Efficient allocation of medical supplies, equipment, and pharmaceutical inventories is crucial — especially in times of high demand like pandemics, seasonal outbreaks, or supply chain disruptions. Mismanagement can lead to shortages, delays in treatment, or wasted resources.

The Challenge:

• Medical resources are often managed reactively rather than proactively

• Forecasting demand is hard due to non-linear variables (e.g., patient influx, regional outbreaks, treatment duration)

• Traditional optimization models are limited by local minima and can’t scale in real-time across networks

• Overstocking leads to waste (especially for perishable drugs); understocking delays treatment

Quantum-Inspired Solution

Multi-Variable Forecasting

HessQ uses quantum-inspired models to simulate thousands of possible demand scenarios across facilities and time frames.

QUBO-based algorithms allocate supplies, beds, or medications based on evolving data — not static thresholds.

Ensures critical resources are sent to where they’re needed most, reducing idle stock and improving care equity.

Dynamic Inventory Optimization

Prioritized Resource Routing

The Result:

• Improved forecasting accuracy (up to +25%)

• Reduced overstock & understock costs

• Faster and smarter distribution of critical supplies

• Better shelf-life utilization for sensitive pharmaceuticals