRAIGON project will provide clinicians with a powerful diagnostic tool to rapidly and affordably achieve comprehensive pathogen identification, genomic resistance profiling, and predicted antimicrobial susceptibility. It will also support the evaluation of outbreak and transmission dynamics, all within a single, partially automated workflow.

This innovative, high-resolution approach acts as an integrated diagnostic platform, enhancing infection control and stewardship strategies while supporting global efforts to combat AMR. It delivers ‘the right antibiotic, for the right infection, at the right time’, empowering faster, evidence-based clinical decisions.

Figure 3. The DRAIGON consortium’s proposed design and development plan for a novel in vitro diagnostic solution using an automated, AI-powered, WGS application. AI, Artificial Intelligence; AMR, Antimicrobial Resistance; gAST, Genomic Antimicrobial Susceptibility Testing; IP, Intellectual Property; TRL, Technology Readiness Level.

Conclusion

The successful implementation of this integrated solution is being driven by a consortium of nine partners, each bringing specialised expertise across critical areas. This collaboration ensures that key aspects of the solution, from technological development to clinical application, are effectively addressed. The project is funded by a €6.98 million grant from the European Union over four years. This funding aligns with the EU’s priority to improve quality of care and to tackle the urgent global threat posed by AMR.

By focusing on critical areas such as BSI and PJI as prototype settings, and by ensuring that these advanced time-saving technologies are accessible in LMICs, this initiative demonstrates the potential of a multidisciplinary approach to transform quality of care and protect global public health, improve global access to next-generation technologies and solutions for AMR, enhance our ability to combat AMR, and preserve the efficacy of treatments for future generations. The time to act is now, and the integration of these advanced technologies represents a critical step forward in the global fight against AMR.

Details of DRAIGON’s work and the results of ongoing scientific advances can be found on our webpage: www.DRAIGON.eu

DRAIGON contact:
Adriana Vives, Project Manager
Email: adriana.vives@euvaccine.eu

Quick facts about the DRAIGON project

Grant funding project’s full name:

Diagnosing Infections with Multi-drug Resistant Microorganisms using AI-powered Genomic Antibiotic Susceptibility Prediction from Long-Read Sequencing Data

Current funding start date:
Current funding end date:

01/01/2024

31/12/2027

Funding agency:

European Commission (EC), the UK Research and Innovation (UKRI) organisation, and Swiss national funds

Budget:

6.98 million Euros

Coordinator:

European Vaccine Initiative (EVI)

Consortium:

Partners from five EU countries, and three organisations from outside the EU, including Albania, the UK, Switzerland, and the USA

Project Partners:

Camtech Innovations Limited (United Kingdom), European Vaccine Initiative (Germany), HEALTH-ECORE B.V. (Netherlands), Isala Hospital (Netherlands), ORTOPADISCHES SPITAL SPEISING GMBH (Austria), Sandoz Pharmaceuticals AG (Switzerland), SPITALI UNIVERSITAR SHEFQET NDROQI (Albania), University Medical Center Groningen (Netherlands),
Mayo Clinic (USA)

European Commission (EC) funding

Funded by the European Union. Views and opinions expressed are, however, those of the author(s) only and do not necessarily reflect those of the European Union or European Health and Digital Executive Agency (HADEA). Neither the European Union nor the granting authority can be held responsible for them. This project has received funding from the European Union’s Horizon Europe research and innovation programme under grant agreement No 101081028.

United Kingdom Research and Innovation (UKRI) funding

This project is receiving funding from UK Research and Innovation (UKRI) under the UK government’s Horizon Europe funding guarantee [grant number 101081028].

References

1. World Health Organization (WHO). Antimicrobial Resistance Diagnostic Initiative: Policy Brief. Geneva: World Health Organization; 2024 Jun 27. (Available from: https://www.who.int/publications/i/item/9789240072015) [Accessed 13 November 2025].

2. World Health Organization (WHO). Antimicrobial resistance. Geneva: WHO; 2020. (Available from: https://www.who.int/news-room/fact-sheets/detail/antimicrobial-resistance) [Accessed 13 November].

3. World Health Organization (WHO). Antimicrobial resistance. Geneva: WHO; 2020. (Available from: https://www.who.int/news-room/fact-sheets/detail/antimicrobial-resistance) [Accessed 13 November 2025].

4. Murray CJL, et al. Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet. 2022;399(10325):629–55.

5. European Centre for Disease Prevention and Control (ECDC). Antimicrobial resistance surveillance in Europe 2022 – 2020 data. Stockholm: ECDC; 2022. (Available from: https://www.ecdc.europa.eu/en/publications-data/antimicrobial-resistance-surveillance-europe-2022-2020-data) [Accessed 13 November 2025].

6. Gu W, et al. Rapid pathogen detection by metagenomic next-generation sequencing of infected body fluids. Nat Med. 2021;27(1):115–24.

7. Kumar A, et al. Duration of hypotension before initiation of effective antimicrobial therapy is the critical determinant of survival in human septic shock. Crit Care Med. 2006;34(6):1589–96.

8. Singer M, et al. The Third International Consensus Definitions for Sepsis and Septic Shock (Sepsis-3). JAMA. 2016;315(8):801-10.

9. World Bank. Drug-resistant infections: a threat to our economic future. Washington, DC: World Bank; 2017. (Available from: https://documents.worldbank.org/en/publication/documents-reports/documentdetail/323311493396993758/final-report) [Accessed 13 Nov 2025].

10. European Commission. Horizon Europe Work Programme 2023–2024: Health. Brussels: European Commission; 2023.