Evaluación de algunas aproximaciones tecnológicas para incrementar la velocidad de disolución de fármaco en pelets de celulosa microcristalina

La celulosa microcristalina (MCC) es el excipiente base más utilizado para la elaboración de pelets por extrusión-esferonización. Las características de plasticidad y de adhesividad de sus masas humectadas le confieren unas propiedades únicas para esta finalidad (Fielden y col., 1992; Shah y col., 1995). Sin embargo, los pelets que contienen celulosa microcristalina no experimentan un proceso de disgregación en medio acuoso y, como consecuencia de ello, exhiben una lenta velocidad de cesión de principio activo, en especial si su hidrosolubilidad es reducida (Pinto y col., 1992)

3D Printed Tablets (Printlets) with Braille and Moon Patterns for Visually Impaired Patients

Visual impairment and blindness affects 285 million people worldwide, resulting in a high public health burden. This study reports, for the first time, the use of three-dimensional (3D) printing to create orally disintegrating printlets (ODPs) suited for patients with visual impairment. Printlets were designed with Braille and Moon patterns on their surface, enabling patients to identify medications when taken out of their original packaging. Printlets with different shapes were fabricated to offer additional information, such as the medication indication or its dosing regimen. Despite the presence of the patterns, the printlets retained their original mechanical properties and dissolution characteristics, wherein all the printlets disintegrated within ~5 s, avoiding the need for water and facilitating self-administration of medications. Moreover, the readability of the printlets was verified by a blind person. Overall, this novel and practical approach should reduce medication errors and improve medication adherence in patients with visual impairmentThe authors thank the Engineering and Physical Sciences Research Council (EPSRC), UK, for their financial support (EP/L01646X)S

3D printed pellets (miniprintlets): A novel, multi-drug, controlled release platform technology

[ENG]Selective laser sintering (SLS) is a single-step three-dimensional printing (3DP) process that can be leveraged to engineer a wide array of drug delivery systems. The aim of this work was to utilise SLS 3DP, for the first time, to produce small oral dosage forms with modified release properties. As such, paracetamol-loaded 3D printed multiparticulates, termed miniprintlets, were fabricated in 1 mm and 2 mm diameters. Despite their large surface area compared with a conventional monolithic tablet, the ethyl cellulose-based miniprintlets exhibited prolonged drug release patterns. The possibility of producing miniprintlets combining two drugs, namely paracetamol and ibuprofen, was also investigated. By varying the polymer, the dual miniprintlets were programmed to achieve customised drug release patterns, whereby one drug was released immediately from a Kollicoat Instant Release matrix, whilst the effect of the second drug was sustained over an extended time span using ethyl cellulose. Herein, this work has highlighted the versatility of SLS 3DP to fabricate small and intricate formulations containing multiple active pharmaceutical ingredients with distinct release propertiesS

Gastrointestinal Tracking and Gastric Emptying of Coated Capsules in Rats with or without Sedation Using CT imaging

Following oral administration, gastric emptying is often a rate-limiting step in the absorption of drugs and is dependent on both physiological and pharmaceutical factors. To guide translation into humans, small animal imaging during pre-clinical studies has been increasingly used to localise the gastrointestinal transit of solid dosage forms. In contrast to humans, however, anaesthesia is usually required for effective imaging in animals which may have unintended effects on intestinal physiology. This study evaluated the effect of anaesthesia and capsule size on the gastric emptying rate of coated capsules in rats. Computed tomography (CT) imaging was used to track and locate the capsules through the gastrointestinal tract. Two commercial gelatine mini-capsules (size 9 and 9h) were filled with barium sulphate (contrast agent) and coated using Eudragit L. Under the effect of anaesthesia, none of the capsules emptied from the stomach. In non-anaesthetised rats, most of the size 9 capsules did not empty from the stomach, whereas the majority of the smaller size 9h capsules successfully emptied from the stomach and moved into the intestine. This study demonstrates that even with capsules designed to empty from the stomach in rats, the gastric emptying of such solid oral dosage forms is not guaranteed. In addition, the use of anaesthesia was found to abolish gastric emptying of both capsule sizes. The work herein further highlights the utility of CT imaging for the effective visualisation and location of solid dosage forms in the intestinal tract of rats without the use of anaesthesia.This research was funded by the Engineering and Physical Sciences Research Council (EPSRC) UK, grant number EP/L01646XS

Accelerating 3D printing of pharmaceutical products using machine learning

[Abstract] Three-dimensional printing (3DP) has seen growing interest within the healthcare industry for its ability to fabricate personalized medicines and medical devices. However, it may be burdened by the lengthy empirical process of formulation development. Active research in pharmaceutical 3DP has led to a wealth of data that machine learning could utilize to provide predictions of formulation outcomes. A balanced dataset is critical for optimal predictive performance of machine learning (ML) models, but data available from published literature often only include positive results. In this study, in-house and literature-mined data on hot melt extrusion (HME) and fused deposition modeling (FDM) 3DP formulations were combined to give a more balanced dataset of 1594 formulations. The optimized ML models predicted the printability and filament mechanical characteristics with an accuracy of 84%, and predicted HME and FDM processing temperatures with a mean absolute error of 5.5 °C and 8.4 °C, respectively. The performance of these ML models was better than previous iterations with a smaller and a more imbalanced dataset, highlighting the importance of providing a structured and heterogeneous dataset for optimal ML performance. The optimized models were integrated in an updated web-application, M3DISEEN, that provides predictions on filament characteristics, printability, HME and FDM processing temperatures, and drug release profiles (https://m3diseen.com/predictionsFDM/). By simulating the workflow of preparing FDM-printed pharmaceutical products, the web-application expedites the otherwise empirical process of formulation development, facilitating higher pharmaceutical 3DP research throughput

Predicting pharmaceutical inkjet printing outcomes using machine learning

[Abstract]: Inkjet printing has been extensively explored in recent years to produce personalised medicines due to its low cost and versatility. Pharmaceutical applications have ranged from orodispersible films to complex polydrug implants. However, the multi-factorial nature of the inkjet printing process makes formulation (e.g., composition, surface tension, and viscosity) and printing parameter optimization (e.g., nozzle diameter, peak voltage, and drop spacing) an empirical and time-consuming endeavour. Instead, given the wealth of publicly available data on pharmaceutical inkjet printing, there is potential for a predictive model for inkjet printing outcomes to be developed. In this study, machine learning (ML) models (random forest, multilayer perceptron, and support vector machine) to predict printability and drug dose were developed using a dataset of 687 formulations, consolidated from in-house and literature-mined data on inkjet-printed formulations. The optimized ML models predicted the printability of formulations with an accuracy of 97.22%, and predicted the quality of the prints with an accuracy of 97.14%. This study demonstrates that ML models can feasibly provide predictive insights to inkjet printing outcomes prior to formulation preparation, affording resource- and time-savings.The research was partially supported by MCIN (PID 2020-113881RB-I00/AEI/10.13039/501100011033), Spain, Xunta de Galicia (ED431C 2020/17), and FEDER.L.R.P. acknowledges the predoctoral fellowship provided by the Ministerio de Universidades (Formación de Profesorado Universitario (FPU 2020). I.S.V. acknowledges Consellería de Cultura, Educación e Universidade for her Postdoctoral Fellowship (Xunta de Galicia, Spain; ED481B-2021-019). L.R.P. acknowledges the predoctoral fellowship provided by the Ministerio de Universidades (Formación de Profesorado Universitario (FPU 2020) .Xunta de Galicia; ED431C 2020/17Xunta de Galicia; ED481B-2021-01

Selective Laser Sintering 3D Printing of Orally Disintegrating Printlets Containing Ondansetron

The aim of this work was to explore the feasibility of using selective laser sintering (SLS) 3D printing (3DP) to fabricate orodispersable printlets (ODPs) containing ondansetron. Ondansetron was first incorporated into drug-cyclodextrin complexes and then combined with the filler mannitol. Two 3D printed formulations with different levels of mannitol were prepared and tested, and a commercial ondansetron orally disintegrating tablet (ODT) product (Vonau® Flash) was also investigated for comparison. Both 3D printed formulations disintegrated at ~15 s and released more than 90% of the drug within 5 min independent of the mannitol content; these results were comparable to those obtained with the commercial product. This work demonstrates the potential of SLS 3DP to fabricate orodispersible printlets with characteristics similar to a commercial ODT, but with the added benefit of using a manufacturing technology able to prepare medicines individualized to the patient.S

3D Printed Tacrolimus Rectal Formulations Ameliorate Colitis in an Experimental Animal Model of Inflammatory Bowel Disease

The aim of this study was to fabricate novel self-supporting tacrolimus suppositories using semisolid extrusion 3-dimensional printing (3DP) and to investigate their efficacy in an experimental model of inflammatory bowel disease. Blends of Gelucire 44/14 and coconut oil were employed as lipid excipients to obtain suppository formulations with self-emulsifying properties, which were then tested in a TNBS (2,4,6-trinitrobenzenesulfonic acid) induced rat colitis model. Disease activity was monitored using PET/CT medical imaging; maximum standardized uptake values (SUVmax), a measure of tissue radiotracer accumulation rate, together with body weight changes and histological assessments, were used as inflammatory indices to monitor treatment efficacy. Following tacrolimus treatment, a significant reduction in SUVmax was observed on days 7 and 10 in the rat colon sections compared to non-treated animals. Histological analysis using Nancy index confirmed disease remission. Moreover, statistical analysis showed a positive correlation (R2 = 71.48%) between SUVmax values and weight changes over time. Overall, this study demonstrates the effectiveness of 3D printed tacrolimus suppositories to ameliorate colitis and highlights the utility of non-invasive PET/CT imaging to evaluate new therapies in the preclinical areaThis research was funded by Xunta de Galicia grant number GRC2013/015 and GPC2017/015. A.F.-F. acknowledges the support of Instituto de Salud Carlos III (Juan Rodés research grant JR18/00014). P.A. acknowledges the support of RYC-2015/17430 (Ramón y Cajal). X.G.-O. acknowledges the financial support of the IDIS (Health Research Institute of Santiago de Compostela)S

Quorum sensing network in clinical strains of A. baumannii : AidA is a new quorum quenching enzyme

Acinetobacter baumannii is an important pathogen that causes nosocomial infections generally associated with high mortality and morbidity in Intensive Care Units (ICUs). Currently, little is known about the Quorum Sensing (QS)/Quorum Quenching (QQ) systems of this pathogen. We analyzed these mechanisms in seven clinical isolates of A. baumannii. Microarray analysis of one of these clinical isolates, Ab1 (A. baumannii ST-2-clon-2010), previously cultured in the presence of 3-oxo-C12-HSL (a QS signalling molecule) revealed a putative QQ enzyme (α/β hydrolase gene, AidA). This QQ enzyme was present in all nonmotile clinical isolates (67% of which were isolated from the respiratory tract) cultured in nutrient depleted LB medium. Interestingly, this gene was not located in the genome of the only motile clinical strain growing in this medium (A. baumannii strain Ab421-GEIH-2010 [Ab7], isolated from a blood sample). The AidA protein expressed in E. coli showed QQ activity. Finally, we observed downregulation of the AidA protein (QQ system attenuation) in the presence of HO (ROS stress). In conclusion, most of the A. baumannii clinical strains were not surface motile (84%) and were of respiratory origin (67%). Only the pilT gene was involved in surface motility and related to the QS system. Finally, a new QQ enzyme (α/β hydrolase gene, AidA protein) was detected in these strains