AtThinkBio.Ai®, we redefine life sciences R&D with powerful AI platforms that break through bottlenecks in drug discovery, data integration, and clinical development. Our solutions equip biotech innovators, pharma leaders, CROs, and academic partners to deliver faster breakthroughs, smarter decisions, and more successful therapies
Rapidly prototype antibodies and cell therapies using AI-guided workflows.
Harness scalable platforms for data integration, target discovery, and multi-omic insights.
Enhance project delivery with AI-driven LIMS tools and advanced data analytics.
Accelerate translational research through discovery tools and curated datasets powered by AI.
With BioThinkHub™ and proprietary knowledge graphs, design adaptive, data-integrated clinical trials that improve robustness and outcomes.
Combine clinical, genomic, and genetic data to identify patient subgroups most likely to benefit from targeted therapies — boosting trial success rates.
Apply advanced AI models to decode complex clinical and omics data, optimize patient selection, and enhance therapeutic outcomes, including tumor microenvironment insights.
Even after failed trials, use BioThinkHub™ to uncover responder subgroups and predictive biomarkers, guiding recovery strategies and future development.
Make smarter, faster research decisions by uniting experimental design, technology choices, data insights, and knowledge interpretation with our integrated AI copilots.
With Pixelomics™, enable detailed segmentation, annotation, and interpretation of medical images to support personalized oncology strategies and advanced tissue analysis.
An intelligent, integrated platform with four specialized copilots (Experimental, Technology, Data, and Knowledge) to streamline workflows, optimize decisions, and accelerate innovation.
An advanced AI system that integrates omics data and scientific knowledge to identify optimal multi-targeting strategies for antibody development, enhancing therapeutic design and clinical success.
Powerful AI models for medical image analysis, including cell-type identification and spatial proteomics, to drive personalized cancer therapies and improve diagnostic precision.
Aggregates structured medical, genomic, and clinical data to fuel research, precision treatment strategies, and clinical trials.