Integrating automation and DOE to streamline and accelerate Quality by Design activities for process chemistry

Significance of the Topic

Quality by Design integration with automation and design of experiments is essential in pharmaceutical process development to reduce project risk, accelerate timelines and ensure robust manufacturing practices consistent with ICH Q8 Q9 Q10 guidelines.

Objectives and Study Overview

This application note demonstrates how Unchained Labs combines automated reaction screening platforms with a statistical design of experiments workflow to explore wide design spaces, gather high density kinetic data and streamline QbD activities. A case study on trans-cinnamic acid hydrogenation illustrates the approach.

Methodology and Used Instrumentation

Automation platforms Big Kahuna and Junior perform plate based reaction screening across compositional and parameter variables. The Optimization Sampling Reactor OSR uses eight independently controlled 16-25 mL vessels capable of temperature control from –20 to 200 C and pressure up to 400 psi. Library Studio within LEA software imports DOE tables in CSV or XLSX format, generates experiment scripts and exports results to users DOE tools. An example experiment hydrogenated trans-cinnamic acid with 5% Pd on carbon in 2-methyltetrahydrofuran at 40 C and 50 psi H2.

Main Results and Discussion

The hydrogenation reaction reached completion in 96 minutes with relative standard deviations below 5 percent across eight parallel reactors. Automated time-point sampling every 24 minutes yielded 48 data points in two hours while consuming 8 grams of substrate. In contrast, a traditional batch approach would have required 40 separate reactions, more than 40 grams of material and approximately six working days of manual work.

Benefits and Practical Applications

• Enlarged design spaces enabling comprehensive risk assessment without excessive material use
• Reduced experimental time and labor through unattended high throughput operation
• Improved data consistency and traceability by automated data management and DOE integration
• Regulatory flexibility as broader design spaces minimize need for post approval submissions

Future Trends and Applications

Ongoing developments may integrate real time analytical feedback, advanced process analytics technology PAT, machine learning driven experiment design and scale up strategies. Further automation of sample quenching, workup and inline analysis will support continuous manufacturing and real time control within a QbD framework.

Conclusion

By coupling high throughput automation with design of experiments software and DOE compatible data workflows, process development laboratories can implement Quality by Design effectively using existing resources, accelerate project timelines and build robust, regulatory compliant processes.