Artificial intelligence generates novel 3D printing formulations Article Swipe
Moe Elbadawi
,
Hanxiang Li
,
Siyuan Sun
,
Manal E. Alkahtani
,
Abdul W. Basit
,
Simon Gaisford
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.apmt.2024.102061
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1016/j.apmt.2024.102061
Formulation development is a critical step in the development of medicines. The process requires human creativity, ingenuity and in-depth knowledge of formulation development and processing optimization, which can be time-consuming. Herein, we tested the ability of artificial intelligence (AI) to create de novo formulations for three-dimensional (3D) printing. Specifically, conditional generative adversarial networks (cGANs), which are generative models known for their creativity, were trained on a dataset consisting of 1437 fused deposition modelling (FDM) printed formulations that were extracted from both the literature and in-house data. In total, 27 different cGANs architectures were explored with varying learning rate, batch size and number of hidden layers parameters to generate 270 formulations. After a comparison between the characteristics of AI-generated and human-generated formulations, it was discovered that cGANs with a medium learning rate (10−4) could strike a balance in generating formulations that are both novel and realistic. Four of these formulations were fabricated using an FDM printer, of which the first AI-generated formulation was successfully printed. Our study represents a milestone, highlighting the capacity of AI to undertake creative tasks and its potential to revolutionize the drug development process.
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- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.apmt.2024.102061
- OA Status
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Artificial intelligence generates novel 3D printing formulationsWork title
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articleOpenAlex work type
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enPrimary language
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2024Year of publication
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2024-01-16Full publication date if available
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Moe Elbadawi, Hanxiang Li, Siyuan Sun, Manal E. Alkahtani, Abdul W. Basit, Simon GaisfordList of authors in order
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https://doi.org/10.1016/j.apmt.2024.102061Publisher landing page
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hybridOpen access status per OpenAlex
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https://doi.org/10.1016/j.apmt.2024.102061Direct OA link when available
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Artificial intelligence, Generative grammar, Computer science, Process (computing), Creativity, Ingenuity, Engineering drawing, Engineering, Programming language, Economics, Law, Political science, Neoclassical economicsTop concepts (fields/topics) attached by OpenAlex
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2025: 29, 2024: 6Per-year citation counts (last 5 years)
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| primary_location.source.host_organization_lineage_names | Elsevier BV |
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| primary_location.raw_source_name | Applied Materials Today |
| primary_location.landing_page_url | https://doi.org/10.1016/j.apmt.2024.102061 |
| publication_date | 2024-01-16 |
| publication_year | 2024 |
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