Votli nosilci kot nov pristop za vgrajevanje učinkovin v razvoju formulacij s 3D tiskanjem talin

Potreba po posamezniku prilagojenem odmerjanju zdravila je dobro zavedana pri sodobnem razvoju in uporabi zdravil. 3D-tiskanje je izpostavljeno kot potencialna strategija za revolucijo na področju personalizirane medicine ter izboljšanje njene prilagodljivosti, učinkovitosti, varnosti in uporabnosti. Namen študije je bil optimizirati nov in poenostavljen pristop k tehnologiji 3D tiskanja s ciljnim nalaganjem, z uporabo votlih nosilcev (HF). S pomočjo računalniško podprtega načrtovanja je bil zasnovan 3D model HF, ki je omogočal enostavnejše in mnogo hitrejše polnjenje učinkovine ter, zaradi večjega votlega volumna, tudi višje masne koncentracije v primerjavi z referenčnim modelom. HF, izdelani iz komercialno dostopnih filamentov polimlečne kisline ali hidroksipropilmetil celuloze, so bili napolnjeni z dvema različnima učinkovinama (naproksenom ali indometacinom) in vstavljeni v 3D-tiskalnik. Za uspešno tiskanje z napolnjenimi HF, je bila potrebna prilagoditev hitrosti tiskanja, temperature tiskanja in vrste adhezije na odlagalni mizici 3D tiskalnika. Razlike v parametrih niso bile opazne le pri različnih polimerih, temveč tudi med posameznim polimerom v kombinaciji z različnimi učinkovinami, kar je kazalo na vpliv medsebojnih interakcij komponent na rezultate tiskanja. Primerjave enakomernosti mas in vsebnosti učinkovin med tabletami enakih HF so pokazale, da so kombinacije polimera in učinkovine, s tiskanjem katerih je bilo možno doseči želeno obliko tablet, imele tudi manjšo variacijo mas in bolj enakomerno porazdelitev učinkovine med tabletami. Ugotovljeno je bilo, da je dobro mešanje polimera ključnega pomena za uspeh 3D tiskanja. Napovedi mešanja med različnimi kombinacijami polimerov in učinkovin, pridobljene na podlagi rezultatov 3D tiskanja, so bile ovrednotene z uporabo Hansenovih parametrov topnosti (HSP), metode depresije temperature taljenja (MPD) in nove metode z uporabo entalpije taljenja in mešanja (Hmm). Zaradi fizikalno-kemijskih lastnosti učinkovin in polimerov, ki so vplivale na rezultate analize s Hmm in MPD, je bilo ugotovljeno, da so HSP najbolj koristno orodje za napovedovanje mešanja in razlago rezultatov za te specifične kombinacije učinkovin in polimerov. The need for patient-tailored drug dosage development has been well recognized in current medication development and usage. 3D printing is highlighted as a potential strategy to revolutionize the personalized medicine field and improve its flexibility, efficiency, safety, and utility. This study aimed to optimize a new and simplified approach to the Fused Deposition Modeling 3D printing technique using hollow filaments (HFs). Computer-aided design of the HF was successfully developed, allowing faster drug loading and, due to the higher filling capacity, higher mass concentrations of the drug compared to the reference model. HFs, printed from commercially available Polylactic acid and Hydroxypropyl Methylcellulose filaments, respectively, were filled with two different drugs (Naproxen or Indomethacin) and fed into the 3D printer. Printing speed, printing temperature, and the adhesion type on the build plate had to be adjusted to successfully achieve the printability of drug-loaded HFs. Not only was the difference in parameters noticeable for different polymers, but also within each polymer with different drugs, indicating the specific drug-polymer interplay had a significant impact on printing outcomes. The mass and dose homogeneity studies between tablets of the same HF showed, that the combinations of the drug and polymer, showing the best miscibility with lower dose variation, in general, had better reproducibility and printability of tablets. The finding suggested that the drug's and polymer's miscibility is crucial in 3D printing success. Predictions of miscibility between different drug-polymer systems, obtained from 3D printing results, were evaluated using Hansen Solubility Parameters (HSPs) method, The Melting Point Depression (MPD) method, and the novel method utilizing The Enthalpy of Melting and Mixing (Hmm). Due to the physicochemical properties of drug-polymer systems that might have affected the analysis outcome of Hmm and MPD, HSPs were found to be the most helpful tool to predict miscibility and explain results acquired from the conducted experiments for these specific drug-polymer systems.