LATIN AMERICAN HIGH PERFORMANCE COMPUTING CONFERENCE

BioCARLA

Accelerating Biomedical and Personalized Medicine through Digital Twins, In Silico Clinical Trials, AI/HPC

Chairs Workshop

  • John Garcia-Henao – Balgrist University Hospital, Switzerland. 
  • Elmer Fernández – Universidad Nacional de Córdoba, Córdoba, Argentina.

Description of the workshop

The 8th edition of the BioCARLA workshop continues to serve as a key forum within the CARLA conference series, bringing together experts in bioinformatics, biomedical engineering, high-performance computing (HPC), and artificial intelligence. In alignment with the PASC26 minisymposium1, BioCARLA 2026 focuses on AI-driven in-silico clinical trials (ISCTs) and medical digital twins as emerging paradigms for accelerating biomedical and personalized medicine. 

While AI has achieved strong performance in isolated clinical tasks, current systems remain limited in multimodal reasoning, generalization, and clinical integration. This workshop explores how large multimodal models (LMMs) and computational patient models enable the transition from single-task AI systems to virtual patient cohorts and in-silico experimentation. 

BioCARLA 2026 aims to bridge AI research, HPC, and clinical practice, fostering interdisciplinary collaboration toward scalable, trustworthy, and clinically actionable virtual trial frameworks. 

The workshop centers on five key challenge areas: 

  1. Multimodal integration of imaging, clinical, omics, and sensor data 
  2. Embedding clinical and physiological knowledge into AI models 
  3. Trustworthy AI: interpretability, robustness, and validation 
  4. Data governance, privacy, and ethical AI deployment 
  5. Scalable infrastructure using HPC, federated, and distributed systems

Submission format

BioCARLA 2026 will feature a mix of peer-reviewed papers and invited contributions, with a focus on reproducibility, methodological rigor, and translational relevance. The program is committed to a fair and streamlined peer-review process.

Proposed program committee (to be confirmed)

  • Kary Ocaña, National Laboratory of Scientific Computing, Brazil
  • Francisco Martínez, Industrial University of Santander, Colombia
  • Carla Osthoff, National Laboratory of Scientific Computing, Brazil
  • Dante Travisany, Americas University, Chile 
  • Denis Jacob Machado, University of North Carolina at Charlotte, USA 
  • Fabricio Alves Barbosa da Silva, Oswaldo Cruz Foundation, Brazil
  • Gustavo Fioravanti Vieira, Universidade La Salle, Brazil 

Call for papers

We invite high-quality submissions addressing the development, validation, and deployment of AI-driven in-silico clinical trials, digital twins, and multimodal biomedical AI systems. Contributions may include theoretical advances, computational frameworks, and real-world clinical applications. 

We welcome two types of contributions: 

  • Regular papers: 6-8 pages, including figures and references, to be presented as oral talks.
  • Short papers: Up to 2 pages, for poster presentations. 

Submission Guidelines 

All submissions must follow the formatting and submission rules provided by CARLA 2026:

  • Paper submission: https://carlaconference.org/call-papers/ 
  • Poster submission: https://carlaconference.org/call-posters/ 

Accepted papers and posters will be included in the CARLA 2026 workshop proceedings. 

Topics of Interest

  • Development and application of small and foundation models in biomedical and life sciences. 
  • Predictive modeling of disease risk, patient outcomes, and treatment response using AI.
  • Multimodal learning integrating omics, clinical text, imaging, and phenotypic data.
  • Interpretability, fairness, and trust in biomedical AI and clinical decision systems.
  • Federated learning and privacy-preserving AI for distributed biomedical research.
  • Training and deployment of efficient biomedical language models and domain-specific LLMs. 
  • Integration of HPC, cloud, and edge computing for bioinformatics and AI workflows.
  • Design and optimization of HPC-enabled workflows for multi-omics and systems biology.
  • Big data analytics and performance evaluation of omics pipelines using HPC infrastructure.
  • Network biology, evolutionary modeling, and functional annotation using AI and HPC.
  • Benchmarking datasets, reproducibility, and standardization for biomedical AI models.
  • Real-world applications of small and foundation models in drug discovery, clinical documentation, and genomics. 

Previous workshop editions