Explore practical strategies for scaling AI implementation across clinical development pipelines, enabling faster trial execution, smarter protocol design, and improved patient recruitment while aligning with evolving regulatory expectations.
Explore h ow AI models predict protein 3D structures from sequences, enabling insights into folding pathways and functional conformations
Examine emerging co-folding models that reveal protein–protein interactions and guide multimeric complex design.
Learn how AI-driven approaches integrate multiomics data, including genomics, proteomics, and transcriptomics, to identify potential drug targets and disease biomarkers for complex diseases.
Explore how AI models synthesize cross-omic data and real-time multiomic information to uncover novel biological mechanisms, identify potential biomarkers and enable precision medicine.
Together with our colleagues, customers and stakeholders, we impact life and health with science. Before researchers can make scientific breakthroughs, they must have access to state-of-the-art tools, services and expertise to perform experiments and engineer new products. That’s where we come in.
We offer one of the broadest portfolios in the industry for scientists, best-in-class products for pharmaceutical development and manufacturing, and a fully integrated service organization to support CDMO and contract testing across traditional and novel modalities.
Our vision is a world where our innovative products, services and digital offerings help create solutions for people globally and a sustainable future for generations to come.
The life science business of Merck KGaA, Darmstadt, Germany, operates as MilliporeSigma in the US and Canada. Merck KGaA, Darmstadt, Germany is a global science and technology company with around 60,000 employees in more than 66 countries.
Demonstrate how AI-driven initiatives - like predictive modelling and automated inspection -translate into measurable outcomes (e.g., defect reduction, shorter batch release cycles) that justify capital investment and cross-functional prioritization.
Learn how predictive simulations, generative AI and differentiating clinical biomarkers are forecasted to cut prototyping timelines by weeks and reduce per‑trial costs.
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At Salesforce, Hitesh is responsible for the end-to-end architecture of platforms delivered to financial services and insurance clients globally. His focus is on working with key strategic customers to align Salesforce implementations with their business goals, particularly around the conjunction of Data+AI and CRM. This involves collaborating with retail and commercial banking, payments, wealth management, investment banking, insurance, and capital markets to influence product roadmaps and shape the future of technology in these industries. A significant part of Hitesh's role includes facilitating discussions with CTOs, CIOs, CDOs, and Chief Architects to: • Analyze current architectures and design target states. • Optimize Salesforce technologies for customer needs. • Integrate and Interoperate with Salesforce platforms within broader ecosystems. Being the executive sponsors for the customers, I play a key role in influencing product development within Salesforce by advocating for customer-driven innovations.
Hitesh oversees end-to-end platform and solution architecture for global financial services and insurance clients. He specializes in aligning Salesforce solutions with strategic business objectives, particularly at the intersection of Data+AI and CRM. By collaborating with retail and commercial banking, payments, wealth management, investment banking, insurance, and capital markets, Hitesh helps influence product roadmaps and shape the future of technology in these industries.
A key part of his role involves engaging CTOs, CIOs, CDOs, and Chief Architects to analyze current architectures, design target states, and optimize Salesforce within broader ecosystems. As an executive sponsor, Hitesh champions customer-driven innovation, ensuring product development meets evolving industry needs.
Empowers strategic R&D with AI-driven predictive modelling early in discovery, fostering a data-driven culture.
Learn how GenAI is transforming early drug discovery by designing novel, drug-like small molecules with improved potency, selectivity, and ADME properties.
Explore how GenAI integrates with synthesis planning and automation tools to prioritize viable candidates and accelerate iterative drug development.
Discuss how AI is used to identify pathological features, discover drug targets, and decode complex disease biology at a systems level.
