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www.bsc.es<\/a><\/strong>\u00a0|\u00a0LinkedIn<\/a><\/strong><\/p>\n [\/vc_column_text][\/vc_column_inner][vc_column_inner width=”3\/4″][vc_empty_space] <\/div><\/div>[vc_column_text css=””]<\/p>\n [\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row][vc_column][vc_empty_space] IDEAI-UPC<\/b><\/a>\u00a0<\/b>|\u00a0LinkedIN<\/a><\/strong><\/p>\n [\/vc_column_text][\/vc_column_inner][vc_column_inner width=”3\/4″][vc_empty_space] <\/div><\/div>[vc_column_text css=””]<\/p>\n [\/vc_column_text][vc_empty_space] [\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row full_width=”stretch_row” bg_type=”bg_color” bg_color_value=”#ffffff” css=”.vc_custom_1683718841357{padding-top: 30px !important;padding-bottom: 30px !important;}”][vc_column][vc_row_inner][vc_column_inner width=”1\/4″][vc_empty_space][vc_single_image image=”69567″ img_size=”full” css=””][vc_empty_space][vc_column_text css=””]<\/p>\n www.infini.es<\/a><\/strong> | LinkedIn<\/a><\/strong><\/p>\n [\/vc_column_text][\/vc_column_inner][vc_column_inner width=”3\/4″][vc_empty_space] <\/div><\/div>[vc_column_text css=””]<\/p>\n [\/vc_column_text][vc_empty_space] [\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][vc_row full_width=”stretch_row” bg_type=”bg_color” bg_color_value=”#ffffff” css=”.vc_custom_1683718841357{padding-top: 30px !important;padding-bottom: 30px !important;}”][vc_column][vc_row_inner][vc_column_inner width=”1\/4″][vc_empty_space][vc_single_image image=”69072″ img_size=”full” css=””][vc_empty_space][vc_column_text css=””]<\/p>\n www.aizon.ai<\/a><\/strong> | LinkedIn<\/a><\/strong><\/p>\n [\/vc_column_text][\/vc_column_inner][vc_column_inner width=”3\/4″][vc_empty_space] <\/div><\/div>[vc_column_text css=””]<\/p>\n [\/vc_column_text][vc_empty_space] [\/vc_column_text][\/vc_column_inner][\/vc_row_inner][\/vc_column][\/vc_row][\/vc_section]<\/p>\n<\/div>","protected":false},"excerpt":{"rendered":" [vc_section][vc_row css=”.vc_custom_1681910300131{padding-bottom: 30px !important;}”][vc_column][\/vc_column][\/vc_row][vc_row full_width=”stretch_row” bg_type=”bg_color” bg_color_value=”#ededed” css=”.vc_custom_1681913912294{padding-top: 30px !important;padding-bottom: 30px !important;}”][vc_column][vc_row_inner][vc_column_inner][vc_column_text css=””] AI is profoundly transforming biotechnology, from drug discovery to personalized diagnostics, synthetic biology, agrobiology, and more. This session highlights how the combination of algorithms and data is accelerating research and opening up new scientific and industrial possibilities in the field of life…<\/p>\n","protected":false},"author":3,"featured_media":68308,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[],"class_list":["post-69082","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-uncategorized-ca","category-1","description-off"],"yoast_head":"\nJUDITH GIROUD<\/h2><\/div>
Project Officer, Barcelona Supercomputing Center (BSC-CNS)<\/h4>\n
PhD in Biomedicine from the University of Barcelona. My career as a researcher has focused on aging, metabolism and stem cell biology. I have an Executive MBA and currently work as a Project Officer at BSC, where I lead training and digitalization projects for companies within the framework of DIH4CAT.<\/h4>\n
Speakers<\/h2><\/div>
KARINA GIBERT<\/h2><\/div>
Dean of the Computer Engineering College of Catalonia, COEINF<\/h4>\n
Professor at the UPC-BarcelonaTech. Graduate and PhD in Computer Science with specialization in computational statistics and artificial intelligence. Dean of the COEINF. Vice-president of the General Council of Professional Colleges of Informatics Engineering of Spain. Founder of donesCOEINF, DonesIAcat and co-founder of Mujeres en Ingenier\u00eda Inform\u00e1tica and BCN chapter of women in ACM. Awards 100 most influential women in Catalonia (Forbes 2025), Medal of Honor of the Parliament of Catalonia 2025, WomenTech 2023 (Women360), National Award for Computer Engineering 2023, DonaTIC2018 Award (GenCat).<\/h4>\n
Applications of artificial intelligence to the integration of omic data in the analysis of complex phenomena<\/h4><\/div><\/div>[vc_empty_space][vc_column_text css=””]<\/p>\n
This talk explores the possibilities offered by artificial intelligence to integrate the analysis of omic data with the context information of the person, allowing for a more holistic approach.<\/h4>\n
NICOL\u00c1S FERNANDEZ<\/h2><\/div>
Director of Technology and Operations, Infini Partner<\/h4>\n
Nicol\u00e1s Fern\u00e1ndez holds a degree in Industrial Engineering from the National University of Tucum\u00e1n (Argentina) and a Master’s in Engineering and Business from the University of Barcelona. He currently leads the Technology and Operations division at Infini, where he develops process automation and applied AI initiatives.<\/h4>\n
Intelligent Automation in Human Genome Analysis<\/h4><\/div><\/div>[vc_empty_space][vc_column_text css=””]<\/p>\n
Artificial intelligence is revolutionizing clinical genetic analysis by automating key tasks such as phenotype identification, variant classification under ACMG criteria, and the creation of personalized diagnostic reports. These processes, traditionally manual, demand high specialization and are prone to errors and inconsistencies. This session will present a real-world use case demonstrating how AI significantly reduces turnaround times, enhances diagnostic precision, and acts as a powerful clinical support tool within hospital environments.<\/h4>\n
TONI MANZANO<\/h2><\/div>
CSO and co-founder, Aizon<\/h4>\n
Toni is the co-founder and CSO of Aizon, a cloud company that provides an AI SaaS platform for the Biotech and Pharma industry. He is member of the PDA Regulatory Affairs and Quality Advisory Board and co-chair of the Advanced Manufacturing and Applied Process Digitalization PDA Interest Group. Toni teaches AI subjects at the university URV and OBS, and SME for the United Nations in AI subjects in Life Sciences. He has written numerous articles in the Pharma field and holds a dozen international patents related to the encryption, transmission, storage and processing of large volumes of data for regulated environments in the cloud. Toni is Physicist, PhD, and Master in Information and Knowledge Society and post graduated in quality systems for manufacturing and research pharmaceutical processes.<\/h4>\n
AI industrialization in drug manufacturing: challenges and benefits<\/h4><\/div><\/div>[vc_empty_space][vc_column_text css=””]<\/p>\n
The industrialization of AI in drug manufacturing is a critical step toward achieving scalable, efficient, and compliant production processes. While AI has demonstrated its potential in predictive quality control, process optimization, and deviation reduction, the challenge lies in scaling AI models beyond pilot projects and ensuring seamless integration within regulated environments, like drug manufacturing.
\nKey barriers to AI industrialization include fragmented data ecosystems, lack of standardized model formats, and regulatory concerns around AI validation and lifecycle management. A major enabler for overcoming these challenges is the adoption of open and scalable AI model formats, such as ONNX (Open Neural Network Exchange), which allows AI models to be deployed across different platforms and hardware without requiring complex reengineering. By leveraging ONNX and model compression techniques, pharmaceutical manufacturers can efficiently scale AI applications from research environments to industrial production, ensuring compatibility with existing manufacturing execution systems and real-time process control architectures.
\nThe relevance of this topic is critical as AI adoption accelerates in Good Manufacturing Practices (GMP) operations. Without scalable deployment strategies, AI remains confined to isolated use cases, limiting its transformative impact. By leveraging ONNX and cloud-based AI model deployment, pharmaceutical companies can unlock AI\u2019s full potential, enabling real-time, AI-driven decision-making at an industrial scale while ensuring regulatory compliance.
\nThis session will provide attendees with a roadmap for AI scalability, covering best practices for deploying AI in large-scale production environments, optimizing model inference performance, and ensuring AI models remain adaptable to dynamic manufacturing conditions.<\/h4>\n