Evidence map›Paper›PMID 42612205›Full record

ArticleJMIR research protocols2026

AI Applied to Formulation Design, Process Optimization, and Quality Control in 3D Printed Drug Products: Protocol for a Scoping Review.

Patricia Garcia Ferreira, Caroline Deckmann Nicoletti, Vitor Francisco Ferreira, Tácio de Mendonça Lima

Abstract read
In one paragraph

Article in JMIR research protocols, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Patricia Garcia Ferreira *Department of Pharmacy and Pharmaceutical Administration, Universidade Federal Fluminense, Niterói, Rio de Janeiro, Brazil.ORCID 0000-0003-0640-5079
Caroline Deckmann Nicoletti *Department of Pharmacy and Pharmaceutical Administration, Universidade Federal Fluminense, Niterói, Rio de Janeiro, Brazil.ORCID 0000-0003-4357-1092
Vitor Francisco Ferreira *Department of Pharmacy and Pharmaceutical Administration, Universidade Federal Fluminense, Niterói, Rio de Janeiro, Brazil.ORCID 0000-0002-2166-766X
Tácio de Mendonça Lima *Department of Pharmacy and Pharmaceutical Administration, Universidade Federal Fluminense, Niterói, Rio de Janeiro, Brazil.ORCID 0000-0003-4395-2098

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

background3D printing is an advanced, computer-aided design (CAD)-guided, layer-by-layer manufacturing technology with strong potential for producing patient-specific drug products. Integrating AI with pharmaceutical 3D printing can accelerate formulation development, improve process robustness and quality, and enable efficient personalization across the preprinting, printing, and postprinting stages. However, evidence remains dispersed across technologies, dosage forms, and AI approaches, making it difficult to obtain a comprehensive understanding of current research and knowledge gaps.

objectiveThis scoping review protocol aims to map and characterize how AI has been applied to the formulation design, process optimization, and quality control of 3D printed drug products across the preprinting, printing, and postprinting stages.

methodsThis review will follow the Joanna Briggs Institute (JBI) methodology and the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) checklist and guidelines for scoping reviews. The following databases and resources will be searched: MEDLINE (PubMed), Scopus, and Web of Science. Screening, data extraction, and data analysis will be conducted by 2 reviewers independently. Findings will be presented in summary tables and a narrative synthesis.

resultsThe protocol and search strategy were finalized in April 2026, and the review was registered on the Open Science Framework (OSF). Literature searches are scheduled to be conducted between May 2026 and June 2026, followed by title and abstract screening and full-text assessment between June 2026 and August 2026. Data extraction and narrative synthesis are expected to be completed by September 2026. The final scoping review is expected to be submitted for publication in the fourth quarter of 2026.

conclusionsThis protocol outlines a scoping review to map the use of AI in the formulation design, process optimization, and quality control of 3D printed drug products, and summarize current research and identify areas for future investigation.

trial registrationOpen Science Framework 10.17605/OSF.IO/2R8ED; https://osf.io/2r8ed/overview. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): PRR1-10.2196/98251.

Indexed as

Artificial IntelligenceChemistry, PharmaceuticalDrug CompoundingPrinting, Three-DimensionalComputer-Aided DesignHumansQuality ControlScoping Reviews as TopicTechnology, Pharmaceutical3D printingadditive manufacturingAIartificial intelligenceformulation designprocess optimization

Identifiers

PMID42612205
PMCPMC13535301

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.