AI-driven solutions for Pharma and Materials Science

We offer AI-powered services for solving complex challenges in drug design and materials science. We utilize advanced software, custom-developed AI toolkits, and machine learning models to solve problems in the pharma industry, materials science, biochemistry, and chemistry. 1We work on both our own and third-party software.

We are an experienced team of scientists and developers with strong support from our parent company, Fujitsu, a the leading Japanese information and communication technology (ICT) company.

We offer the following AI-powered services:

• AI-driven SAR and QSPR modeling: Developing robust machine learning models (e.g., Random Forest, deep neural networks) to quantify the relationship between chemical structure and biological activity or material properties.

• Predictive Toxicology and ADMET Profiling: Using AI to accurately forecast the pharmacokinetic and toxicity profiles of drug candidates, reducing late-stage failures.

• Generative Design for Drugs and Materials: Employing generative AI models for the de novo design of novel molecules and materials with optimized, user-defined properties.

• AI-enhanced Materials Discovery: Accelerating the search for new materials by using AI to screen vast chemical spaces and identify promising candidates with desired characteristics.

• Predictive Analytics for Material Properties: Building models to forecast the physical, chemical, and electronic properties of materials, enabling targeted design and reducing the need for extensive experimental work.

• Explainable AI (XAI) for Model Interpretation: Providing deeper insights into the "black box" of complex models, helping to understand key drivers and build trust in AI-driven predictions.

• Custom AI Model and Software Development: Creating bespoke AI solutions and cheminformatics tools tailored to your unique research challenges and data.