Resumo executivo
A resistência antimicrobiana está entre as dez principais ameaças globais à saúde da Organização Mundial da Saúde, com projeções de que infecções resistentes causem até 10 milhões de mortes por ano até 2050.
A resistência surge por meio de múltiplos mecanismos intrínsecos e adquiridos, desde a alteração da permeabilidade da parede celular e bombas de efluxo até mutações genéticas e degradação enzimática de medicamentos.
O desenvolvimento de novos antibióticos está perigosamente atrasado em relação ao ritmo da resistência, dificultado por biofilmes, defesas de bactérias Gram-negativas, baixo retorno sobre o investimento e prazos de 10 a 15 anos.
Alternativas como vacinas bacterianas, peptídeos antimicrobianos, bacteriófagos e a inibição da resposta rigorosa oferecem caminhos promissores além dos antibióticos convencionais de pequenas moléculas.
Soluções de materiais avançados e métodos emergentes de descoberta impulsionados por IA têm o potencial de reduzir os prazos de desenvolvimento e a dependência de antibióticos tradicionais. Em agosto de 2205, pesquisadores do MIT relataram a invenção de antibióticos usando IA generativa contra cepas resistentes de gonorreia e Staphylococcus aureus.
Atualização, maio de 2026: o FDA aprovou o Zaynich, um antibiótico que resiste à adaptação bacteriana ao atacar três proteínas bacterianas de uma só vez em vez de uma, oferecendo aos médicos uma opção de tratamento contra infecções resistentes que antes quase não tinham.
The World Health Organization (WHO) defines a microorganism that is not killed/inactivated after the due course of treatment as ‘resistant’, and the rise in resistant organisms is multifactorial. According to the Centers for Disease Control and Prevention (CDC), more than 2.8 million antibiotic-resistant bacterial infections occur each year, resulting in 35,000+ deaths. Worryingly, projections made by the World Bank estimate this number might increase to 10 million deaths a year by 2050.
As such, the WHO has declared antimicrobial resistance as one of the top ten primary health concerns, and new solutions are urgently needed.
Antibiotic resistance is multifactorial
Antibiotic resistance can result from both intrinsic and acquired factors. Intrinsic factors include cell wall permeability, modified drug targets, activation of efflux pumps, and enzymatic degradation of antibiotics. Acquired resistance arises from the gain of new genetic material or mutation in the bacterial genome that mediates survival.
The need for new antibacterial treatments
Antibiotics cover many different classes. Each one is categorized by its structure and how it tackles bacteria in the body.
| Antibiotic class | Structure |
| Aminoglycosides (e.g., streptomycin, 57-92-1) |  |
| Beta-lactams (e.g., penicillin, 61-33-6) |  |
| Sulfonamides (e.g., sulfadiazine, 68-35-9) |  |
| Amphenicols (e.g., chloramphenicol, 56-75-7) |  |
| Polymyxins (e.g., polymixin B, 1404-26-8) |  |
| Tetracyclines (e.g., tetracycline, 60-54-8) |  |
| Macrolides (e.g., clarithromycin, 81103-11-9) |  |
| Pyrimidines (e.g., sulfadiazine 68-35-9) |  |
| Rifamycins (e.g., rifampicin, 13292-46-1) |  |
| Quinolones and fluoroquinolones (e.g., nalidixic acid, 389-08-2) |  |
| Streptogramins (e.g., quinupristin, 120138-50-3) |  |
| Lincosamides (e.g., lincomycin, 154-21-2) |  |
| Pleuromutilins (e.g., lefamulin, 1061337-51-6) |  |
| Oxazolidinones (e.g., linezolid, 165800-03-3) |  |
Table 1. The different classes of antibiotics.
Despite these established treatment options, many infections are becoming resistant to existing antibiotic treatments. Coupled with an estimated rise in related deaths, there is a pressing need to rethink how we tackle bacterial infections.
The challenges new antimicrobials face
While the rise in antimicrobial resistance is multifaceted, it is compounded by the slower pace of developing new treatment options compared to the rate of antimicrobial resistance development.
This is apparent when looking at the number of journal publications around antimicrobial resistance vs. the low proportion of patents (Figure 2). This indicates that researchers in academia are taking a more prominent role in developing new antimicrobials — and that these efforts must be translated into commercially available therapies.
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This can be explained by several factors that make antimicrobial development challenging. Beyond many innate or acquired mechanisms microbes can use to resist antimicrobials (Figure 1), there are also broader factors that make development difficult (Figure 3).
The ability of bacteria to tolerate antimicrobials, combined with the high development cost and long timeframes (Figure 3), has led to few antibiotics reaching the market in recent decades despite the dire need.
Alternatives to conventional antibiotics
Bringing new antibiotics to market is a time-consuming challenge (Figure 3), so alternatives are helping combat antimicrobial resistance.
The future of antimicrobials
Enhanced drug delivery methods through materials can provide localized, prolonged, and stimulus-dependent antibacterial activity. There are several ways of achieving antimicrobial delivery outside of traditional administration. Medical devices such as implants and catheters can be infection sources, which can be potentially prevented by using antimicrobial materials. Likewise, antimicrobial coatings on high-traffic surfaces can reduce the transmission of microbes and minimize the need for cleaning.
Advances in artificial intelligence (AI) have led to an acceleration in antimicrobial drug development using algorithms to identify potential new molecules. Although the number of journal publications has steadily increased, there hasn’t been a corresponding surge in patent applications, suggesting that most antimicrobial AI research is still in the academic stage(Figure 5).
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The rise in multi-drug-resistant bacteria poses an alarming threat to human health, and the need to develop novel antibiotics and antibacterial materials is urgent. Widespread AI use is still in its infancy; however, it holds promise for streamlining and reducing timelines for future efforts. Learn more about AI’s impact on chemistry in our Insight Report, the rise of large-language models, and how biomaterials are being used across the therapeutic landscape in a variety of new approaches.
