STUDENT SHOWCASE
Our students bring cutting-edge research to life through dynamic presentations that bridge computational biology, structural biochemistry, and artificial intelligence.
Explore their work below.
Rare Diseases Meet AI
This thought-provoking video explores the intersection of artificial intelligence and rare disease diagnosis, a field where over 300 million people worldwide face years of uncertainty before receiving a correct diagnosis.
The presentation makes a compelling case for AI as a support tool: capable of detecting invisible patterns in large datasets, yet fundamentally unable to replace the human judgment, empathy, and ethical responsibility at the heart of medicine. Through interviews with a physician and a patient, the video captures two honest perspectives on trust, privacy, and the limits of algorithmic decision-making. Dr. Ricardo Almeida emphasises that AI should enhance clinical capability, not eliminate the human role. Luisa Silva, living with Huntington’s disease, voices both cautious optimism, AI can accelerate diagnosis and improve treatment, and a real concern for data privacy and personal autonomy.
The video closes with a clear message:
AI recognises patterns. Decisions remain human.
By Ana Fernandes, Manuel Couto and Vicente Caiado
Supercomputadores Que Aceleram a Ciência
Esta apresentação cativante mergulha no mundo dos receptores acoplados à proteína G (GPCRs) — os “interruptores” celulares que controlam tudo, desde batimentos cardíacos a pensamentos. Beatriz e Ana explicam como estes receptores críticos, alvos de um terço de todos os fármacos modernos, respondem a sinais químicos como chaves encaixando em fechaduras.
Usando simulações de dinâmica molecular suportadas pelo supercomputador Mar Nostrum 5, uma das máquinas mais poderosas da Europa, elas revelam como os átomos se movem segundo a segundo, desvendando as mudanças estruturais por trás da função saudável e da doença. Desde receptores de dopamina ligados a distúrbios cerebrais até ao design de fármacos, este trabalho mostra como a supercomputação transforma insights moleculares de meses para meras horas.
Desenvolvido com apoio da SCT e alojado no Mar Nostrum 5.
By Ana Beatriz and Ana Amorim published at FCCN educast.
GPCRs and Computational Drug Design
This visually striking animation explores GPCRs — the largest protein family in the human genome and targets of over 30% of approved drugs. Beginning with the Nobel Prize-winning discovery of rhodopsin, it traces the evolution of GPCR research from static structures to dynamic computational modelling.
The video highlights how AI-powered structural biochemistry accelerates drug discovery, from predicting protein function to analysing omics data and repurposing existing drugs. It celebrates the “powerful synergy” of physics-based calculations and machine learning revolutionising biosciences.
By Urszula Orzel and Luana Afonso
AI-Enhanced Toxicity Prediction
Addressing a critical bottleneck in drug development — where one-third of candidates fail due to toxicity — this presentation outlines the four phases of drug discovery and the limitations of traditional testing methods. While animal studies predict human toxicity with only 30% accuracy, AI offers a breakthrough.
By analysing chemical structures and vast toxicity datasets, machine learning models identify harmful compounds earlier, reducing animal testing and cutting costs. The video emphasises collaboration and data sharing as essential for advancing AI-driven toxicity prediction, promising safer drugs and improved public health.
By Ana Amorim
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