Pfizer Advances Production Planning with Hybrid Quantum Optimization

Improving Scheduling Efficiency at Pfizer’s Freiburg Manufacturing Site

Pfizer Inc. is one of the world’s largest biopharmaceutical companies, operating a complex global network across R&D, manufacturing, and distribution. Its products span critical therapeutic areas like oncology, immunology, and vaccines, requiring precise, multi-stage production under strict quality and regulatory standards.

Efficient scheduling is essential to manage this scale and complexity.

To explore next-generation planning solutions, Pfizer partnered with D-Wave and QuantumBasel to conduct a Proof of Technology (PoT) using a hybrid Quantum-classical annealing approach. The goal: improve production scheduling at Pfizer’s Freiburg plant compared to existing and newly optimized classical methods.

The Challenge

Pfizer's Freiburg site faced significant complexity in its production planning. The plant operates under conditions of high resource utilisation and interdependent, multi-stage manufacturing processes operated in product campaigns.

In addition, the schedule needs to be flexible and quickly adaptable to any unforeseen events or changes in the production process. Last-minute schedule changes require significant manual effort and expertise, making it hard to consistently optimize for delivery, output, and cost. The result is a need for more agile, intelligent scheduling solutions that can reliably handle these dynamic conditions and enhancing the utilization rate of the machines.

The Approach

In collaboration with QuantumBasel and D-Wave, Pfizer initiated a Proof of Technology (PoT) project to explore advanced methods for job shop scheduling.

The primary objective was to evaluate the effectiveness of hybrid Quantum-classical annealing methods compared to the current production solution as well as to compare against a newly designed classical high-performance computing (HPC) solution in optimising a six-week production campaign at the Freiburg site.

The project aimed to improve critical performance metrics while assessing the potential for scalable implementation across Pfizer's global manufacturing network. This initiative has brought together local and global stakeholders to test the viability of next-generation computing technologies in a real-world pharmaceutical manufacturing environment.

Key performance indicators (KPIs) included:

• Total makespan
• Number of late jobs
• Average tardiness
• Constraint violations (e.g., machine conflicts, priority clashes)

The Results

Both the classical and hybrid Quantum solutions outperformed Pfizer’s baseline scheduling system. However, the hybrid Quantum model delivered the strongest overall results:

- 66% reduction in makespan

- 33% fewer constraint violations

- No observed machine overlaps, priority conflicts, or deadline violations

- Marked reduction in late jobs and average tardiness

These results demonstrate the feasibility of using Quantum-enabled optimization to improve complex job shop scheduling under real-world manufacturing conditions.

"This collaboration with QuantumBasel and D-Wave has allowed us to explore the real potential of Quantum technologies in a high-stakes production environment. The results we’ve seen at our Freiburg site demonstrate that hybrid Quantum approaches can meaningfully enhance scheduling performance and support a more agile manufacturing process.” — Pembe Gül Bilir, Project Engineer Innovation, Pfizer Freiburg

Next Steps

Optimised schedules have the potential to transform the way Pfizer manages production planning. Faster, more flexible scheduling supports faster ramp-ups, adapts more easily to unforeseen events and changes in the production process and reduces the time required for manual adjustments. By improving resource efficiency, the new schedules could potentially increase overall output and provide significant potential to use machine downtime more effectively - for example, for preventive maintenance.

This may lead to cost savings through reduced energy consumption and improved capacity planning. Importantly, the hybrid Quantum approach is highly scalable and particularly well suited to larger data sets and more complex manufacturing scenarios. To gain further insights into the method’s global business impact, the next step would be to test it on larger datasets.

Following the success of the PoT, Pfizer plans to extend the study with:

• Larger and more complex datasets
• Additional production sites
• Deeper integration with existing enterprise systems

The long-term objective is to evaluate the global scalability of hybrid Quantum optimization within Pfizer’s broader manufacturing network.

"While there are many theoretical proofs of concept for Quantum annealing, real-world applications remain rare. This project with Pfizer is one of the latter, and a key example of how hybrid Quantum-classical methods are already delivering real business value in complex areas such as manufacturing planning.” — Dr. Julien Baglio, Quantum Algorithms Researcher, QuantumBasel

Additional Reading

For more insights into the collaborations of QuantumBasel and Pfizer, check out the Pfizer Healthcare Hub.

Or why not reach out to our team directly below and see how your organization can benefit from the power of Quantum?