2023年7月10日,

開發的第一個醫學生殖AI進入人體試驗7月10日,2023年在12:30生物技術公司Insilico醫學已經開始生成AI-discovered和發達的醫學人體試驗。的anti-fibrotic INS018_055生成AI幫助製定旨在治療特發性肺纖維化(IPF),疤痕肺部組織不可逆的肺部疾病,導致重大長期健康問題。二期臨床試驗的藥物現在美國和中國在通過人類患者的安全測試。生殖醫藥Insilico醫學自稱是“生成AI-driven”和第一個推測使用人工智能設計新藥早在2016年就在科學期刊上。自那以來,該公司已經創建了一個生成對抗網絡(GAN)來構建和組合算法提出使用商用製藥公司新藥的想法。人工智能平台。研究人員使用AI發現目標和想出一種藥物的分子結構可以幫助對抗疾病。的第一階段測試INS018_055今年順利,導致計劃的隨機、雙盲研究,將測試藥物的有效性和安全性在12周與IPF 60科目。“當我們開始開發生成人工智能藥物發現,我沒想到會看到臨床和臨床結果我們有今天,“Insilico醫學聯合首席執行官和創始人Alex Zhavoronkov說。“啟動二期試驗與這部小說抑製劑IPF代表的一個重要裏程碑深生成強化學習在藥物發現。我們將探討病人的療效AI-discovered和設計治療在臨床試驗中,這是一個真實的驗證生成的人工智能平台。 We are eager to continue to advance this potentially first-in-class therapy forward to help patients in need and show the value of generative AI in drug discovery and development.” Medical AI Applying generative AI to biology is still a new idea but is on the cusp of rapid growth. For instance, Drug discovery startup Variational AI used generative AI on its Enki platform to develop and file patents for novel small molecules that could treat COVID-19. The startup’s variational autoencoder (VAE) trained on both public and proprietary datasets to produce the protease inhibitors, which could play a key role in future COVID-19 antiviral treatments. Nvidia is a key player in the space, counting Insilico among its technology partners for bringing generative AI to pharmaceuticals. Nvidia and pharmaceutical startup Evozyne introduced a new generative AI model that can produce proteins for medicine and other industries earlier this year. The Protein Transformer Variational AutoEncoder (ProT-VAE) is built on Nvidia’s BioNeMo framework and uses generative AI to rapidly create examples of synthetic protein designs that fit given parameters and speed up development. For Insilico, Nvidia is a central component to looking for medical drugs with generative AI. The company engaged Nvidia’s DGX server system to develop its algorithms. “When we started, there were hundreds of companies claiming to use AI for drug discovery,” Zhavoronkov said. “Insilico was started as a deep learning pureplay at Nvidia GTC, a global conference on AI and the metaverse. We were one of the first to get the DevBox, test the latest hardware early, and now work on Nvidia DGX. We made a bet on generative AI early, tapped Nvidia’s best-in-class technology, worked hard, and now we can tangibly demonstrate substantial R&D performance boosts and real clinical-stage drugs imagined by AI.”