RecruitingNot ApplicableNCT07414576

AI-driven Total Parenteral Nutrition Platform

Clinical Decision Support for Total Parenteral Nutrition Constituents in Neonatal Intensive Care Unit (NICU) Patients: A Pilot Study


Sponsor

Takeoff41, Inc.

Enrollment

260 participants

Start Date

Jan 21, 2026

Study Type

INTERVENTIONAL

Conditions

Summary

This study tests whether an artificial intelligence (AI) tool can help doctors order total parenteral nutrition (TPN) for babies in the neonatal intensive care unit (NICU). Premature babies often cannot eat by mouth and need nutrition delivered through an IV. Ordering TPN is complex, time-consuming, and mistakes can happen. This study will test an AI tool that suggests TPN formulas to doctors based on each baby's lab values and health information. Doctors can accept, change, or reject the suggestions at any time. The main goal is to measure how often doctors accept the AI suggestions. The study will also track time to complete TPN orders, weight changes, days on TPN, whether lab values stay in normal ranges, provider satisfaction, and baby health outcomes including complications such as lung disease, brain bleeding, infections, and other conditions common in premature babies. Babies admitted to the NICU who need TPN may participate if their doctors agree to use the tool. Each baby will be in the study while they need TPN, typically about 14 days. The AI tool only makes suggestions and does not replace doctor decision-making. All other care remains the same as standard practice.


Eligibility

Max Age: 6 Months

Inclusion Criteria4

  • Any newborns or infants requiring total parenteral nutrition in a neonatal ICU that performs daily laboratory tests
  • -month old at the time of admission
  • Any gestational age or birthweight
  • Any race or sex

Exclusion Criteria1

  • \- Infants deem unfit for the suggested TPN due to safety concerns by physicians

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Interventions

DEVICEAI-driven total parenteral nutrition (TPN)

An AI-driven clinical decision support (CDS) software integrated with EHR system that provides TPN composition recommendations to NICU providers. The tool uses patient lab values, basic profile (days since birth, weight, gestational age), and physician inputs to suggest TPN components. Providers can accept, modify, or decline if needed. The final prescribing authority remains with the providers. The intervention targets provider workflow efficiency while maintaining precision and equivalent patient outcomes (including labs and long-term adverse outcomes).


Locations(1)

Stanford University

Stanford, California, United States

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NCT07414576


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