Facile radiolabeling optimization process via design of experiments and an intelligent optimization algorithm:...

Area of Science:

• Nuclear medicine
• Radiopharmaceutical chemistry
• Process optimization

Background:

• Radiopharmaceuticals are crucial for medical diagnosis and therapy.
• Optimizing radiopharmaceutical production is essential for clinical applications.

Purpose of the Study:

• To optimize the radiolabeling process for omeprazole using a hybrid design.
• To develop a radiotracer for stomach imaging using iodine-125 labeled omeprazole.

Main Methods:

• Fractional Factorial Design Analysis (FFDA) was employed to study factors affecting radiolabeling.
• Particle Swarm Optimization (PSO) algorithm was used to further refine the process parameters.
• Omeprazole was radiolabeled with iodine-125 (125I).

Main Results:

• FFDA identified optimal conditions yielding an 88.4% radiolabeling yield (RY) for 125I-omeprazole.
• PSO further improved the RY to 93.78%.
• Practical verification confirmed a high RY of 93.99%.

Conclusions:

• The combined FFDA and PSO approach effectively optimizes radiopharmaceutical production.
• This method holds potential for enhancing the yield of radiolabeled compounds like 125I-omeprazole for diagnostic imaging.