3D-printed prednisolone phosphate suppositories with tunable dose and rapid release for the treatment of inflammatory bowel disease.

Established medicines are often not tailored to the needs of the pediatric population, causing difficulties with administration or dosing. Three-dimensional (3D) printing technology allows novel approaches for compounding of personalized medicine, as is exemplified in this study for the automated compounding of rectal preparations for children. We investigated the material requirements to print prednisolone phosphate-loaded suppositories with tunable dose and rapid drug release for the treatment of inflammatory bowel diseases. Three formulations containing 4 % w/w prednisolone sodium phosphate (PSP) and different amounts of hydroxypropyl cellulose (HPC) and mannitol as excipients were printed as suppositories with a fused deposition modeling (FDM) 3D-printer. Dissolution studies showed that the PSP release rate was increased when higher weight fractions of mannitol were added as a pore former, with 90 % drug release within 30 min for mannitol 48 % w/w. We further printed suppositories with 48 % mannitol with different infill densities and dimensions to tune the dose. Our findings demonstrated that 3D-printed suppositories with PSP doses ranging from 6 to 30 mg could be compounded without notably affecting the dissolution kinetics, ensuring equivalent therapeutic efficacies for different doses.

3D printed, personalized sustained release cortisol for patients with adrenal insufficiency.

The standard of care for patients with Adrenal Insufficiency (AI) is suboptimal. Administration of hydrocortisone three times a day produces plasma cortisol fluctuations associated with negative health outcomes. Furthermore, there is a high inter-individual variability in cortisol need, necessitating a personalized approach. It is hypothesized that a personalized, sustained release formulation would enhance the pharmacotherapy by mimicking the physiological cortisol plasma concentration at a higher level. Therefore, a novel 24 h sustained release 3D printed (3DP) hydrocortisone formulation has been developed (M3DICORT) by coupling hot-melt extrusion with fused deposition modeling. A uniform drug distribution in the 3DP tablets is demonstrated by a content of 101.66 ± 1.60 % with an acceptance value of 4.01. Furthermore, tablets had a stable 24 h dissolution profile where the intra-batch standard deviation was ± 2.8 % and the inter-batch standard deviation was ± 6.8 %. Tablet height and hydrocortisone content were correlated (R2 = 0.996), providing a tool for easy dose personalization. Tablets maintained critical quality attributes, such as dissolution profile (f2 > 60) and content uniformity after process transfer from a single-screw extruder to a twin-screw extruder. Impurities were observed in the final product which should be mitigated before clinical assessment. To our knowledge, M3DICORT is the first 3DP hydrocortisone formulation specifically developed for AI.

Identification of Dutch children diagnosed with atopic diseases using prescription data: a validation study.

PURPOSE: The aim of this study is to validate medication proxies for the identification of children diagnosed with atopic disorders that can be applied in various types of epidemiological research. METHODS: Records of 7439 children, aged between 0 and 10 years, in the period 2001 until 2010, were retrieved from the Registration Network Groningen database, a general practitioners database in the north-eastern part of the Netherlands. The sensitivity and positive predictive value (PPV) of 22 medication proxies for the identification of children diagnosed with atopic disorders (asthma, atopic dermatitis, and allergic rhinitis) were computed using the registered diagnoses as gold standards. In addition, different capture periods (1 year, half year, and length of study period) for the detection of prescriptions were tested for all the medication proxies. RESULTS: The highest PPV (0.84, 95 % CI 0.81-0.87) in combination with a sufficient sensitivity value (0.54, 95 % CI 0.50-0.57) for the identification of children diagnosed with asthma was yielded for the medication proxy, ≥2 prescriptions for anti-asthma medication within 1 year, including 1 inhaled steroid. PPV and sensitivity were even higher in the age group 6-10 years. The proxies designed for the identification of children diagnosed with atopic dermatitis and allergic rhinitis yielded only high PPVs (≥0.75) in combination with low sensitivity values (≤0.22). Altering the capture period for the detection of prescriptions to half a year or the length of the study period only affected sensitivity values. CONCLUSION: Children diagnosed with asthma can be identified reliably with a range of medication proxies. The use of prescription data for the identification of children diagnosed with atopic dermatitis and allergic rhinitis is questionable.