Developments in Anti-Microbial Resistance Surveillance


Anti-microbial resistance surveillance creates publicly accessible records that identify emerging trends in AMR and inform policy to prevent it.

Anti-microbial resistance surveillance creates publicly accessible records that identify emerging trends in AMR and inform policy to prevent it.

The 2021 World Anti-Microbial Resistance Congress is the world’s largest AMR conference. Held in-person this year from November 8-9 in Washington, DC, roundtables, presentations, and discussions were made available “for all stakeholders combating anti-microbial resistance.”

One presenter, Chris Longshaw, Senior Director of Scientific Affairs at Shionogi, Inc., gave a pre-recorded talk entitled, “Supporting open data protocols: Encouraging companies to share resistance surveillance data.”

Longshaw began his presentation with a question: “Why do we need AMR surveillance?” He stressed that if you can’t measure it, you can’t improve it. AMR is a major issue that must be understood if it is to be stopped. Identifying emerging trends in AMR is necessary to establish national and international antimicrobial stewardship policy.

Longshaw detailed that AMR surveillance is primarily undergone by the World Health Organization (WHO) and other government entities, academia, and the pharmaceutical industry. About half of surveillance is carried out privately, meaning the data collected is not available to the general public.

To remedy this, the AMR Industry Alliance, comprised of over 100 companies, committed to increased sharing of their AMR surveillance data. The industry uses this surveillance data for post-approval commitment to monitor resistance, to demonstrate drug activity against contemporary pathogens, for medical education and publications, and to validate AST materials.

Longshaw explained that collected data includes information about pathogens, patients, and antibiotics. Most commonly, pathogen data includes identity, serotype/sequence type, site of infection, clinical specimen, and genotype. Rarely, pathogen data may also include virulence factors, colonization, and heteroresistance. Patient data commonly includes geographical origin, hospital versus community, ward, infection type, age, and gender. Rarely, it may include patient comorbidities, renal/liver failure, or prior antibiotic exposure. Antibiotic data collected most often includes susceptibility, and rarely includes MBC, synergy, and disk zone.

Next, Longshaw covered the strengths and weaknesses of industry surveillance. The strengths include the high quality data from contract research labs, large number of isolates, standardization of methodology, and longitudinal collection to identify trends over time. Weaknesses were limited geography, sentinel surveillance (usually in large hospitals), limited antibiotics tested, limited pathogens collected, no real-world testing, lack of clinical data, heterogeneous metadata that complicates pooling datasets, and the raw data usually not being publicly accessible.

This last issue in particular is being addressed by Longshaw and his team. A data sharing pilot with the Open Data Institute (ODI) yielded a 90-day proof of concept project that allowed researchers to develop a register of AMR surveillance programs, accessible here. The ODI dataset included 12 countries and 85 antimicrobials.

The ODI project has morphed into a new project, called the AMR Register. Longshaw anticipates the AMR Register will launch sometime next year, with hope that the initiative will provide increased visibility of industry surveillance.

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