Evidence map›Paper›PMID 37552427›Full record

ArticleAAPS PharmSciTech2023

Integrating Artificial Intelligence with Quality by Design in the Formulation of Lecithin/Chitosan Nanoparticles of a Poorly Water-Soluble Drug.

Marwa H S Dawoud, Islam S Mannaa, Amira Abdel-Daim, Nabila M Sweed

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Article in AAPS PharmSciTech, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

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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.

Marwa H S DawoudDepartment of Pharmaceutics, Faculty of Pharmacy, October University for Modern Sciences and Arts, intersection of 26th of July road and Elwahat road, 6th of October city, Giza, Egypt. mdawoud@msa.edu.eg.ORCID http://orcid.org/0000-0001-8281-4144
Islam S MannaaDepartment of Pharmaceutics, Faculty of Pharmacy, October University for Modern Sciences and Arts, intersection of 26th of July road and Elwahat road, 6th of October city, Giza, Egypt.
Amira Abdel-DaimDepartment of Biochemistry, Faculty of Pharmacy, October University for Modern Sciences and Arts, Giza, Egypt.
Nabila M SweedDepartment of Pharmaceutics, Faculty of Pharmacy, October University for Modern Sciences and Arts, intersection of 26th of July road and Elwahat road, 6th of October city, Giza, Egypt.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The aim of the current study is to explore the potential of artificial intelligence (AI) when integrated with Quality by Design (QbD) approach in the formulation of a poorly water-soluble drug, for its potential use in carcinoma. Silymarin is used as a model drug for its potential effectiveness in liver cancer. A detailed QbD approach was applied. The effect of the critical process parameters was studied on each of the particle size, size distribution, and entrapment efficiency. Response surface designs were applied in the screening and optimization of lecithin/chitosan nanoparticles, to obtain an optimized formula. The release rate was tested, where artificial neural network models were used to predict the % release of the drug from the optimized formula at different time intervals. The optimized formula was tested for its cytotoxicity. A design space was established, with an optimized formula having a molar ratio of 18.33:1 lecithin:chitosan and 38.35 mg silymarin. This resulted in nanoparticles with a size of 161 nm, a polydispersity index of 0.2, and an entrapment efficiency of 97%. The optimized formula showed a zeta potential of +38 mV, with well-developed spherical particles. AI successfully showed high prediction ability of the drug's release rate. The optimized formula showed an enhancement in the cytotoxic effect of silymarin with a decreased IC50 compared to standard silymarin. Lecithin/chitosan nanoparticles were successfully formulated, with deep process and product understanding. Several tools were used as AI which could shift pharmaceutical formulations from experience-dependent studies to data-driven methodologies in the future.

Indexed as

ChitosanNanoparticlesSilymarinArtificial IntelligenceDrug CarriersDrug LiberationLecithinsParticle SizeWaterChitosanDrug CarriersLecithinsSilymarinWaterartificial neural networkdeep learninghepatocellular carcinomaIshikawa diagramlecithin chitosan nanoparticlesquality by designresponse surface design

Identifiers

PMID37552427

What OpenQuestion holds

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Registered trials

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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.