ArticleDigital discovery2025
Efficient discovery of new medicine formulations using a semi-self-driven robotic formulator.
Article in Digital discovery, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Machine-Learning-Driven Optimization of Functional Excipients and Their Biointeractions in Drug Formulations.ACS pharmacology & translational science · 2026Review
- A user's guide to your first self-driving liquid handling lab.Digital discovery · 2026Article
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
We present the discovery of new medicine formulations using a semi-self-driven robotic formulator. Solubilising drugs is a significant challenge in the pharmaceutical industry, with the majority of active molecules in development for therapies being poorly soluble. The discovery of high solubility drug formulations, is a highly complex challenge involving the mixing of drugs with excipients in thousands of potential combinations. We have developed a self-driving laboratory process for the production, assessment, and optimisation of solubility of liquid formulations suitable for injectable medicines, and apply it to the example molecule curcumin. Our system discovered 7 lead formulations with high solubility (>10 mg mL
Identifiers
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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.