Setting the Standard for Infection Models
Interview with Carina Sofia Matias: COMBINE
The COMBINE project aims to improve the understanding of animal infection model reproducibility and translation to clinical efficacy by developing standardised protocols and establishing reference strains. A recently developed mouse pneumonia model with Methicillin-resistant Staphylococcus aureus (MRSA) was presented at the ESCMID Global 2025 in Vienna, Austria. MRSA is one of the most prevalent pathogens responsible for hospital-acquired pneumonia in immunocompromised patients and continues to pose a significant clinical threat. One of the study’s authors, Carina Sofia Matias, shared her perspective on cross-disciplinary teamwork and the challenges of AMR research.
What brought you to study the pre-clinical development of new antibiotics and antimicrobial treatments?
My interest in Microbiology started during my Bachelor’s in Health Sciences when I worked on a project identifying antibiotic-resistant bacteria in children’s playgrounds. That experience really made me aware of how widespread and relevant antimicrobial resistance is in everyday settings. Wanting to learn more, I went on to do a Master’s in Microbiology. After that, I moved to Copenhagen to start a PhD focused on the development of antimicrobials, and I’ve been involved in the field ever since.
Carina Sofia Matias is a postdoctoral researcher at
Statens Serum Institut (SSI), Copenhagen, Denmark
“Working on a project identifying antibiotic-resistant bacteria in children’s playgrounds during my Bachelor studies made me aware of how widespread and relevant antimicrobial resistance is in everyday settings.”
What is the role of pre-clinical research in the fight against AMR?
One of the biggest challenges in the early stages of testing new antimicrobial compounds is identifying which ones truly have therapeutic potential. In vitro assays can sometimes give promising results that don’t hold up in more complex models. Reproducibility across different bacterial strains and optimising test conditions to mimic real-life infections can also be tricky. When it comes to early murine testing, translating those in vitro findings into meaningful in vivo outcomes is another major hurdle. Factors like dosing, toxicity, and how the drug behaves in a living system all come into play—and even small differences can have a big impact on the results.
In our lab at SSI, we work closely with European projects, universities, and small biotech companies to help move their small-molecule candidates through the pre-clinical stage. We test how effective these compounds are in the lab and in early murine models, with the goal of identifying ones that could eventually become real treatment options.
What is a crucial aspect in your field?
Collaboration is key in AMR research because tackling antimicrobial resistance really does require input from many different fields. I also get a lot of motivation from the collaborative side of the work—getting to learn from others, share ideas, and see progress, even in small steps, is incredibly rewarding.
Within the COMBINE project, I worked together with the Department of Pharmacy of Uppsala University. Our team at SSI generated the in vitro and in vivo data, and Uppsala developed the PK/PD models based on that. The collaboration led to the findings we presented as a poster at the ESCMID Global Conference on 11–15 April 2025 and soon will be published as a joint manuscript.
What advice would you give other researchers or students interested in AMR research?
For anyone interested in AMR research, my biggest advice is to stay curious and be persistent. It’s a challenging field, and things don’t always go as planned, so being open to learning and able to adapt to changing projects is really important.
What scientific advancements are you most excited about?
One of the most exciting developments in AMR research, I think, is the use of Artificial Intelligence to help find new antimicrobial compounds and targets. It’s still a growing area, but it seems really promising because it can speed up the discovery process and help us explore options we might not find otherwise.
Can you describe a typical day for you?
There’s really no such thing as a typical day in my work, and that’s something I really enjoy! Some days are spent in the lab planning and running experiments; other days are more focused on analysing data, writing reports, or taking part in project meetings to discuss progress and collaborations.
How do you balance your professional and personal life?
Balancing work and personal life is really important to me, and I try not to bring work home when I can avoid it. In my free time, I enjoy reading, spending time with family, taking walks with my dogs, and going to the gym to stay active.
Want to know more? Take a look at other publications from COMBINE:
- Gadiya Y, Genilloud O, Bilitewski U, et al. Predicting Antimicrobial Class Specificity of Small Molecules Using Machine Learning. Journal of Chemical Information and Modeling. Published online February 23, 2025. doi:10.1021/ACS.JCIM.4C02347
- Fernow J, Olliver M, Couet W, et al. The AMR Accelerator: from individual organizations to efficient antibiotic development partnerships. Nature Reviews Drug Discovery 2024. Published online September 23, 2024. doi:10.1038/d41573-024-00138-9. Green Open Access available through DiVA.
- Arrazuria R, Kerscher B, Huber KE, et al. Expert workshop summary: Advancing toward a standardized murine model to evaluate treatments for antimicrobial resistance lung infections. Frontiers in Microbiology. 2022;13:988725. doi:10.3389/fmicb.2022.988725
- Arrazuria R, Kerscher B, Huber KE, et al. Variability of murine bacterial pneumonia models used to evaluate antimicrobial agents. Frontiers in Microbiology. 2022;13:988728. doi:10.3389/fmicb.2022.988728
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Bekeredjian-Ding I. Challenges for Clinical Development of Vaccines for Prevention of Hospital-Acquired Bacterial Infections. Frontiers in Immunology. 2020;11:533705. doi:10.3389/FIMMU.2020.01755