Elbadawi, Moe;
Li, Hanxiang;
Basit, Abdul W;
Gaisford, Simon;
(2024)
The Role of Artificial Intelligence in Generating Original Scientific Research.
International Journal of Pharmaceutics
, 652
, Article 123741. 10.1016/j.ijpharm.2023.123741.
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Abstract
Artificial intelligence (AI) is a revolutionary technology that is finding wide application across numerous sectors. Large language models (LLMs) are an emerging subset technology of AI and have been developed to communicate using human languages. At their core, LLMs are trained with vast amounts of information extracted from the internet, including text and images. Their ability to create human-like, expert text in almost any subject means they are increasingly being used as an aid to presentation, particularly in scientific writing. However, we wondered whether LLMs could go further, generating original scientific research and preparing the results for publication. We taskedGPT-4, an LLM, to write an original pharmaceutics manuscript, on a topic that is itself novel. It was able to conceive a research hypothesis, define an experimental protocol, produce photo-realistic images of printlets, generate believable analytical data from a range of instruments and write a convincing publication-ready manuscript with evidence of critical interpretation. The model achieved all this is less than 1h. Moreover, the generated data were multi-modal in nature, including thermal analyses, vibrational spectroscopy and dissolution testing, demonstrating multi-disciplinary expertise in the LLM. One area in which the model failed, however, was in referencing to the literature. Since the generated experimental results appeared believable though, we suggest that LLMs could certainly play a role in scientific research but with human input, interpretation and data validation. We discuss the potential benefits and current bottlenecks for realising this ambition here.
| Type: | Article |
|---|---|
| Title: | The Role of Artificial Intelligence in Generating Original Scientific Research |
| Location: | Netherlands |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.ijpharm.2023.123741 |
| Publisher version: | http://dx.doi.org/10.1016/j.ijpharm.2023.123741 |
| Language: | English |
| Additional information: | © 2024 The Author(s). Published by Elsevier B.V. under a Creative Commons license (http://creativecommons.org/licenses/by/4.0/). |
| Keywords: | Pharmaceutical 3D printing, Selective laser sintering, Artificial intelligence, Large language models, Poly(D,L-lactide-co-glycolide), (PLGA) |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Life Sciences > UCL School of Pharmacy > Pharmaceutics |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10185917 |
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