METHODS: The PubMed database and Google scholar were browsed by keywords of 3-D printing, drug delivery, and personalised medicine. The data about techniques employed in the manufacturing of 3-D printed medicines and the application of 3-D printing technology in the fabrication of individualised medicine were collected, analysed and discussed.
RESULTS: Numerous techniques can fabricate 3-D printed medicines however, printing-based inkjet, nozzle-based deposition and laser-based writing systems are the most popular 3-D printing methods which have been employed successfully in the development of tablets, polypills, implants, solutions, nanoparticles, targeted and topical dug delivery. In addition, the approval of Spritam® containing levetiracetam by FDA as the primary 3-D printed drug product has boosted its importance. However, some drawbacks such as suitability of manufacturing techniques and the available excipients for 3-D printing need to be addressed to ensure simple, feasible, reliable and reproducible 3-D printed fabrication.
CONCLUSION: 3-D printing is a revolutionary in pharmaceutical technology to cater the present and future needs of individualised medicines. Nonetheless, more investigations are required on its manufacturing aspects in terms cost effectiveness, reproducibility and bio-equivalence.
DESIGN: A digitally derived 3-dimensional maxillary model incorporating the palatal defect was generated from the patient's existing cone beam computerized tomography data and compared with the scanned cast from the conventional impression for linear dimensions, area, and volume. The digitally derived cast was 3-dimensionally printed and the obturator fabricated using traditional techniques. Similarly, an obturator was fabricated from the conventional cast and the fit of both final obturator bulbs were compared in vivo.
RESULTS: The digitally derived model produced more accurate volumes and surface areas within the defect. The defect margins and peripheries were overestimated which was reflected clinically.
CONCLUSION: The digitally derived model provided advantages in the fabrication of the palatal obturator; however, further clinical research is required to refine consistency.
METHODS: The Z Printer 450 (3D Systems, Rock Hill, SC) reprinted 10 sets of models for each category of crowding (mild, moderate, and severe) scanned using a structured-light scanner (Maestro 3D, AGE Solutions, Pisa, Italy). Stone and RP models were measured using digital calipers for tooth sizes in the mesiodistal, buccolingual, and crown height planes and for arch dimension measurements. Bland-Altman and paired t test analyses were used to assess agreement and accuracy. Clinical significance was set at ±0.50 mm.
RESULTS: Bland-Altman analysis showed the mean bias of measurements between the models to be within ±0.15 mm (SD, ±0.40 mm), but the 95% limits of agreement exceeded the cutoff point of ±0.50 mm (lower range, -0.81 to -0.41 mm; upper range, 0.34 to 0.76 mm). Paired t tests showed statistically significant differences for all planes in all categories of crowding except for crown height in the moderate crowding group and arch dimensions in the mild and moderate crowding groups.
CONCLUSIONS: The rapid prototyping models were not clinically comparable with conventional stone models regardless of the degree of crowding.
METHODS: Two 3D printed models were designed and fabricated using actual patient imaging data with reference marker points embedded artificially within these models that were then registered to a surgical navigation system using 3 different methods. The first method uses a conventional manual registration, using the actual patient's imaging data. The second method is done by directly scanning the created model using intraoperative computed tomography followed by registering the model to a new imaging dataset manually. The third is similar to the second method of scanning the model but eventually uses an automatic registration technique. The errors for each experiment were then calculated based on the distance of the surgical navigation probe from the respective positions of the embedded marker points.
RESULTS: Errors were found in the preparation and printing techniques, largely depending on the orientation of the printed segment and postprocessing, but these were relatively small. Larger errors were noted based on a couple of variables: if the models were registered using the original patient imaging data as opposed to using the imaging data from directly scanning the model (1.28 mm vs. 1.082 mm), and the accuracy was best using the automated registration techniques (0.74 mm).
CONCLUSION: Spatial accuracy errors occur consistently in every 3D fabricated model. These errors are derived from the fabrication process, the image registration process, and the surgical process of registration.