March 2021 in “Medico-Legal Update” The androgen receptor gene doesn't affect women with recurrent spontaneous abortions, but having a mutant genotype might protect against it.
10 citations
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August 1998 in “Journal of Investigative Dermatology” The compounds tested could potentially treat hair loss and alopecia.
February 2026 in “Advanced Science” Targeting the p300/AR axis may help treat polycystic ovary syndrome.
April 2024 in “The Journal of urology/The journal of urology” SRD5A2 methylation in blood can predict how well someone will respond to finasteride treatment.
3 citations
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November 2022 in “European Journal of Human Genetics” New models predict male pattern baldness better than old ones but still need improvement.
89 citations
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August 2013 in “PloS one” Androgen receptors are active in many tissues of both male and female mice, not just reproductive organs.
8 citations
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March 2002 in “Archiv Der Pharmazie” The compound 4c effectively inhibits the enzyme linked to hair loss.
January 2026 in “RSC Advances” Epristeride's metabolism in zebrafish helps improve doping detection methods.
32 citations
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September 2018 in “Journal of pharmaceutical sciences” The model better predicts how water-loving and fat-loving substances move through the skin by including tiny pores and hair follicle paths.
2 citations
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July 2024 in “Journal of Cosmetic Dermatology” The HAIR-Q is a reliable tool for assessing patient satisfaction with hair loss treatments.
November 2025 in “Frontiers in Medicine” The SAALIQ is a reliable tool for measuring the impact of alopecia areata on Spanish-speaking patients' quality of life.
1 citations
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November 2023 in “BMC chemistry” Tadalafil and Finasteride may help treat aggressive melanoma.
3 citations
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June 2023 in “Frontiers in Medicine” A new model uses specific blood markers to predict if children's hair loss will return.
A new system for classifying curly hair types using precise measurements can improve hair care products and cultural inclusion.
September 2024 in “International Journal of Applied Pharmaceutics” A reliable method was developed to measure Finasteride and Tadalafil in rat blood.
October 2025 in “Frontiers in Toxicology” A new method effectively predicts estrogen-related health effects for early screening.
April 2026 in “The Journal of Steroid Biochemistry and Molecular Biology” 110 citations
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February 2024 in “Journal of Chemical Information and Modeling” PandaOmics uses AI to find new disease treatment targets and biomarkers.
3 citations
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April 2019 in “Clinical Therapeutics” Computational tools identified 29 drugs that could potentially target 19 genes involved in chemotherapy-induced hair loss, which could lead to more effective treatments.
January 2014 in “Journal of Clinical and Investigative Dermatology” Young rats are better for testing hair loss treatments after chemotherapy.
September 2019 in “Journal of Investigative Dermatology” The 3D-SeboSkin model effectively simulates Hidradenitis suppurativa and is useful for future research.
12 citations
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December 2012 in “Current Drug Targets” The Androgen Receptor could be a target for treating diseases like cancer, but more research is needed to confirm the effectiveness of potential treatments.
January 2025 in “PROTEOMICS” Drug repositioning is a promising way to quickly develop new treatments, especially for rare diseases.
23 citations
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October 2008 in “Journal of medicinal chemistry” PF-998425 is a new, effective, and non-phototoxic treatment for skin conditions related to androgens.
22 citations
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October 2001 in “Biochemical Pharmacology” GI198745 is more potent and longer-lasting than finasteride, potentially better for treating hair loss.
70 citations
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August 2019 in “European Journal of Medicinal Chemistry” ETS2 drives cancer progression in squamous cell carcinoma and is linked to poor patient outcomes.
1 citations
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September 2017 C-scores can help predict gain-of-function and loss-of-function mutations.
37 citations
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October 2017 in “Saudi pharmaceutical journal” All evaluated shampoos meet Saudi standards.
May 2026 in “International Journal of Drug Delivery Technology” Machine learning can accurately predict PCOS phenotypes using lifestyle and symptom data.