Behzad Mohebbi

Director, R&D – Grooming Analytical & Measurement Science Procter & Gamble

Agenda Day 2

As digital modelling expands the experimental possibilities available to R&D,

laboratory execution risks becoming the next bottleneck. This case study will

explore how physical AI, flexible automation and orchestration can connect

predictive models with physical experimentation to create faster, more

adaptive discovery workflows.

• Accelerate discovery by using physics-based simulation and neural

networks to prioritise the experiments most likely to deliver valuable results

• Enhance laboratory flexibility by replacing rigid automation with adaptable systems

that work across formulations, chemistries, analytical methods and devices

• Minimise experimental iteration by feeding laboratory results back into

predictive models to continuously improve future recommendations

Check out the incredible speaker line-up to see who will be joining Behzad.

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