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Scan a medicine and see it within the protein it acts on, through an interactive 3D model, with plain-language explanations and usage & timing warnings when two of your medicines hit the same target.
analytics pipeline
Unattended Taskmaster: a living evidence graph so LLM answers are more precise and checkable.
Accelerate Target Discovery & MoA with 10x Speed Thousands of potential medical breakthroughs stay hidden because research is siloed. We uncover the hidden links for novel treatments.
ChatGPT tells you about biology. Benchwork does the biology, and shows its work.
“Predicting lung toxicity from molecular structure of drugs.”
ToxIQ accelerates drug discovery using AI to predict and visually explain chemical toxicity. Our assistant instantly pulls live FDA and PubChem data to map drug safety and real-world side effects.
We use quantum algorithms and quantum hardware to screen Alzheimer's drug candidates. Combining IBM quantum hardware with AI protein analysis to predict what drugs will actually bind to the target.
Reversing drug discovery to unlock rare disease treatments from deprioritized and generic drugs.
An AI-powered pipeline that lets you ask a simple question, "Does this drug bind this protein?" and automatically handles all the computational bottlenecks behind the scenes to give you an answer.
Accelerating Alzheimer's cures by replacing years of animal trials with minutes of AI prediction.
NeuThera is an AI-driven drug discovery toolkit integrating multiple SOTA generative models for de novo molecular design. Combines graph-based retrieval with advanced compound fingerprint embeddings.
Heisenberg.ai is a cutting-edge, AI-powered drug discovery platform that leverages advanced machine learning and molecular modeling to streamline the development of new medication for common diseases!
We implemented a predictive tool with machine learning to determine the most appropriate drugs to treat a disease. We aim to reduce drug production costs as well as the development time of new drugs.
An iterative process that uses two machine learning models to generate the best inhibitors for a target protein
