Revolutionary Particle Size Distribution Method Enhances Pharmaceutical Manufacturing Efficiency

The pharmaceutical manufacturing sector has faced ongoing challenges in monitoring the properties of drying mixtures, a crucial phase in the production of medications and chemical compounds. Traditionally, two non-invasive characterization methods have been employed: one involves imaging samples and counting individual particles, while the other estimates particle size distribution (PSD) through scattered light analysis. While the former is time-consuming and can lead to increased waste, the latter method presents a more efficient alternative.

A Breakthrough in Scattered Light Analysis

Recent advancements by engineers and researchers from MIT have led to a new physics and machine learning-based approach to scattered light analysis. This innovative technique significantly enhances manufacturing processes for pharmaceutical pills and powders, boosting both efficiency and accuracy while reducing the incidence of production failures. A newly published open-access paper, titled “Non-invasive estimation of the powder size distribution from a single speckle image,” featured in the journal Light: Science & Applications, elaborates on this groundbreaking work by introducing an even swifter methodology.

Insights from Leading Researchers

As Qihang Zhang, PhD ’23, an associate researcher at Tsinghua University, notes, “Understanding how scattered light behaves is critical in optics. Our advancements in analyzing this phenomenon have led to the development of a valuable tool for the pharmaceutical industry. Identifying and addressing key challenges through fundamental research is what excites our team most.”

The paper introduces a novel PSD estimation technique that utilizes pupil engineering, which minimizes the number of frames required for analysis. According to the researchers, “Our machine learning-based model can derive powder size distribution from just a single speckle image, drastically reducing reconstruction time from 15 seconds to only 0.25 seconds.”

“Our primary contribution is enhancing the particle size detection speed by 60 times through a comprehensive optimization of both algorithms and hardware,” Zhang explains.

“This high-speed probe can track size variations in fast-moving dynamic systems, paving the way for studying various processes within the pharmaceutical industry, including drying, mixing, and blending.”

Cost-effective Non-invasive Measurement Solution

This method presents a cost-effective, non-invasive solution for measuring particle size by collecting back-scattered light from powder surfaces. The compact and portable prototype is designed to be compatible with most drying systems available on the market, provided there is an observation window. This online measurement strategy could significantly improve manufacturing process control, leading to enhanced efficiency and product quality.

Additionally, the previous absence of online monitoring hindered systematic studies of dynamic models in manufacturing processes. This probe may serve as a new platform for conducting extensive research and modeling on particle size evolution.

Collaborative Innovation at MIT-Takeda

This innovative work results from a successful collaboration between physicists and engineers under the MIT-Takeda program. The research team consists of members from three MIT departments: Mechanical Engineering, Chemical Engineering, and Electrical Engineering and Computer Science. The senior author of the article is George Barbastathis, a professor of mechanical engineering at MIT.