Bioengineering

Bioengineering
BENG Research Labs

BENG comprises 6 Research Labs in the Lisbon pole in a total of 24 integrated members (7 permanent faculty & research staff and 17 non-permanent research staff) who supervise 38 PhD students. This group applies bioengineering principles, as well as artificial intelligence-based models, to develop and optimize bioprocesses and bio-inspired solutions to address challenges in the health and the bioeconomy.

 

Leveraging our unique pilot plant facilities and industrial partners, the scale-up of bioprocesses will be done to ensure cost-effective and sustainable production of biopolymers from wastes and translation to industry. Emphasis will be given to online spectroscopic tools for real-time bioprocess control. Also, BENG will develop deep hybrid modelling tools that merge first-principles models, AI and deep learning along 3 focus areas: 1) Bioprocess digital twins for industry 5.0; 2) AI for metabolic engineering; 3) In silico culture media design.

 

On biomanufacturing, BENG will also contribute to the development of more sustainable fermentation (ongoing Pathfinder projects) and downstream processes (ongoing FET-OPEN project) aiming at reducing the cost and environmental footprint of biologicals manufacturing.

 

Research also focuses on developing sensors for health and environmental applications, using biodegradable and stimuli-responsive biomaterials. Specifically, the olfaction-inspired materials and technologies from two ERC PoC grants will provide new solutions for managing bladder cancer and diagnosing Parkinson's disease. Additionally, a high-throughput screening platform for olfactory evaluation, with implications for the fragrance industry, will be developed.

 

Exploration of the actinobacteria biorepository, housing over 1500 strains from the Macaronesia Atlantic ecozone, as cell factories for producing pharmaceutical compounds and biopolymers with diverse properties, will continue, thereby contributing to the growth of Blue Bioeconomy.


Recent publications
Oliveira, CD; de Souza, JN; Barreto, NMPV; Araújo, AWC; Sousa, JR; Marauxa, VAP; Pinheiro, CD; Almeida, MG; Teixeira, MCA; Soares, NM. 2025. Immunodominant Molecules for the Immunodiagnosis of<i> Strongyloides</i> stercoralis Infection. DIAGNOSTIC MICROBIOLOGY AND INFECTIOUS DISEASE, 111, DOI: 10.1016/j.diagmicrobio.2024.116649
Freitas, C; Eleutério, J; Soares, G; Enea, M; Nunes, D; Fortunato, E; Martins, R; Aguas, H; Pereira, E; Vieira, HLA; Ferreira, LS; Franco, R. 2025. Towards Rapid and Low-Cost Stroke Detection Using SERS and Machine Learning. BIOSENSORS-BASEL, 15, DOI: 10.3390/bios15030136
Almeida, JR; Leon, ES; Corona, EL; Fradinho, JC; Oehmen, A; Reis, MAM. 2023. Ammonia impact on the selection of a phototrophic - chemotrophic consortium for polyhydroxyalkanoates production under light-feast / dark-aerated-famine conditions. WATER RESEARCH, 244, DOI: 10.1016/j.watres.2023.120450
Concordio-Reis, P; Ferreira, SS; Alves, VD; Moppert, X; Guezennec, J; Coimbra, MA; Reis, MAM; Freitas, F. 2023. Rheological characterization of the exopolysaccharide produced by Alteromonas macleodii Mo 169. INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES, 227, DOI: 10.1016/j.ijbiomac.2022.12.117
de Almeida, MP; Rodrigues, C; Novais, A; Grosso, F; Leopold, N; Peixe, L; Franco, R; Pereira, E. 2023. Silver Nanostar-Based SERS for the Discrimination of Clinically Relevant Acinetobacter baumannii and Klebsiella pneumoniae Species and Clones. BIOSENSORS-BASEL, 13, DOI: 10.3390/bios13020149