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February 15, 2024
InSilico Medicine, a clinical-stage company utilizing generative artificial intelligence (AI) for drug discovery, reveals the development of
December 29, 2023
Insilico Medicine ("Insilico"), a generative artificial intelligence (AI)-driven clinical-stage drug discovery company, today announced the nomination of ISM8001, a novel molecule targeting FGFR2/3 for the treatment of tissue-agnostic solid tumors bringing the total number of PCCs nominated in 2023 to six.
July 5, 2023
After having natural human-like conversations with humans, AI could potentially be treating them medically, as the first drug fully generated by artificial intelligence has now entered clinical...
July 3, 2023
Washington DC (UPI) Jul 2, 2023 - The first dose of a drug developed by artificial intelligence has been delivered to its first patient.
July 3, 2023
In a first, a drug discovered and designed using artificial intelligence (AI) for the treatment of idiopathic pulmonary fibrosis (IPF), a chronic disease that causes scarring in the lungs, has entered human clinical trials.Hong Kong-based ...
July 3, 2023
In a first, a drug discovered and designed using artificial intelligence (AI) for the treatment of idiopathic pulmonary fibrosis (IPF)
July 3, 2023
In a first, a drug discovered and designed using artificial intelligence (AI) for the treatment of idiopathic pulmonary fibrosis (IPF)
July 2, 2023
Insilico Medicine, a biotechnology company based in Hong Kong, announced that human patients have begun receiving the drug INS018_055, an anti-fibrotic small molecule inhibitor.
June 29, 2023
The first-ever drug generated by artificial intelligence has entered Phase 2 clinical trials, with the first dose successfully administered to a human, Insilico Medicine announced yesterday.
June 21, 2023
A new research paper was published in Aging (listed by MEDLINE/PubMed as "Aging (Albany NY)" and "Aging-US" by Web of Science) Volume 15, Issue 11, entitled, "Precious1GPT: multimodal transformer-based transfer learning for aging clock development and feature importance analysis for aging and age-related disease target discovery."