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Wednesday, 19 Nov, 2025RegistrationMorning BreakMorning Sessions
Discuss how AI is used to identify pathological features, discover drug targets, and decode complex disease biology at a systems level.
Discuss how AI revolutionizes drug design through de novo creation of novel molecular scaffolds.
Explore how machine learning integrates with synthetic chemistry.
Empowers strategic R&D with AI-driven predictive modelling early in discovery, fostering a data-driven culture.
Learn how predictive simulations and dynamic cohort adjustments can accelerate your go/no‑go decisions, helping you cut prototyping timelines by weeks and reduce per‑trial costs.
Afternoon SessionsExplore how AI integrates multiomics data to enhance understanding of complex diseases and improve target identification and validation.
Examine how AI tools predict key molecular properties such as solubility, permeability, and metabolic stability.
Discover methods for evaluating drug-like features and mitigating off-target risks.Guides strategic IT decisions by clarifying trade-offs between cloud and on-premise solutions, to align infrastructure strategy with agility, security, and compliance objectives.
Gain practical strategies for continuous AI‑based safety monitoring post‑approval, enabling proactive lifecycle management that drives down long‑term surveillance spend.
LunchAfternoon SessionsExplore how AI is transforming biomarker discovery in the lab by analyzing large datasets to uncover novel biomarkers for disease diagnosis and therapeutic efficacy.
Learn how AI-driven virtual screening filters vast chemical libraries to identify promising candidates.
Discuss the application of QSAR models to predict biological activity and optimize lead compounds.Strategic insights from complex, high-dimensional healthcare data, fostering integrated analytics and strengthening the organization’s competitive edge in precision medicine.
Showcasing generative models that craft hyper‑personalized outreach messages and informed consent materials, driving up engagement rates and shaving weeks off recruitment timelines.
Discover how ML‑driven forecasts for recruitment rates and optimized site selection translate into faster first‑patient‑in and lower screen‑fail/dropout rates, saving you both time and budget.Explore how ML-enabled real-time control systems and continuous process verification improve yield predictability, reduce rework, and enable faster release - offering a direct line of sight to cost savings and product quality gains.
Understand how AI can be used to optimize biologic drug design, particularly in antibody engineering and protein structure prediction.
Understand how AI forecasts reaction outcomes to streamline synthetic planning.
See how reaction prediction models minimize experimental trial and error.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.
See how AI‑powered feasibility assessments and automated start‑up workflows can slash administrative cycle times, freeing your team to focus on critical clinical oversight.
Afternoon Break -
Thursday, 20 Nov, 2025Morning Sessions
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.
Morning BreakMorning SessionsDiscuss how Lab in the Loop is revolutionizing drug discovery by integrating AI with experimental workflows, enhancing speed and accuracy in data collection and analysis.
Discuss the transformation of synthetic workflows by integrating AI into lab automation.
Discover how real-time data analysis and automated systems enhance reaction efficiency and reproducibility.Reinforces trust and compliance by embedding robust data governance frameworks and ethical AI practices, to responsibly harness data and mitigate future regulatory risks.
Understand how NLP and computer‑vision tools for real‑time data ingestion, normalization, and QC can eliminate manual queries, reducing data‑lock delays and speeding interim analyses.
Demonstrating LLM‑based data mapping and error‑correction pipelines that automatically normalize free‑text entries, generate query explanations, and cut manual QC workloads in half.Afternoon SessionsLearn how AI algorithms generate entirely new chemical structures, expanding the realm of drug-like molecules.
Understand the synergy between AI-driven design and traditional medicinal chemistry practices.Harnesses collaborative innovation networks to integrate external expertise and accelerate breakthrough AI development.
Learn to deploy anomaly‑detection models that flag safety signals earlier, streamline DSMB reviews, and accelerate regulatory reporting, cutting risk and compliance costs.
LunchAfternoon SessionsAddress the challenges of transforming multi-source biological datasets into standardized formats for AI compatibility.
Address challenges in constructing robust QSAR models from diverse datasets.
Explore best practices in data normalization, model validation, and performance enhancement.Safeguards the innovation pipeline by proactively securing sensitive research data, enhancing risk resilience and ensuring stakeholder confidence in the integrity of AI-driven discoveries.
Explore integrating predictive analytics into lab and imaging workflows to fast‑track endpoint review, deliver interim insights sooner, and shorten your time‑to‑efficacy.
Highlighting generative tools that draft preliminary adjudication reports from imaging and lab data, surface key findings, and accelerate DSMB reviews by providing concise, AI‑written summaries.Understand how AI governance frameworks and model documentation tools streamline audit readiness, reduce inspection prep burden, and support confident regulatory engagement without stalling innovation.
Understand how AI-powered single-cell technologies enable insights into cellular heterogeneity and disease progression.
Understand how integrating virtual screening with reaction prediction offers a comprehensive strategy in drug design.
See how advanced data integration improves candidate selection and expedites discovery pipelines.Forges powerful ecosystems by aligning pharma, tech, and academia, enabling shared expertise and resources to accelerate breakthroughs and navigate complex R&D challenges.
Equip yourself with KPI dashboards and financial models to quantify time‑to‑value, optimize resource allocation, and build a compelling business case for AI investment.
Afternoon Break
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