ArticleDrug delivery and translational research2023
Machine learning in accelerating microsphere formulation development.
Article in Drug delivery and translational research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
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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.
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Who cites it
11 citing papers in PubMed.
- Computational insights into drug hygroscopicity by coupling machine learning and molecular simulation.Drug delivery and translational research · 2026Article
- Engineering smart polymeric lipid nanoparticles for breast cancer: AI-guided formulation design, biological barriers, and translational constraints.Journal of nanobiotechnology · 2026Review
- Predicting early and complete drug release from long-acting injectables using explainable machine learning.International journal of pharmaceutics · 2026Article
- Artificial intelligence for drug delivery: Yesterday, today and tomorrow.Acta pharmaceutica Sinica. B · 2026Review
- Predicting Early and Complete Drug Release from Long-Acting Injectables Using Explainable Machine Learning.ArXiv · 2026Article
- Machine Learning Predicts Drug Release Profiles and Kinetic Parameters Based on Tablets' Formulations.The AAPS journal · 2025Article
- PLGA-based long-acting injectable (LAI) formulations.Journal of controlled release : official journal of the Controlled Release Society · 2025Review
- Computer-driven formulation development of Ginsenoside Rh2 ternary solid dispersion.Drug delivery and translational research · 2025Article
- Artificial intelligence-driven rational design of ionizable lipids for mRNA delivery.Nature communications · 2024Article
- The Dawn of a New Pharmaceutical Epoch: Can AI and Robotics Reshape Drug Formulation?Advanced healthcare materials · 2024Article
- Machine Learning for Predicting Drug Release Behavior of PLGA Microspheres.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Microspheres have gained much attention from pharmaceutical and medical industry due to the excellent biodegradable and long controlled-release characteristics. However, the drug release behavior of microspheres is influenced by complicated formulation and manufacturing factors. The traditional formulation development of microspheres is intractable and inefficient by the experimentally trial-and-error methods. This research aims to build a prediction model to accelerate microspheres product development for small-molecule drugs by machine learning (ML) techniques. Two hundred eighty-six microsphere formulations with small-molecule drugs were collected from the publications and pharmaceutical company, including the dissolution temperature at both 37 ℃ and 45 ℃. After the comparison of fourteen ML approaches, the consensus model achieved accurate predictions for the validation set at 37 ℃ and 45 ℃ (R
Indexed as
Identifiers
36454434What OpenQuestion 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 OpenQuestion graph.