Antimicrobial resistance (AMR) has become a global public health crisis, leading to over 1.27 million deaths worldwide in 2019 alone. The overuse and misuse of antibiotics have led to the development of resistant strains of bacteria and fungi, which can be difficult to treat and can cause severe infections. To combat this growing threat, there is an urgent need to improve diagnostic and surveillance capabilities, and it is essential to develop novel approaches for accurate and effective antimicrobial treatment. This article will explore ways to improve existing strategies, technologies, and methods to support the surveillance and diagnosis of bacterial and fungal infections. The aim is to identify new, more effective ways to rule out antimicrobial use or help identify the most effective antimicrobial treatment. This article provides recommendations on developing approaches that can rule out antimicrobial use or help identify the most effective antimicrobial treatment, which can contribute to curbing the spread of AMR.
1. Developing New or Improving Existing Diagnostics:
To address the unmet needs in the AMR diagnostics and surveillance sectors, it is essential to develop new, improve, or repurpose existing strategies, technologies, and methods for the rapid, accurate, and affordable detection of bacterial or fungal infections and/or resistance patterns and elements.
Such tests can help clinicians identify the presence of bacterial or fungal infections and determine whether antimicrobial treatment is necessary or not. Rapid and accurate diagnostic tests that can differentiate between bacterial and viral infections are needed to reduce the unnecessary use of antimicrobial agents. Current diagnostic methods such as culture-based techniques are time-consuming, taking up to 48 hours to obtain results.
Traditional culture-based methods for detecting bacterial and fungal infections can take several days to yield results, leading to the empirical use of antibiotics. This approach often results in the inappropriate use of antibiotics and the development of resistance. Rapid diagnostic tests that can provide accurate results in a matter of hours can reduce the need for empirical antibiotic use and improve the identification of effective treatments.
Improving Existing Diagnostics:
There are several approaches to improving diagnostics for AMR surveillance. One such approach is to repurpose existing technologies for the rapid detection of bacterial and fungal infections. For example, the use of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) has been expanded to include the identification of bacterial resistance patterns.
Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a rapid and accurate method for identifying bacterial and fungal pathogens. The integration of MALDI-TOF MS with POC diagnostics can provide rapid and accurate identification of bacterial and fungal pathogens, allowing for targeted antimicrobial treatment.
Additionally, next-generation sequencing (NGS) is a powerful tool for identifying bacterial and fungal species and their resistance patterns. By using NGS data to develop targeted treatments, clinicians can avoid the use of broad-spectrum antibiotics, which can contribute to the development of resistance.
Developing New Techniques:
There are several approaches to developing diagnostics for AMR surveillance.
Point-of-Care Diagnostics
One way to achieve this is through the development of point-of-care diagnostics. Point-of-care (POC) diagnostics are tests that can be performed at the bedside or in the field, without the need for sophisticated laboratory equipment, and with results available within minutes. POC diagnostics can be a valuable tool in the diagnosis of bacterial and fungal infections, especially in resource-limited settings where access to laboratory facilities is limited. The development of rapid POC diagnostic tests that can accurately detect infections and antimicrobial resistance patterns can be crucial in preventing the spread of AMR. Such tests could be especially useful in community settings where individuals can be quickly screened for infections before the start of treatment. Some of the most promising technologies in this area include microfluidics, paper-based assays, and biosensors.
Nucleic Acid-based Methods
Another approach is the development of nucleic acid-based methods for detecting pathogens and resistance genes, such as nucleic acid amplification tests (NAATs), loop-mediated isothermal amplification (LAMP), lateral flow assays (LFAs), and digital microfluidics (DMF) platforms. These methods have the potential to provide rapid and accurate detection of pathogens and resistance genes. Several innovative approaches have been developed to address this need, including.
NAATs, such as PCR, have become the gold standard for diagnosing bacterial and fungal infections due to their high sensitivity and specificity. They detect and amplify the DNA or RNA of the pathogen, allowing for the rapid identification of the causative agent. NAATs can be performed on various sample types, including blood, urine, sputum, and cerebrospinal fluid. Furthermore, multiplex PCR assays can detect multiple pathogens simultaneously, reducing the time and cost required for diagnosis. NAATs have also been used to detect AMR genes, enabling the identification of drug-resistant pathogens.
LFAs are simple, rapid, and affordable tests that can be used in resource-limited settings. They use a strip containing an immobilized antigen that reacts with the pathogen’s antibodies, producing a visible signal. LFAs have been developed for various bacterial and fungal infections, including tuberculosis, malaria, and cryptococcal meningitis. LFAs have also been used to detect AMR markers, such as beta-lactamase enzymes, in bacterial isolates.
DMF is a promising technology that allows for the automated and precise manipulation of fluids on a microscale. DMF platforms have been developed for various applications, including cell sorting, drug discovery, and diagnostics. DMF-based assays have been developed for bacterial and fungal infections, enabling the rapid and sensitive detection of pathogens and resistance markers. DMF assays have also been integrated with NAATs to enable the detection of multiple pathogens and resistance markers simultaneously.
2. Facilitating Uptake and Use of Diagnostics in Varied Economic Settings:
Despite the availability of various diagnostic tests for bacterial and fungal infections, their uptake and use in varied economic settings remain limited. The implementation of diagnostics in resource-limited settings can be challenging due to the lack of infrastructure, trained personnel, and funding. Therefore, it is crucial to study ways to facilitate the uptake and use of existing diagnostics, especially in low-income and middle-income countries (LMICs) where the burden of infectious diseases is high.
One approach is to develop low-cost user-friendly diagnostics that do not require specialized training or equipment, and are suitable for use in resource-limited settings. For example, lateral flow assays are simple, easy-to-use tests that can provide rapid results for a range of infectious diseases, including malaria and influenza. By expanding the range of diseases that can be diagnosed using lateral flow assays, clinicians can improve their overall diagnostic capabilities and reduce the use of unnecessary antibiotics. LAMP assays can be performed using inexpensive equipment, and the results can be read visually, eliminating the need for expensive instrumentation.
Another approach is to implement training programs that educate healthcare professionals on the appropriate use of diagnostics and the importance of combating AMR, while increasing awareness about the importance of accurate diagnosis and appropriate use of antimicrobial agents, and ensuring that diagnostic tests are affordable and accessible.
There is also a need for collaborative efforts between researchers, policymakers, and healthcare providers. Such efforts should focus on developing cost-effective and sustainable diagnostic solutions that can be adapted to the local context. Public-private partnerships can also play a crucial role in providing funding, technical support, and market access for diagnostic solutions.
3. Optimizing Tools, Technologies, and Methods for Diagnostic Data Capture and Usage:
The use of tools, technologies, and methods for diagnostic data capture and usage can improve the accuracy of diagnosis, promote appropriate use of antimicrobial agents and to inform AMR surveillance and control efforts. Digital health technologies can be used to capture diagnostic data in real-time and provide clinicians with insights into disease patterns and treatment outcomes. By analyzing this data, healthcare professionals can make more informed decisions about the use of antibiotics and identify areas where improved diagnostics are needed.
Such technologies can include electronic medical records (EMRs), clinical decision support systems, and surveillance networks.
Electronic medical records (EMRs) can help to capture patient data, including laboratory results, and provide a comprehensive patient history, which can aid in accurate diagnosis. EMRs can provide a wealth of information on patient demographics, diagnostic results, and treatment outcomes, which can be used to inform surveillance and control efforts. However, the implementation of EMRs can be challenging, particularly in resource-limited settings.
Clinical decision support systems can provide clinicians with real-time guidance on the selection of appropriate antimicrobial agents, reducing the risk of resistance development.
Surveillance networks can help to identify trends in the prevalence of infections and resistance patterns, providing valuable information for public health decision-making. Incorporating diagnostics into existing surveillance systems, such as the Global Antimicrobial Resistance Surveillance System (GLASS) can provide a more comprehensive understanding of AMR trends and patterns.
The integration of diagnostics with surveillance strategies can enable the real-time monitoring of infectious diseases and AMR patterns. Such integration can facilitate the identification of outbreaks, the tracking of AMR trends, and the evaluation of intervention strategies.
The use of digital tools, such as mobile applications and cloud-based platforms, can enable the rapid and secure sharing of diagnostic and surveillance data, improving the speed and accuracy of decision-making. Data analytics tools can be used to identify patterns of resistance and monitor the effectiveness of treatment regimens. Moreover, the use of digital technologies, such as telemedicine, can improve the accessibility of diagnostics and enable remote consultations, which is particularly relevant in rural or remote areas.
4. Identifying Effective Antimicrobial Treatment
Identifying the most effective antimicrobial treatment for bacterial infections is essential to reduce the development of AMR. Traditionally, the antimicrobial susceptibility of bacterial pathogens is determined through culture-based methods, which can take up to several days. New or improved methods for the rapid determination of antimicrobial susceptibility are urgently needed.
One approach is to use molecular methods, such as polymerase chain reaction (PCR) or next-generation sequencing (NGS), to detect antimicrobial resistance genes (ARGs) or mutations. NGS has the potential to revolutionize antimicrobial susceptibility testing by providing rapid and comprehensive detection of ARGs and mutations. For example, the use of NGS-based assays has shown promise in predicting the susceptibility of Mycobacterium tuberculosis to first-line drugs.
Another approach is to use artificial intelligence (AI) algorithms to predict the most effective antimicrobial treatment. AI algorithms can analyze large amounts of data, including genomic data and patient data, to predict the susceptibility of bacterial pathogens to antimicrobial agents. A recent study used an AI algorithm to predict the susceptibility of Escherichia coli to antimicrobial agents with high accuracy.
In Conclusion:
Developing approaches to rule out antimicrobial use or identify the most effective treatment is crucial to mitigate the impact of AMR on global health and food security. This can be achieved through the development of novel or improving existing strategies, tools, technologies, and methods for diagnosis and/or One Health AMR surveillance. The recommendations presented in this article aim to improve understanding, monitoring, detection, and mitigation of infection and AMR, or optimization of antimicrobial use. Collaboration among stakeholders is crucial to implement these recommendations and promote the uptake of existing diagnostics, the integration of diagnostic data with surveillance strategies, and the optimization of diagnostic data capture and usage. The efforts to curb AMR will have a global impact on human, animal, and plant health and food safety and security.