Why Attend the Practical AI for Drug Discovery & Preclinical Development Summit?
Your one-stop shop to capturing industry’s most exciting AI use cases to advance towards data-driven solutions
As the global AI for drug discovery market is expected to grow from $1.5 billion in 2023 to $9.1 billion in 2030, the Practical AI for Drug Discovery & Preclinical Development Summit is a must-attend meeting to capture all the latest case studies you need to contribute to the paradigm shift.
Diving into the advances in generative AI,in silico screening, spatial analytical tools, organ-on-a-chip technology, ML-based image analysis, large language models and multimodal, this is your exclusive learning and networking opportunity to advance your pipelines with more precise drug discovery efforts and faster preclinical stages.
Don’t miss out on hearing from 17 AI experts over 3 days jam-packed with all the latest AI use cases and methods to overcome the data paucity challenge, develop trustworthy and interpretable models, identify appropriate context experts and infrastructure, and standardize the approach towards data acquisition and sourcing.
Turbocharge early drug discovery efforts by successfully identifying novel targets with Insilico Medicine, Pfizer and Skaggs School of Pharmacy and Pharmaceutical Sciences by leveraging structure-based generative chemistry, in silico screening and predictive ML models
Explore an ML approach used to identify subphenotypes in heterogeneous diseases with GEn1E Lifesciences to improve accuracy and optimise drug discovery
Effectively apply AI on image and omics data with Evaxion Biotech to better gain insight into treatment effect and improve novel personalized treatment
Streamline cross-functional relationships with Takeda to successfully transition into the next generation techniques for protein design
Analyse RNA-seq data and validate novel neoepitopes using AI with Envisagenics to develop safe immunotherapies with limited off-target effects
Who Could You Meet?
What Your Peers Have to Say:
"Good opportunity to learn about new methods, models, and ways to answer different drug discovery questions"
"Networking and hearing from big pharma companies’ methodology was really impactful"
"The domain knowledge each speaker brought to the conference is impressive"