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Material Properties and Compressibility Using Heckel and Kawakita Equation with Commonly Used Pharmaceutical Excipients

By Choi, Du-Hyung; Kim, Nam-Ah Chu, Kyung-Rok Jung, Youn-Jung; Yoon, Jeong-Hyun; Jeong, Seong-Hoon

Published on

Abstract

This study investigated basic material properties and compressibility of commonly used pharmaceutical excipients. Five classes of excipients are selected including starch, lactose, calcium phosphate, microcrystalline cellulose (MCC), and povidone. The compressibility was evaluated using compression parameters derived from Heckel and Kawakita equation. The Heckel plot for lactose and dicalcium phosphate showed almost linear relationship. However, for MCC and povidone, curves in the initial phase of compression were observed followed by linear regions. The initial curve was considered as particle rearrangement and fragmentation and then plastic deformation at the later stages of the compression cycle. The Kawakita equation showed MCC exhibited higher compressibility, followed by povidone, lactose, and calcium phosphate. MCC undergoes significant plastic deformation during compression bringing an extremely large surface area into close contact and facilitating hydrogen bond formation between the plastically deformed, adjacent cellulose particles. Lactose compacts are consolidated by both plastic deformation and fragmentation, but to a larger extent by fragmentation. Calcium phosphate has poor binding properties because of its brittle nature. When formulating tablets, selection of suitable pharmaceutical excipients is very important and they need to have good compression properties with decent powder flowability. Material properties tested in this study might give a good guide how to select excipients for tablet formulations and help the formulation scientists design the optimum ones.

Journal

Journal of Pharmaceutical Investigation. Volume 40,, 2010, 237-244

DOI

10.4333/kps.2010.40.4.237

Type of publication

Peer-reviewed journal

Affiliations

  • Dongguk University

Article Classification

Research Article

Classification Areas

  • Modeling

Tags