Silos forced teams to manually chase data. Now, AI agents identify adverse events in seconds, eliminating weeks of cross-referencing.
A century-old global pharmaceutical company generating billions of data points from clinical trials across diabetes, obesity, and chronic disease research, with over 60 teams operating across eight cloud regions.
Clinical trial data lived in a 'patchwork spiderweb' of fragmented, individually managed storage solutions, with no single person holding knowledge...
“We’re at a crossroads of democratizing data access to a wider number of people so that insights can be leveraged by more.”
Pharmaceutical company specializing in diabetes, obesity, and rare blood disorders.
Databricks is a Big Data company that offers a unified analytics platform for data science, engineering, and analytics teams.
Novo Nordisk's Clinical data insights is part of this use case:
Related implementations across industries and use cases
Validating hypotheses took specialists weeks of manual coding. Now, an AI agent drafts analyses for expert review in minutes.
Teams reactively managed trials across scattered systems. AI now integrates data to predict bottlenecks and recommend interventions.
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
Teams reactively managed trials across scattered systems. AI now integrates data to predict bottlenecks and recommend interventions.
Target assessments took a full quarter. Now, AI agents synthesize 1,000+ datasets to finish in hours.
A maze of disconnected systems obscured global trial visibility. Now, a digital twin guides AI to automate heavily regulated workflows.
Every HCP response required manually searching regulated literature. Now agents surface cited answers from 3,100+ medical documents.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.
Silos forced teams to manually chase data. Now, AI agents identify adverse events in seconds, eliminating weeks of cross-referencing.
A century-old global pharmaceutical company generating billions of data points from clinical trials across diabetes, obesity, and chronic disease research, with over 60 teams operating across eight cloud regions.
Clinical trial data lived in a 'patchwork spiderweb' of fragmented, individually managed storage solutions, with no single person holding knowledge...
“We’re at a crossroads of democratizing data access to a wider number of people so that insights can be leveraged by more.”
Pharmaceutical company specializing in diabetes, obesity, and rare blood disorders.
Databricks is a Big Data company that offers a unified analytics platform for data science, engineering, and analytics teams.
Novo Nordisk's Clinical data insights is part of this use case:
Related implementations across industries and use cases
Validating hypotheses took specialists weeks of manual coding. Now, an AI agent drafts analyses for expert review in minutes.
Teams reactively managed trials across scattered systems. AI now integrates data to predict bottlenecks and recommend interventions.
Custom analytics required months of full-stack development. Now, self-serve AI apps connect analysts directly to data models.
Teams reactively managed trials across scattered systems. AI now integrates data to predict bottlenecks and recommend interventions.
Target assessments took a full quarter. Now, AI agents synthesize 1,000+ datasets to finish in hours.
A maze of disconnected systems obscured global trial visibility. Now, a digital twin guides AI to automate heavily regulated workflows.
Every HCP response required manually searching regulated literature. Now agents surface cited answers from 3,100+ medical documents.
Tournaments running simultaneously meant an hour of manual checks each. AI agents now run them in minutes, freeing the team to be proactive.
Large AI training jobs meant fighting for preemptible slots or leaving campus. Marlowe gave any lab guaranteed multi-node access on demand.