ArticlePharmaceutics2021
Data-Enriched Edible Pharmaceuticals (DEEP) with Bespoke Design, Dose and Drug Release.
Article in Pharmaceutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed, 12 citations in OpenAlex.
- Ink to innovation: Pioneering printing technologies for next-generation drug delivery systems.Drug delivery and translational research · 2026Review
- Predicting pharmaceutical inkjet printing outcomes using machine learning.International journal of pharmaceutics: X · 2023Article
- Data-enriched edible pharmaceuticals (DEEPs): Patients' preferences, perceptions, and acceptability of new dosage forms and their digital aspects - An interview study.Exploratory research in clinical and social pharmacy · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 3 countries.
Funding
Abstract
Data-enriched edible pharmaceuticals (DEEP) is an approach to obtain personalized medicine, in terms of flexible and precise drug doses, while at the same time containing data, embedded in quick response (QR) codes at a single dosage unit level. The aim of this study was to fabricate DEEP with a patient-tailored dose, modify drug release and design to meet patients' preferences. It also aimed to investigate physical stability in terms of the readability of QR code patterns of DEEP during storage. Cannabinoids, namely, cannabidiol (CBD) and delta-9-tetrahydrocannabinol (THC), were used as the model active pharmaceutical ingredients (APIs). Three different substrates and two colorants for the ink were tested for their suitability to fabricate DEEP by desktop inkjet printing. Flexible doses and customizable designs of DEEP were obtained by manipulating the digital design of the QR code, particularly, by exploring different pattern types, embedded images and the physical size of the QR code pattern. Modification of the release of both APIs from DEEP was achieved by applying a hydroxypropyl cellulose (HPC) polymer coating. The appearance and readability of uncoated and polymer-coated DEEP did not change on storage in cold and dry conditions; however, the HPC polymer layer was insufficient in preserving the readability of the QR code pattern in the extreme storage condition (40 °C and 75% relative humidity). To sum up, the DEEP concept provides opportunities for the personalization of medicines, considering also patients' preferences.
Indexed as
Identifiers
What Socratic holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.