Privacy first
Patient data is sensitive. We design for minimal data use, strong security and respect for privacy regulations.
AI for medication safety
Personalizing medication safety through AI
Deepnosis’s goal is to revolutionize personalized medication management through the power of machine learning. We provide predictive tools for healthcare professionals to minimize adverse drug reactions, and offer patients customized education for safer medication use.
01
Predict
Machine learning models that anticipate adverse drug reactions before they happen.
02
Personalize
Guidance shaped around each patient’s own profile, not an average one.
03
Protect
Clear, timely education so patients and care teams can act with confidence.
Our mission
Every patient responds to medication differently. Safety should too.
Adverse drug reactions are a major, and often preventable, source of harm in healthcare. Deepnosis turns complex patient data into practical, individualized insight, so the right medication reaches the right person at the right dose.
Platform
From data to safer decisions
One intelligent layer that learns from the clinical picture and delivers the right insight to the right person.
- 1
Understand the patient
Securely bring together medication history, clinical context and other relevant signals into a single patient profile.
- 2
Predict the risk
Machine learning models estimate the likelihood of adverse drug reactions and highlight the factors driving each prediction.
- 3
Guide the action
Clinicians receive decision support at the point of care, while patients receive plain-language education tailored to them.
For healthcare professionals
Predictive tools that fit the way you practice
Spend less time searching for risks and more time acting on them. Deepnosis surfaces what matters for the patient in front of you.
- Early warning for potential adverse drug reactions
- Transparent, explainable risk insights
- Support for safer prescribing and dose decisions
- Designed to complement clinical judgment, never replace it
For patients
Medication education made personal
Informed patients are safer patients. Deepnosis translates complex medication information into clear guidance that fits each person’s own situation.
- Plain-language explanations of what to expect
- Personalized reminders and warning signs to watch for
- Confidence to ask better questions at every visit
- Shared understanding between patients and care teams
Principles
Built on trust
Explainable
Predictions come with the reasoning behind them, so professionals can evaluate every recommendation.
Human in the loop
AI supports the care team. Clinicians and patients always make the final decisions together.
Evidence-driven
Models are grounded in scientific evidence and continuously evaluated against real-world outcomes.
About the name
Deep learning meets gnosis.
Deepnosis blends deep learning with gnosis, the Greek word for knowledge. It reflects our belief that deeper knowledge of each patient leads to safer care for everyone.
FAQ
Questions, answered
What does Deepnosis do?
Deepnosis builds machine learning tools that personalize medication management. Clinicians get predictive insight to help minimize adverse drug reactions, and patients get customized education for safer medication use.
Who is Deepnosis for?
Deepnosis is designed for healthcare professionals such as physicians, pharmacists and care teams, and for the patients they care for.
Does Deepnosis replace clinical judgment?
No. Deepnosis is built to support, not replace, healthcare professionals. Predictions are meant to inform decisions that clinicians and patients make together.
How does Deepnosis approach patient privacy?
Privacy and security are design requirements. We follow data minimization principles and are building our practices to align with healthcare privacy regulations. Read our privacy policy.
How can I get in touch?
Email [email protected] to request early access, discuss a pilot, or ask a question.
Safer medication starts with a conversation.
We’re working with early partners across healthcare. Tell us about your team and what you’d like to improve.