ArticleACS omega2020
Prediction of Drug Loading in the Gelatin Matrix Using Computational Methods.
Article in ACS omega, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed.
- Nanocurcumin-containing Spongy Membrane for Improving the Quality of Hard and Soft Tissues in the Extracted Tooth Area: A Double-Blind Split-Mouth Clinical Trial Study.Pharmaceutical nanotechnology · 2025Trial
- Encapsulation of Protein-Based Drug Carriers for Controlled Loading and Releasing Efficiency: A Review.The protein journal · 2026Review
- Bioinspired caffeic acid-laden milk protein-based nanoparticles targeting folate receptors for breast cancer treatment.Therapeutic delivery · 2025Article
- Gelatin and lipidoid integrate to createBioactive materials · 2024Article
- Molecular Design of Encapsulin Protein Nanoparticles to Display Rotavirus Antigens for Enhancing Immunogenicity.Vaccines · 2024Article
- Article
- Enhancing Effector Jurkat Cell Activity and Increasing Cytotoxicity against A549 Cells Using Nivolumab as an Anti-PD-1 Agent Loaded on Gelatin Nanoparticles.Gels (Basel, Switzerland) · 2024Article
- Application of Nanoparticles for Immunotherapy of Allergic Rhinitis.International journal of nanomedicine · 2024Review
- Translational Challenges and Prospective Solutions in the Implementation of Biomimetic Delivery Systems.Pharmaceutics · 2023Review
- Review
- Article
- Peptide-Based Drug Delivery Systems.Medicina (Kaunas, Lithuania) · 2021Review
- Evolution of the Computational Pharmaceutics Approaches in the Modeling and Prediction of Drug Payload in Lipid and Polymeric Nanocarriers.Pharmaceuticals (Basel, Switzerland) · 2021Review
- Comparing cefotaxime and ceftriaxone in combating meningitis through nose-to-brain delivery using bio/chemoinformatics tools.Scientific reports · 2020Article
- Chloroquine and hydroxychloroquine for combating COVID-19: Investigating efficacy and hypothesizing new formulations using Bio/chemoinformatics tools.Informatics in medicine unlocked · 2020Article
- Mechanistic Understanding From Molecular Dynamics Simulation in Pharmaceutical Research 1: Drug Delivery.Frontiers in molecular biosciences · 2020Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The delivery of drugs is a topic of intense research activity in both academia and industry with potential for positive economic, health, and societal impacts. The selection of the appropriate formulation (carrier and drug) with optimal delivery is a challenge investigated by researchers in academia and industry, in which millions of dollars are invested annually. Experiments involving different carriers and determination of their capacity for drug loading are very time-consuming and therefore expensive; consequently, approaches that employ computational/theoretical chemistry to speed have the potential to make hugely beneficial economic, environmental, and health impacts through savings in costs associated with chemicals (and their safe disposal) and time. Here, we report the use of computational tools (data mining of the available literature, principal component analysis, hierarchical clustering analysis, partial least squares regression, autocovariance calculations, molecular dynamics simulations, and molecular docking) to successfully predict drug loading into model drug delivery systems (gelatin nanospheres). We believe that this methodology has the potential to lead to significant change in drug formulation studies across the world.
Identifiers
What 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.