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A data mining approach to optimize pellets manufacturing process based on a decision tree algorithm.

Joanna Ronowicz1, Markus Thommes2, Peter Kleinebudde3

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This study identified key factors influencing pellet shape, crucial for pharmaceutical product quality. Optimal pellet sphericity is achieved through specific extrusion/spheronization parameters, improving flow characteristics.

Keywords:
Aspect ratioData miningDecision treesPellets

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Area of Science:

  • Pharmaceutical Technology
  • Chemical Engineering
  • Data Science

Background:

  • Pellet quality attributes, such as shape, significantly impact final product performance and manufacturability.
  • Understanding the complex interplay between formulation, process parameters, and pellet quality is essential for pharmaceutical development.

Purpose of the Study:

  • To analyze cause-effect relationships between pellet formulation/process variables and pellet shape (aspect ratio).
  • To identify critical parameters influencing pellet sphericity using a data-driven approach.

Main Methods:

  • Chemometric analysis of a data matrix comprising 224 pellet formulations with eight active pharmaceutical ingredients.
  • Application of a tree regression algorithm, aligned with Quality by Design (QbD) principles.
  • Identification of 14 input variables (formulation and process) and one output variable (pellet aspect ratio).

Main Results:

  • Spheronization speed, spheronization time, number of holes in the extruder, and extrudate water content were identified as key factors affecting pellet aspect ratio.
  • Optimal conditions for achieving highly spherical pellets include a high number of holes, high spheronizer speed, and extended spheronization time.
  • Decision rules were generated to interpret the influence of these parameters on pellet sphericity.

Conclusions:

  • The data mining approach provides valuable insights into the pelletization process, supporting the identification of optimal conditions for producing spherical pellets.
  • This methodology aids industrial scientists in rational decision-making for enhanced pellet technology and improved product flow characteristics.