Gain actionable strategies for embedding generative AI and large language models into early-phase trial design and execution, from protocol drafting and site selection to patient engagement, accelerating timelines while ensuring data quality and compliance
Reinforces trust and compliance by embedding robust data governance frameworks and ethical AI practices, to responsibly harness data and mitigate future regulatory risks.
Explore how AI-driven approaches enhance high-throughput screening by optimizing DNA-encoded libraries (DEL) for rapid identification of potential drug candidates.
Learn how AI algorithms accelerate the analysis of complex screening data, enabling more efficient lead discovery and targeting of molecular interactions.
Discuss how Lab in the Loop is revolutionizing drug discovery by integrating AI with experimental workflows, enhancing speed and accuracy in data collection and analysis.
Generoso Ianniciello is a strategic leader in life sciences with expertise in multi-omics, diagnostics, biopharma, and platform services. As Chief Business Officer at Anima Biotech, he leads the global strategy for the Biology GPU - a new category in drug discovery infrastructure that connects how AI thinks with how biology works, tackling one of the biggest challenges in the field.
Previously, as CBO at Dante Genomics, he scaled the start-up into a global enterprise with over 200 employees and $100 million in annual revenue. He launched the Dante MyGenome Platform for longevity, personalized medicine, and rare disease diagnostics, and built key partnerships with hospitals, biopharma, and research institutions worldwide.
Anima Biotech has built the biology runtime for AI - the Biology GPU.
The Biology GPU is the infrastructure layer that connects how AI thinks with how biology works. It enables AI models to visually compute inside cells in a closed loop of experimental reasoning, revealing the pathways that drive disease.
Powered by a Visual Biology Model trained on 2B+ proprietary cellular pathway images and technology that directly visualizes biological processes and pathways at AI scale, the Biology GPU runs visual experiments inside cells - identifying which pathways are active, how they interact, and where compounds act.
From pathways to targets, mechanisms to compounds, the Biology GPU transforms discovery into a runtime where AI engages directly with biology across the entire lifecycle.
Validated in 20+ discovery programs and collaborations with AbbVie, Takeda, and Lilly, Anima Biotech is defining the runtime infrastructure for AI in biology.
This session provides the unique opportunity to listen to, and engage with, some of the most innovative AI Drug Discovery and Development start-ups globally. Focusing exclusively on early-stage funding, six startups picked by our esteemed selection committee will take to the stage in front of 100+ potential partners. Through a series of rapid-fire presentations, these pioneers will demonstrate their vision of the future of drug discovery, and how their product, technology, or service fits into it.
Highlight how digital twins and hybrid ML models (e.g., Bayesian, predictive) enable virtual experimentation and proactive troubleshooting, reducing scale-up failures and supporting more reliable process performance at commercial scale.
Bolsters innovation agility by embedding ML Ops practices, aligning data science and IT workflows to ensure reliable, scalable AI deployments and a culture of continuous improvement.
Discover how ML and active learning techniques are revolutionizing the search for promising drug candidates in vast chemical libraries, accelerating hit identification.
Learn how AI models navigate ultra-large chemical spaces, prioritize bioactive compounds, and streamline the discovery of potential hits for further development.
