Fast-track drug development
Therapeutics development is complex, long, and costly. Disconnected processes and siloed data across the organization and CDMOs inhibits collaboration and informed decision making. Streamline and accelerate preclinical studies, formulation development, and CMC processes by 50% with Scientific AI.
Fragmented data is slowing your portfolio advancement and development cycles
Portfolio acceleration blockers
Siloed systems result in manual data sharing across teams and CDMOs, turning quick decisions into week-long delays. Inaccessible data prevents in silico modeling, adding 10x more time on costly wet experiments.
Past data untapped for next-gen process development
Disconnected data prevents learning from historical datasets. Current imbalance between wet to dry lab ratio limits process optimization and velocity for next-gen processes and complex drug modalities.
Limited scientist productivity
Multiple manual data entries and fragmented systems waste 50% of scientist time, increase error risk and constraints throughput. Limited FAIR data leads to lack of data reuse and repeat experiments.
Build AI-ready R&D data foundation with TetraScience: your IND acceleration engine
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The scientific data journey with TetraScience
Analytics and scientific AI use cases / apps
Use case-specific ontology
Taxonomy
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8 → 2.5 months
reduction in clone selection and stability studies
85%
reduction in COGS by increasing titer production by 10x
Parallel analysis
of clone stability and productivity of all clones by automating data collection and harmonization from bioreactors, cell counters, sc-RNA seq, LC-MS, microscopy and more
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2 weeks → 1 day
by visualizing bioreactor, cell health, metabolite, and analytical data in one dashboard
50%
gains in productivity from automated data collection, enabling near real-time decisions and troubleshooting
>10
days saved in creating a Upstream Development Report
Improve efficiency in downstream development by visualization process (FPLC) and analytical (HPLC) data
Enable smarter, faster method development and batch release by comparing performance across batches, sites, and historical data
Get faster, smarter, and more predictable development
Up to 50% productivity gain
Automate data collection, prep and transfer – eliminate manual, error-prone (re)work so scientists can focus on high-value work.
100% institutional knowledge reuse
Transform historical data into actionable, AI-ready assets that power in silico models, and fast-track process optimization.
2x faster portfolio delivery
Centralize R&D data for near real-time insights for rapid decisions at project and portfolio levels.
Streamlined regulatory prep
FAIR, traceable and contextualized data in one place streamlines regulatory dossiers prep and review.
