HyperLab Blog - AI

HyperLab’s Hyper Screening, In-house Screening, and Hyper Screening X transform drug discovery. Hyper Screening delivers a 9% hit ratio, boosting efficiency in identifying active compounds.

We've taken an early look at key ICML 2025 papers on drug discovery, bioinformatics, and molecular generation.

Hyper Binding Co-folding builds on AlphaFold3 to enhance precision and usability, boosting accuracy and efficiency in drug discovery.

"HyperLab 2.0," equipped with more advanced features and workflows, has been released.

The HyperLab AI assistant is an LLM-based tool specialized for drug development, automating tasks from literature review to data analysis to maximize research productivity.

The $500B “Stargate Project” — What’s behind President Trump’s bold move, and what does it really mean?

Introduces the concept of deep learning architecture and compares two representative models: Transformer and Titans.

Here’s why AI drug development is gaining attention, along with its past, present, and future at a glance

Hyper Screening X utilizes RxnFlow to efficiently explore a 7-trillion-compound ultra-large library, identifying innovative drug candidates with low binding energy and over 60% synthetic feasibility.

In this article, we introduce the development background and outstanding performance of PIGNet, which overcomes the limitations of traditional molecular docking by integrating deep learning with physical laws.