Artificial intelligence generates novel 3D printing formulations
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.
Highlights
- Artificial intelligence (AI) was able to create de novo formulations for three-dimensional (3D) printing.
- Conditional generative adversarial networks (cGANs) were trained on a dataset consisting of 1437 fused deposition modelling (FDM) printed formulations.
- 27 different cGANs architectures were explored with varying learning rate, batch size and number of hidden layers parameters to generate 270 formulations.
- cGANs with a medium learning rate (10−4) could strike a balance in generating formulations that were both novel and realistic.
- Four of the formulations were fabricated using an FDM printer.
- This is the first time an AI-generated formulation has been successfully printed.
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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Moe Elbadawi, Hanxiang Li, Siyuan Sun, Manal E. Alkahtani, Abdul W. Basit, Simon Gaisford, Artificial intelligence generates novel 3D printing formulations, Applied Materials Today, Volume 36, 2024, 102061, ISSN 2352-9407, https://doi.org/10.1016/j.apmt.2024.102061.
Read more article from the Basit-Group:
- The Role of Artificial Intelligence in Generating Original Scientific Research
- Ensuring the quality of 3D printed medicines
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