Pyxir

®

To inspire drug discovery from

multiple dimensions

About Pyxir®

Pyxir®, our drug discovery platform, provides end-to-end solutions in preclinical drug discovery. The Pyxir® Platform has integrated advanced artificial intelligence technologies and domain knowledge from computational chemistry, medicinal chemistry and biology.

Evolved from tools and experience of medicinal chemistry, computational chemistry and biology, the Pyxir® platform provides end-to-end solutions in preclinical drug discovery such as molecular generation, property prediction, virtual screening and optimization. Using hundreds of models and world leading algorithms, the Pyxir® platform inspires drug discovery from multiple dimensions.

About Pyxir<span>&#174;</span>About Pyxir<span>&#174;</span>

Technology Highlights

Multi-objective optimization

Galixir's independently developed SSF multi-objective molecular optimization system can simultaneously support the optimization of multiple indicators such as activity, ADME, synthetic difficulty, diversity, etc., generating molecules that meet corresponding conditions.

Multi-objective optimization

Variety and Novelty

Galixir leverages cutting-edge AI algorithms to find candidate molecules with high potency, good druggability and novel structures. Our self-developed molecular generation and design models have stood out in diversity and novelty.

Variety and Novelty

Target Selectivity

The requirements for target selectivity are attained by building AI models and using computational chemistry tools to capture subtle differences in targets and binding sites.

Target Selectivity

Multi-dimensional Property Prediction

Based on multi-dimensional data, our ADMET property prediction models are used in virtual high-throughput screening of candidate molecules.

Multi-dimensional Property Prediction
Multi-objective
optimization
Variety
and Novelty
Target
Selectivity
Multi-dimensional
Property Prediction

To empower your pre-clinical discovery with AI

Novel target-based design of molecules
Virtual high-throughput screening of hit compounds
Predicting and optimizingthe drug-likeness of lead compounds
Designing the synthetic pathwayfor molecules