Predicting Drug Release from 3D Printed Oral Medicines Based on the Surface Area to Volume Ratio of Tablet Geometry

3D printing offers the advantage of being able to modify dosage form geometry, which can be exploited to modify release characteristics. In this study, we investigated the influence of the surface area to volume ratio (SA/V) to change and predict release profiles of 3D printed dosage forms. Geometries with varying SA/V and dosages were designed and printed, and drug dissolution was investigated.

Three drug substances were used: pramipexole, levodopa (both BCS I) and praziquantel (BCS II). Two polymers were chosen as matrix formers: polyvinyl alcohol (water-soluble) and ethylene vinyl acetate (inert). Drug release was characterized using the mean dissolution time (MDT) and established equations that describe complete dissolution curves were applied. Predictions were validated with previously un-printed dosage forms. Based on an identified MDT-SA/V correlation, the MDT can be predicted with a deviation of ≤5 min for a given SA/V.

Using correlations of fit parameters and SA/V, RMSEP values of 0.6–2.8% and 1.6–3.4% were obtained for the BCS I formulations and RMSEP values of 1.0–3.8% were obtained for the BCS II formulation, indicating accurate prediction over a wide range of dissolution profiles. With this approach, MDT and release profiles of dosage forms with a given SA/V can be precisely predicted without performing dissolution tests and vice versa, the required SA/V can be predicted for a desired release profile.

Download the full article as a PDF here or read it here

Materials:

Formulation 1, referred to as the PVA-PDM formulation, consisted of 5% (w/w) pramipexole dihydrochloride monohydrate (PDM, Chr. Olesen, Denmark) as an API of the biopharmaceutics classification system (BCS) class I, declared as good water solubility (c_s ≥ 200 mg/mL) [49,50]. Mannitol (Parteck M^®, Merck, Germany) was used as a plasticizer at 10% (w/w) content. Polyvinyl alcohol (84%, PVA, Parteck MXP^®, Merck, Germany) was selected as a polymer. Formulation 2, referred to as the EVA-LD formulation, consisted of 10% (w/w) levodopa (Zhejiang Wild Wind Pharmaceutical, Dongyang, China), and was also a BCS class I API (c_s ≥ 12 mg/mL) [51]. As water soluble component, a vinylpyrrolidone-vinyl acetate copolymer (VP-VA) was used (39.5%, Kollidon VA 64^®, BASF, Ludwigshafen, Germany) and 10% mannitol was added as a plasticizer. The matrix consisted of ethylene vinyl acetate (EVA) with a content of 18% vinyl acetate (39.5%, Escorene^® FL 01418, TER Chemicals, Hamburg, Germany). To improve flowability, 1% fumed silica (Aerosil^® 200 VV Pharma, Evonik, Germany) was added to both formulations. Formulation 3, referred to as the PVA-PZQ formulation, consisted of 5% (w/w) praziquantel (PZQ, donated from Bayer AG, Leverkusen, Germany) as an API of BCS class II (c_s = 0.4 mg/mL) [52,53,54], declared as poorly water-soluble. As a polymer basis, PVA was chosen with 95% content. All filament formulations were systematically developed to minimize diameter fluctuations of the filaments and to ensure highest printability with the available equipment. The criteria for the drug selection were heat stability and different classifications in the BCS. The melting point of PDM is also the decomposition point at 296–305 °C [20,55,56,57]. LD melts and decomposes at 260–330 °C [58]. PZQ has its melting point already at 140–143 °C but decomposes only at temperatures >400 °C [59,60]. The investigated dose ranges do not correspond to therapeutic dosages and result from the drug loading of the filament and the volume of the objects. The polymer matrix of the first formulation should be water soluble and generate prolonged drug release. PVA fulfils both criteria as the polymer forms a water-soluble hydrocolloid matrix [61]. To test the transferability of the predictive model to other formulations, an inert, non-swelling matrix, EVA, was chosen [62]. To improve the printability and hydrophilicity of the filament, VP-VA was added. PVA was again chosen for transferring the model to the BCS class II drug, for the extended drug release as well as better printability. Thus, variations resulting from the process could be eliminated and the differences clearly attributed to the API.

Article information: Windolf, H.; Chamberlain, R.; Quodbach, J. Predicting Drug Release from 3D Printed Oral Medicines Based on the Surface Area to Volume Ratio of Tablet Geometry. Pharmaceutics 2021, 13, 1453. https://doi.org/10.3390/pharmaceutics13091453

Find out more about 3d printing in our 3d printing special here: