title: Investigation of active pharmaceutical ingredient loss in pharmaceutical compounding of capsules.
abstract: Pharmaceutical compounding of capsules is still an important corner stone in today's health care. It allows for a more patient specific treatment plan as opposed to the "one size fits all"-approach, used by the pharmaceutical industry when producing fixed dose finished drug products. However, loss of active pharmaceutical ingredient (API) powder during pharmaceutical capsule compounding can lead to under-dosed finished drug products and annul the beneficiary therapeutic effects for the patient. The amount and location of API loss was experimentally determined during capsule compounding of five different preparations: 10 and 20mg hydrocortisone capsules, 4mg triamcinolone capsules and 0.25mg dexamethasone capsules, using a 10% m/m self-made or commercial trituration. The total API amount present in the five capsule preparations varied between 90.8% and 96.6%, demonstrating that for certain preparations, significant API mass loss occurred during the pharmaceutical compounding of capsules. Swabbing results of the different compounding equipment and working areas indicated the mortar surface as the largest API loss location. An agate mortar accounted for the least amount of API loss, whereas an extensively used porcelain mortar accounted for the highest amount of API loss. Optical microscopy and roughness (Ra) determination by profilometry of the different mortar surfaces revealed a significant influence of the mortar surface wear and tear on the observed API loss. This observation can be explained by physical deformation, or scratch formation, of the relatively soft porcelain mortar surface, in which the API particles can become adsorbed. Furthermore, a small effect of the capsulation device material on the API loss was also observed. The presence of a chemical molecule effect on the API loss was demonstrated through data mining using a set of assay results containing 17 different molecules and 1922 assay values. The 17 median assay values were modeled in function of corresponding molecular descriptors, using stepwise multiple linear regression. The obtained MLR model, containing RDF060m, R6e(+) and R3m(+) variables, explained 92.5% of the observed variability between the 17 median assay values.
authors.affiliation: Drug Quality and Registration (DruQuaR) group, Faculty of Pharmaceutical Sciences, Ghent University, Harelbekestraat 72, B-9000 Ghent, Belgium.
authors.forename: Matthias
authors.initials: M
authors.lastname: D'Hondt
authors.affiliation: Drug Quality and Registration (DruQuaR) group, Faculty of Pharmaceutical Sciences, Ghent University, Harelbekestraat 72, B-9000 Ghent, Belgium.
authors.forename: Evelien
authors.initials: E
authors.lastname: Wynendaele
authors.affiliation: Drug Quality and Registration (DruQuaR) group, Faculty of Pharmaceutical Sciences, Ghent University, Harelbekestraat 72, B-9000 Ghent, Belgium.
authors.forename: Kirsten
authors.initials: K
authors.lastname: Vandercruyssen
authors.affiliation: Department of Pharmacy, Ghent University Hospital, De Pintelaan 185, B-9000 Ghent, Belgium.
authors.forename: Tiene
authors.initials: T
authors.lastname: Bauters
authors.affiliation: Department of Pharmacy, Ghent University Hospital, De Pintelaan 185, B-9000 Ghent, Belgium.
authors.forename: Johan
authors.initials: J
authors.lastname: Vandenbroucke
authors.affiliation: Flemish Institute for Technological Research (VITO), Boeretang 200, B-2400 Mol, Belgium.
authors.forename: Steven
authors.initials: S
authors.lastname: Mullens
authors.affiliation: Laboratory of Pharmaceutical Technology, Faculty of Pharmaceutical Sciences, Ghent University, Harelbekestraat 72, B-9000 Ghent, Belgium.
authors.forename: Chris
authors.initials: C
authors.lastname: Vervaet
authors.affiliation: Laboratory of Pharmaceutical Technology, Faculty of Pharmaceutical Sciences, Ghent University, Harelbekestraat 72, B-9000 Ghent, Belgium.
authors.forename: Jean Paul
authors.initials: JP
authors.lastname: Remon
authors.affiliation: Drug Quality and Registration (DruQuaR) group, Faculty of Pharmaceutical Sciences, Ghent University, Harelbekestraat 72, B-9000 Ghent, Belgium. Electronic address: Bart.DeSpiegeleer@UGent.be.
authors.forename: Bart
authors.initials: B
authors.lastname: De Spiegeleer
mesh_terms: D002214:Capsules; D057225:Data Mining; D003907:Dexamethasone / Q000737:chemistry*; D004339:Drug Compounding / Q000295:instrumentation / Q000379:methods*; D004867:Equipment Design; D006854:Hydrocortisone / Q000737:chemistry*; D016014:Linear Models; D008853:Microscopy / Q000379:methods; D011208:Powders; D014221:Triamcinolone / Q000737:chemistry*
chemical_list: D002214:Capsules; D011208:Powders; D014221:Triamcinolone; D003907:Dexamethasone; D006854:Hydrocortisone
keywords: API loss; Pharmaceutical capsule compounding; R-GETAWAY autocorrelation; Radial distribution function (RDF); Surface profilometry