AI-powered drug discovery We combine cutting-edge machine learning and biology to advance drug discovery Get in touch What we do We develop state-of-the-art, AI-based computational technologies from rich, multimodal patient data to discover new treatments ...
Pharmaeconomica - AI-Driven Drug Discovery. We discover and optimize active, specific, non-toxic, and patentable small molecules delivering superior drug candidates in a faster and more cost-effective manner.
最近一篇发表在 Nature 子刊 Nature Machine Intelligence 上的论文《人工智能驱动的药物发现的双重用途》（Dual - use of artificial Intelligence -powered drug discovery）显然把它的作者吓坏了。这体现在文本的基调和没有透露关键信息上。一次可能性验证 2021 年，总部位于美国北卡罗来纳州罗利的 Collaborations Pharma...
该项成果以“AlphaFold accelerates artificial intelligence powered drug discovery: efficient discovery of a novel CDK20 small molecule inhibitor”(《利用AlphaFold加速人工智能赋能的药物发现:高效发现CDK20小分子抑制剂》)为题,发表在英国...
近日，该模型相关论文“Conformational Space Profiling Enhances Generic Molecular Representation for AI-powered Ligand-based Drug Discovery”已发布于国际期刊 Advanced Science 杂志。图 2. GeminiMol 模型架构图[11]。3AI 制药，未来会怎么样？去年，Insilico Medicine 公司基于 AI 生成的抗纤维化药物，名为 INS...
2023年11月,来自施维雅Patrimony团队的研究人员在Drug Discovery Today发表文章Transforming drug discovery with a high-throughput AI-powered platform: A 5-year experience with Patrimony。 文章介绍了施维雅推出的Patrimony平台如何利用计算科学和...
AIDDISON平台已商业化，并对公众开放（https://www.sigmaaldrich.com/US/en/services/software-and-digital-platforms/aiddison-ai-powered-drug-discovery）。该平台集合了了rdkit部分功能，REINVENT模型以及第三方软件软件，如BioSolveIT的FTrees算法、Cresset的Flare和pyFlare等。Rusinko A, Rezaei M, Friedrich L,...
AIDDISON平台已商业化,并对公众开放(https://www.sigmaaldrich.com/US/en/services/software-and-digital-platforms/aiddison-ai-powered-drug-discovery)。该平台集合了了rdkit部分功能,REINVENT模型以及第三方软件软件,如BioSolveIT的FTrees算法、Cresset的Flare和pyFlare等。
AIDDISON平台已商业化,并对公众开放(https://www.sigmaaldrich.com/US/en/services/software-and-digital-platforms/aiddison-ai-powered-drug-discovery)。该平台集合了了rdkit部分功能,REINVENT模型以及第三方软件软件,如BioSolveIT的FTrees算法、Cresset的Flare和pyFlare等。
Due to low success rates and long cycles of traditional drug development, the clinical tendency is to apply omics techniques to reveal patient-level disease characteristics and individualized responses to treatment. However, the heterogeneous form of data and uneven distribution of targets make drug di...