1- A federative AI which turns unreachable biomedical inputs into browsable assets
2- Semantic models which understand risks, benefits and patients profiles
3- A User Interface that lets you target, browse, visualize & compare billions of new datapoints
1 tool gathering information, multiple models that knows what risks, benefits and patients are and provides automated reports
We improve patients' and drugs' safety through :
- Pharmacovigilance Automation : signal detection, automated PSURs
- Translational Safety : benefit-risk prediction between clinical phases
- Benefit-Risk Assessment automated generation :12 months VS 1 week
- Clinical optimization : recruitments, market access
ArcaScience provided the first and only solution giving us both the ability to leverage and to access our data out of hundreds of different sources never merged together and to target crucial oncology datapoints (mostly biomarkers and adverse events), leading us to save millions over a year and significantly accelerate our pace of development.
85m publications & 20m medical records, clinical trials, R&D data etc.
>80% of your own data rendered annotated, interoperable & searchable
Starting from state of the art querying, side-effect retrieval, all the way to gene extraction
What secondary data targets this molecule/biomarker/etc. ?
How can I discover biomarkers to assist with patient stratification?
How can I monitor my molecule’s effects? Dynamic Signal Detection Dashboard
How can I spend less time reporting? Automatic filling & rendering of PSURs
What is this molecule’s potential for clinical development?
Can we predict safety issues?
What is the potential benefit/risk of this drug for my patients?
Translational Safety with Patient Profiling
How can I simplify my protocol drafting? State of the art Benefit-Risk automated report
Where can I find specific patients?
HCPs targeting and patient profiling
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