Research introduction of new antibiotics

Description of proposed project

Antibiotic resistance threatens the foundations of modern medicine and is a major threat to health. Antibiotic resistant infections take longer to treat, are associated with higher rates of morbidity and mortality, and incur higher cost on average than antibiotic susceptible infections. As drug resistance proliferates globally, the scientific, clinical, and private sectors have sought to develop new, effective antibiotics. Despite many challenges and a high failure rate, a handful of new antibiotics are now in or have recently successfully completed Phase 3 trials. Yet, we lack a formal framework to answer a critical question relevant to each new drug—how do we optimally introduce these new, precious resources to minimize the emergence of resistance? Without a systematic, quantitative framework, we risk squandering these resources and limiting the potential benefit from each new antibiotic.

The scale of the problem of resistance is massive. Multidrug resistant strains of many pathogens have become prevalent, and for some pathogens, like Mycobacterium tuberculosis—the cause of tuberculosis, one of the most prevalent infections globally—and Acinetobacter baumannii—which causes infections most commonly seen in critically ill hospitalized patients—strains resistant to all approved antibiotics have been detected. For other pathogens, like Neisseria gonorrhoeae, the cause of the sexually transmitted disease gonorrhea, only one antibiotic remains recommended for treatment.

New antibiotics for each of these—and for other conditions—are on the horizon. How will they be deployed? Standard antibiotic stewardship principles are guided by the understanding that antibiotic use drives resistance. Consequently, the standard approach to the rollout of new antibiotics is to try to use them as little as possible, waiting for resistance to existing therapy to reach some threshold before switching to the new antibiotic.

But this strategy to hold new drugs in reserve, though intuitive, is sometimes the worst performing strategy. In recent papers, my lab and I used mathematical modeling of infectious disease dynamics to show that for gonorrhea rolling out the new drugs as quickly as possible performs better and results in a longer clinically useful lifespan for both drugs (Reichert et al., 2023; Kline et al., 2025). Here, the intuition is that treatment is empiric—there is no testing for antibiotic susceptibilities—and as such using both drugs in the population distributes the selective pressures driving resistance both to the existing and new drugs and thus slows the spread of resistance. The standard stewardship strategy fails in this circumstance because it does not consider all the factors involved in driving disease transmission and resistance spread.

For tuberculosis, the recent experience with bedaquiline, the first new anti-TB therapy in decades, demonstrates another blindspot in traditional approaches to drug rollout. Treatment of TB is accomplished with multi-drug therapy—usually four drugs taken together, as the likelihood of resistance arising to all four simultaneously is the product of the likelihoods of resistance emerging to each. But bedaquiline was tested and initially used in individuals with multi-drug resistant infections. Though infected people may have received multiple drugs together with bedaquiline, essentially the new drug was the only active medication, meaning that instead of effective combination therapy, the individuals were essentially only on a single agent. Predictably, resistance emerged quickly and now resistance prevalence is increasing to substantial levels. Now, the global TB drug development community recognizes that clinical trials and use of new anti-TB therapies must be done in pairs, with clinical evaluation only done for two new drugs at a time.

Here, we aim to build on our work and on these and similar observations. We propose to (1) write an overview of this topic and the needs of the field; (2) develop a mathematical framework grounded in our understanding of the pathways to antibiotic resistance and the factors that shape the likelihood of its spread in populations.

Why are you qualified to work on this?

My lab and I are the right team to do this work because of my background as a clinically trained infectious disease specialist and internal medicine physician and as an infectious disease epidemiologist and because my lab and I have defined trends in antibiotic use and resistance, pioneered work on quantitative approaches to how antibiotic use drives resistance, and published key papers that address the critical question about how best to rollout new antibiotics. Our work spans epidemiological, mathematical modeling, genomic, and molecular microbiology, as we bring an interdisciplinary approach to studying how pathogens evolve and spread through populations and how we can develop and best apply tools to control them. We collaborate with clinical and public health institutions at local, national, and international levels.

Selected relevant publications:

Olesen SW, MacFadden D, Grad YH. Cumulative risk of receiving an antibiotic prescription. New England Journal of Medicine. 2019; 380:1872-1873. DOI: 10.1056/NEJMc1816699.

Reichert E, Yaesoubi R, Rönn MM, Gift TL, Salomon JA, Grad YH. Resistance-minimizing strategies for introducing a novel antibiotic for gonorrhea treatment: a mathematical modeling study. Lancet Microbe. 2023 Oct;4(10):e781-e789. doi: 10.1016/S2666-5247(23)00145-3. Epub 2023 Aug 21.

Kissler SM, Roster KIO, Petherbridge R, Mehrotra A, Barnett ML, Grad YH. Drivers of geographic patterns in outpatient antibiotic prescribing in the United States. Clinical Infectious Diseases. 2024. 10.1093/cid/ciae111

Helekal D, Mortimer TD, Mukherjee A, Palace SG, Grad YH. Quantifying the impact of genetic determinants of antibiotic use and genetic determinants of resistance on bacterial lineage dynamics. bioRxiv. 2025.

Kline MC, Oliveira Roster KI, Helekal D, Rumpler E, Grad YH. Comparing strategies to introduce two new antibiotics for gonorrhea: a modeling study. medRxiv. 2025.

What would you do if not funded?

In the absence of ACX funding support for this project, we will seek funding from other sources. While NIH and FDA would be likely candidates, Harvard is, at least as of now, not eligible for federal funding, and many private foundations and philanthropies are overwhelmed with funding requests. As such, it may be possible to find time to achieve aim (1) even without funding, but aim (2) would remain uncompleted, as support for the postdoctoral fellow would be critical.

How much money do you need?

I estimate that for a 10% fraction of my effort and for 50% of a postdoctoral fellow, we request $78,122.

Supporting documents

Here are links to two of our relevant publications:

https://www.thelancet.com/journals/lanmic/article/PIIS2666-5247(23)00145-3/fulltext

https://www.medrxiv.org/content/10.1101/2025.07.01.25330638v2