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Explore how life sciences organisations can leverage Databricks to address data complexity and establish an AI-ready foundation for clinical and R&D operations.
How do life sciences organisations turn complex clinical and R&D data into an AI-ready foundation with Databricks?
Life sciences organizations can unlock significantly more value from clinical and R&D data by making it AI-ready: consistently described, governed, discoverable and harmonized.
This enables clinical, scientific and data teams to find relevant datasets faster, combine studies more safely, detect issues earlier and generate insights with less manual effort.
Featuring real-world life sciences examples and outcomes, this session gives clinical and data teams a clear roadmap to AI-powered clinical trial analytics and discovery on Databricks.
Topics include:
- Reducing dependency on manual data engineering: By using governed metadata, Unity Catalog and Genie, teams can reduce the manual effort normally required to find datasets, understand schemas, harmonize studies and prepare analysis-ready data.
- Accelerating clinical trial analytics: Clinical teams can move faster from raw study data to insights by automating parts of dataset discovery, study comparison, anomaly detection and insight generation.
- Improving cross-study analysis quality: The harmonisation angle is important. AI can help detect schema conflicts, inconsistent value encodings, missing context and semantic mismatches before they create analytical errors.
Is this webinar for you and what you will take away?
Data, digital, and IT leaders in life sciences
Platform owners, heads of data & analytics, CDOs, and Databricks leads responsible for building and governing AI-ready clinical and R&D data platforms.
What you will take away:
- How to assess and close the gap between your current data estate and a truly AI-ready platform using, Unity Catalog as the governance backbone
- Proven approaches to standardising how clinical and R&D data is named, described, tagged, and contracted, so every new dataset immediately extends your AI capabilities
- How to design a data ecosystem where AI agents autonomously discover, validate, and harmonise datasets across studies and systems, reducing reliance on manual engineering
- A replicable architecture and delivery roadmap you can bring back to your organisation and begin executing against immediately
R&D, clinical operations, and biometrics leaders
Clinical innovation leaders, biometrics directors, and translational research leads who need better insight and decision-making from complex trial data.
What you will take away:
- How AI can answer complex scientific questions directly from clinical and trial data, without requiring researchers to understand the underlying data structure or engineering pipelines
- What it looks like in practice when AI agents surface anomalies, reconcile datasets across studies, and generate insights in real time with examples drawn from life sciences environments
- How to make the case internally for AI-powered clinical analytics, and what governance and platform investments are needed to make it a reality
- A clearer picture of the decisions your data teams need to make today to accelerate your organisation's path to AI-driven R&D and clinical trial intelligence
About our speakers
Santiago Gutierrez Orta, Senior Consultant | ADC
Santiago is a Senior Consultant at ADC, based in Copenhagen, working with health and life science clients on data and AI solutions in pharma and medtech. Over the past three years he has been involved in cloud-based data platform projects, data modelling and transformation work for R&D teams, and building solutions mainly on AWS and Databricks with a focus on optimization, simplicity, robustness, and data confidentiality. His background covers data engineering, machine learning, and statistical modelling. He has a personal interest in molecular data, bioinformatics, and chemistry, and enjoys the challenge of turning complex scientific questions into something a data platform can actually work with. At this session he will share what he has learned about making clinical and R&D data ready for AI, with practical examples from the field.
LinkedIn
Jacob Vestergaard, Principal & Head of Commercial | ADC
Jacob Vestergaard is a Principal and Head of Commercial at ADC Denmark, where he leads strategic client partnerships and commercial development across the Nordic market. Before joining ADC, Jacob spent over 11 years at Microsoft in senior data, AI and consulting sales roles, leading high‑performing teams and driving large‑scale cloud and digital transformation programs for some of Denmark’s largest enterprises. This experience gives him a deep understanding of how to align complex technology agendas with commercial outcomes in enterprise settings. He works with senior stakeholders to shape data and AI roadmaps, connecting ADC’s technical expertise with concrete business outcomes in sectors such as retail, transportation and financial services. Jacob frequently collaborates with cross-functional teams on offerings like Databricks-based data platforms and AI capability building, ensuring ADC’s solutions are grounded in real customer needs and deliver measurable commercial impact.
LinkedInEvent details
Date and time: Friday 19th of June | 10:00 - 11:00
Location: Online
Duration: 1 hour
Get in touch
Questions about the event?
Contact Jacob Vestergaard at jacob.v@adc-consulting.com