drTarget
DrTarget applies machine learning to drug discovery, leveraging proprietary databases constructed from public sources like ChEMBL, NCBI, and Uniprot. Their tools predict molecular activity, identify new targets, and analyze pathways, aiding in drug repurposing and the design of compound collections for screening. The company's approach aims to reduce research costs and accelerate the drug discovery process by identifying molecules with a high likelihood of activity against specific targets. They offer solutions for prediction of activity, target identification, pathways analysis, and drug repurposing, utilizing algorithms such as decision trees, random forests, naive Bayes, neural networks, and support vector machines. DrTarget collaborates with biotech companies, research institutions, and pharmaceutical partners to accelerate research through AI-optimized screening.
drTarget
DrTarget applies machine learning to drug discovery, leveraging proprietary databases constructed from public sources like ChEMBL, NCBI, and Uniprot. Their tools predict molecular activity, identify new targets, and analyze pathways, aiding in drug repurposing and the design of compound collections for screening. The company's approach aims to reduce research costs and accelerate the drug discovery process by identifying molecules with a high likelihood of activity against specific targets. They offer solutions for prediction of activity, target identification, pathways analysis, and drug repurposing, utilizing algorithms such as decision trees, random forests, naive Bayes, neural networks, and support vector machines. DrTarget collaborates with biotech companies, research institutions, and pharmaceutical partners to accelerate research through AI-optimized screening.