Offering services in computational sciences and technology to complement biopharma R&D
Biopharma R&D teams' key objectives from computational capabilities
Leverage in silico modeling and solutions to accelerate drug discovery and development and bring therapeutic drugs (SMOL and Biologics) faster to market.
Scale up and augment R&D by working with extended teams/service providers while keeping costs low.
Leverage AI/ML technologies to discover and design de novo drugs and reduce AEE (Avoidable Experimental Expenditure).
Develop computational solutions and building blocks that are reusable across therapeutic pipelines, and reduce the overall cost of R&D.
Enable scientists with intuitive data analysis visualization applications and frameworks leveraging modern UI technologies.
Enable accessible on-demand computational infrastructure to speed-up the processing of bioinformatics and cheminformatics pipelines while optimizing costs and minimizing dependency on technology teams to conduct computational experiments.
We offer services in 3 main categories:
We develop tools that accelerate our client’s research and development process. These solutions include our clients’ omics and single-cell omics analysis pipelines, capsid engineering for gene therapy, antibody design, etc. Our AI models, guided by in-house experts, continuously improve on the increasingly available data to provide more intelligent solutions
We develop in silico solutions to reduce Avoidable Experimental Expenditure (AEE) and accelerate drug discovery and development stages for Small Molecules (SMOL) and biologics. Our computational chemistry solutions include designing de novo molecules with generative models, predicting ADMET properties for SMOL and bRo5 compounds, and predicting reaction yields.
Cloud & Infra
Technology and Cloud
We leverage technological advances related to Data, Analytics, AI, Machine Learning, and Cloud to develop high throughput computational biology and chemistry solutions. Our focus on developing solutions for straight-through processing, high performance, robustness, scalability, extensibility, and automation helps biopharma R&D teams to minimize manual effort and accelerate drug discovery and development processes.