Dual Drug Repurposing: The Example of Saracatinib
Open accessAbstract
Saracatinib (AZD0530) is a dual Src/Abl inhibitor initially developed by AstraZeneca for cancer treatment; however, data from 2006 to 2024 reveal that this drug has been tested not only for cancer treatment, but also for the treatment of other diseases. Despite the promising pre-clinical results and the tolerability shown in phase I trials, where a maximum tolerated dose of 175 mg was defined, phase II clinical data demonstrated a low therapeutic action against several cancers and an elevated rate of adverse effects. Recently, pre-clinical research aimed at reducing the toxic effects and enhancing the therapeutic performance of saracatinib using nanoparticles and different pharmacological combinations has shown promising results. Concomitantly, saracatinib was repurposed to treat Alzheimer’s disease, targeting Fyn. It showed great clinical results and required a lower daily dose than that defined for cancer treatment, 125 mg and 175 mg, respectively. In addition to Alzheimer’s disease, this Src inhibitor has also been studied in relation to other health conditions such as pulmonary and liver fibrosis and even for analgesic and anti-allergic functions. Although saracatinib is still not approved by the Food and Drug Administration (FDA), the large number of alternative uses for saracatinib and the elevated number of pre-clinical and clinical trials performed suggest the huge potential of this drug for the treatment of different kinds of diseases.
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Saracatinib (AZD0530) is a tyrosine kinase inhibitor undergoing Phase II trials and has been demonstrated to improve memory in transgenic mice models of AD.
“The tyrosine kinase inhibitor saracatinib (AZD0530 (labeled as 14, Figure 5)) is undergoing Phase II trials [174,175,176] and has been demonstrated to improve memory in transgenic mice models of AD.”
From Recent Advances in Therapeutics for the Treatment of Alzheimer’s Disease (2024) · cites this paper as [175]
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Recent Advances in Therapeutics for the Treatment of Alzheimer’s Disease
Thawabteh, A. M., Ghanem, A. W., AbuMadi, S., Thaher, D., Jaghama, W., Karaman, D., & Karaman, R. (2024) · Molecules · doi:10.3390/molecules29215131 · Cited by 56 · see citing works
- Authors
- Ramos, R., & Vale, N.
- Affiliations
- Universidade do Porto (PT)
- Corresponding author
- Vale, Nuno
- Venue
- International Journal of Molecular Sciences
- Publisher
- MDPI AG
- Published
- 2024-04-22
- Volume
- 25
- Issue
- 8
- Pages
- 4565
- ISSN
- 1422-0067 (ISSN-L)
- PMC
- PMC11050334
- OpenAlex
- W4395011119
- Cited by
- 24
- References
- 82
- Citations by year
- 2026: 8 · 2025: 13 · 2024: 3
- FWCI
- 1.36
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- International Journal of Molecular Sciences (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- Funders
- Fundo Europeu de Desenvolvimento Regional (FEDER) (IF/00092/2014/CP1255/CT0004)
- Fundação para a Ciência e a Tecnologia (FCT) (IF/00092/2014/CP1255/CT0004)
- Faculty of Medicine, University of Porto (FMUP) (IF/00092/2014/CP1255/CT0004)
- Topics
- Health Sciences › Medicine › Physiology › Alzheimer's disease research and treatments
- Health Sciences › Medicine › Pathology and Forensic Medicine › Cancer Mechanisms and Therapy
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- saracatinib, AZD0530, drug repurposing, Alzheimer's disease, Fyn, pulmonary fibrosis, liver fibrosis, analgesia, anti-allergic activity, nanoparticle drug delivery, adverse effects, cancer therapy
- MeSH terms
- Alzheimer Disease, Animals, Antineoplastic Agents, Humans, Neoplasms, Quinazolines, src-Family Kinases, Protein Kinase Inhibitors, Benzodioxoles, Drug Repositioning
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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