Takeoff41, Inc.
Developer of an AI-driven clinical decision support platform that generates personalized parenteral nutrition (TPN) recommendations for neonatal intensive care. The platform integrates with electronic health records, applies pharmacological and physicochemical safety checks, and is supported by peer‑reviewed research and clinical feasibility studies.
Industries
N/A
Nr. of Employees
small (1-50)
Products
AI-guided parenteral nutrition platform
Platform that formulates and orders parenteral nutrition for neonatal patients using validated AI models, EHR integration, configurable institutional policies, and automated safety evaluations.
AI-guided parenteral nutrition platform
Platform that formulates and orders parenteral nutrition for neonatal patients using validated AI models, EHR integration, configurable institutional policies, and automated safety evaluations.
Services
Onboarding and integration of AI-based parenteral nutrition recommendation workflows into hospital EHR environments with configurable governance and safety settings.
A clinical decision support platform that generates personalized, adjustable parenteral nutrition formulations for neonatal intensive care; includes safety checks, nutrition analytics, and EHR order workflow integration.
Onboarding and integration of AI-based parenteral nutrition recommendation workflows into hospital EHR environments with configurable governance and safety settings.
A clinical decision support platform that generates personalized, adjustable parenteral nutrition formulations for neonatal intensive care; includes safety checks, nutrition analytics, and EHR order workflow integration.
Expertise Areas
- Neonatal clinical decision support
- Parenteral nutrition optimization
- EHR integration and interoperability
- Clinical AI development and validation
Key Technologies
- Machine learning / deep learning
- Natural language processing for clinical text
- Clinical decision support systems
- EHR integration (in‑context ordering and order return)
News & Updates
Launched a sequential-design feasibility study deploying the AI-assisted TPN ordering workflow in a live NICU environment to enroll approximately 260 infants and measure physician acceptance of AI recommendations.
Obtained an exclusive license for the patent covering the core AI methods for data-driven TPN formulation and assignment using EHR data.
FDA review concluded the system provides advisory recommendations that clinicians can review, adjust, or override, and therefore did not meet the definition of a regulated medical device.
Advanced to Phase II funding to support EHR integration, safety and compliance infrastructure, and pilot study launches following completion of Phase I milestones.
Peer-reviewed study underlying the AI platform was selected as a finalist for the Clinical Research Forum Top 10 Clinical Research Achievement Awards.
Peer-reviewed article describing AI models trained on a decade of neonatal TPN prescriptions that identified standardized formulas and showed clinical performance aligned with expert recommendations.
Launched a sequential-design feasibility study deploying the AI-assisted TPN ordering workflow in a live NICU environment to enroll approximately 260 infants and measure physician acceptance of AI recommendations.
Obtained an exclusive license for the patent covering the core AI methods for data-driven TPN formulation and assignment using EHR data.
FDA review concluded the system provides advisory recommendations that clinicians can review, adjust, or override, and therefore did not meet the definition of a regulated medical device.
Advanced to Phase II funding to support EHR integration, safety and compliance infrastructure, and pilot study launches following completion of Phase I milestones.
Peer-reviewed study underlying the AI platform was selected as a finalist for the Clinical Research Forum Top 10 Clinical Research Achievement Awards.
Peer-reviewed article describing AI models trained on a decade of neonatal TPN prescriptions that identified standardized formulas and showed clinical performance aligned with expert recommendations.