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Transforming trading ecosystems through data-driven insights and secure, agile platforms that empower global commerce.
Customer & Marketing Strategy
Reimagining customer engagement with personalized, connected experiences that build trust and long-term value.
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Turning ideas into scalable digital solutions—accelerating transformation through design, technology, and engineering excellence.
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Redefining mobility hubs with digital innovation to create smarter, sustainable experiences for people and businesses on the move.
Supply Chain & Industry 5.0
Building resilient, intelligent supply networks that anticipate change and deliver efficiency with purpose.
Sustainability
Driving responsible innovation to help organizations achieve net-zero goals and create a positive impact for future generations.
Business Talk
Digital Lab of the Future
Reinventing pharmaceutical R&D by combining AI, robotics, and data-driven experimentation
Traditional laboratory processes are slow, siloed, and highly manual, limiting productivity and extending drug development timelines.
Why digital lab of the future?
The Digital Lab of the Future integrates AI models, robotics, and advanced data platforms to orchestrate experiments end to end.
By digitizing workflows and leveraging predictive analytics, laboratories move from trial-and-error experimentation to data-driven discovery, reducing costs and time-to-insight while increasing scientific quality. This delivers where science meets automation—from experiments to intelligence.
Key benefits
Faster experiment cycles and optimization
Improved data quality and reuse
Integration with legacy lab systems
Change management for scientific teams
How NTT DATA helps
01
Digital lab strategy and roadmap
02
AI models for molecule optimization
03
Robotics and workflow orchestration
04
Unified R&D data platforms
05
Change enablement for researchers
Proven impact
R&D productivity, redefined
Results that matter
Pharma & Life Science organizations achieve measurable improvements:
Experiment cycles
Reduced duration
R&D cost per candidate
Lowered
Data reuse
Increased utilization
Reinvent pharmaceutical R&D with AI, robotics, and data-driven experimentation
Accelerate discovery with intelligence
