Intestinal FailureNCT07414576
AI-driven Total Parenteral Nutrition Platform
A study testing AI-driven total parenteral nutrition (TPN) in people with Intestinal Failure, run by Takeoff41, Inc. at 1 site in United States.
Trial 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. Read more about this study
- Who is it for?
- Ages Up to 6 months
- Conditions the study is for
- Intestinal Failure
- What is being tested?
- AI-driven total parenteral nutrition (TPN)
- Type of treatment
- Medical device
- Could I receive a placebo?
- No, everyone receives an active treatment
- How many people
- 260 participants
- Where
- 1 siteUnited States
- Study dates
- 21 Jan 2026to 21 Feb 2027
- Phase
- Interventional
- Are there results?
- Not yet: the study is under way
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages Up to 6 months
- All sexes
- No healthy volunteers
- Child
Who may be able to join
- Any newborns or infants requiring total parenteral nutrition in a neonatal ICU that performs daily laboratory tests
- 6-month old at the time of admission
- Any gestational age or birthweight
- Any race or sex
Who cannot join
- Infants deem unfit for the suggested TPN due to safety concerns by physicians
Trial locations and contacts
1 site in 1 country. Contact the study team or a site near you to ask about taking part.
United States1 site, 1 recruiting
- Recruiting
Stanford University
Stanford, California, 94305
Thanaphong Phongpreecha, PhD, 551-482-4827, joe@takeoff41.com
Barbara Chargin, 650-723-7222, bchargin@stanford.edu
About this study
Official title: Clinical Decision Support for Total Parenteral Nutrition Constituents in Neonatal Intensive Care Unit (NICU) Patients: A Pilot Study
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.
Read the detailed description
Our AI-driven TPN (TPN2.0) platform is a combination of AI and a premade set of TPN units. The AI is used to formulate and assign the optimal TPN unit to each infant, given their daily profile and lab test values. It is driven by decades of data, including our published morbidity risks, basic demographics, and routinely collected lab test values. The approach will save staff time and eliminate high errors in the current TPN ordering process.
Our pilot will be deployed as a clinical decision support tool that only makes recommendations, and doctors can always override it. As such, this minimally affects the current practice. We aim to enroll 260 neonates in this pilot study. The primary outcome is physician acceptance rate of TPN2.0 recommendations. Secondary outcomes include time to complete TPN orders, change in weight z-score, days on TPN, lab value abnormalities (values outside normal range), provider satisfaction, and a composite morbidity index comprising rates of bronchopulmonary dysplasia, necrotizing enterocolitis, retinopathy of prematurity, respiratory distress syndrome, congenital heart disease, sepsis, anemia, intraventricular hemorrhage, cholestasis, jaundice, pulmonary hemorrhage, pulmonary hypertension, readmission during the study, and mortality.
- Conditions
- Intestinal Failure
- Being tested
- AI-driven total parenteral nutrition (TPN)
- Keywords
- parenteral nutrition
- Medical subject headings
- Intestinal Failure, Hyperphagia
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
AI-driven total parenteral nutrition (TPN)Device
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).
| Study group | Role | What they receive |
|---|---|---|
| Standard TPN Ordering (Control) | No intervention | Patients admitted during Period 1. Providers use current standard TPN ordering practice without AI assistance. Serves as baseline comparison. |
| AI-driven total parenteral nutrition (TPN) | Experimental | Patients admitted during Period 2. Providers use the AI-assisted TPN decision support tool integrated with Epic to order TPN. Providers may opt out and use traditional ordering if needed. Receives: Device: AI-driven total parenteral nutrition (TPN) |
What is being measured
The primary outcome is the main question the study is designed to answer.
System Acceptance Rate
Percentage of AI-generated recommendations that are accepted or modified by providers for each ingredient of TPN. Measured by retrospective comparison between AI suggestion and actual TPN order submitted.
Measured: 10 months
Secondary outcomes (4)
Change in Weight Z-Score
Change in weight-for-age z-score from admission to discharge. Calculated from daily weights recorded in EMR. Target is to maintain or improve z-score trajectory in Period 2 compared to Period 1.
Measured: 10 months
Days on TPN
Number of days the infants have to get TPN
Measured: 10 months
Composite Clinical Outcome
Outcome Measure: Composite Clinical Outcome
Description: Number and proportion of participants who experienced at least one of the following neonatal morbidities during the study period: bronchopulmonary dysplasia (BPD), necrotizing enterocolitis (NEC), retinopathy of prematurity (ROP), respiratory distress syndrome (RDS), congenital heart disease (CHD), sepsis, anemia, intraventricular hemorrhage, cholestasis, jaundice, pulmonary hemorrhage, pulmonary hypertension, hospital readmission during the study period, or mortality.
Each morbidity is assessed in the same unit -- as present or absent. Participants experiencing one or more listed morbidities are counted once in the composite outcome.
Measured: 13 months
Rate of Laboratory Value Abnormalities
Outcome Measure: Abnormal Serum Laboratory Values Description: Number and proportion of participants with ≥1 serum laboratory value outside the age-appropriate normal range during the study period. Laboratory values assessed include sodium, potassium, calcium, magnesium, phosphorus, glucose, triglycerides, aspartate aminotransferase (AST), alanine aminotransferase (ALT), and direct bilirubin. Participants with one or more abnormal values will be counted once in this outcome.
Measured: 10 months
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted17 Feb 2026
- Study start21 Jan 2026
- Primary completion21 Feb 2027 (estimated)
- Study completion21 Feb 2027 (estimated)
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Intestinal FailureStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Interventional
- Phase
- Phase N/A
- Primary purpose
- Health services research
- Allocation
- Non-randomised
- Intervention model
- Sequential
- Model description
- Single-arm sequential design. Patients (participants) are assigned to one arm based on their admission timing: those admitted during Period 1 (first half of the study) receive care from providers using standard TPN ordering, while those admitted during Period 2 (second half) receive care from providers using AI-assisted ordering. Since the average patient stay is \~14 days, patients are exposed to only one condition. A sequential design is necessary because in the NICUs each patient is cared for by multiple rotating providers depending on the day of the week and shift coverage, making parallel randomization impractical-if some providers had AI assistance while others did not, the same patient could receive inconsistent care. This design ensures uniform exposure within each period.
- Masking
- None (open label)
- Enrolment
- 260 participants (estimated)
Sponsor and investigators
- Lead sponsor
- Takeoff41, Inc.
- Sponsor type
- Industry (pharma, biotech, devices)
- Collaborators
- Stanford University
- Responsible party
- Sponsor
- Investigators
- David Stevenson, MD, Principal investigator, Stanford University
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT07414576
- Sponsor's protocol ID
- 74413
- Status last verified
- Jan 2026
- First submitted
- 28 Jan 2026
- Last updated
- 17 Feb 2026
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No: Sharing of individual participant data, even de-identified, is subject to approval by the Stanford Privacy Office and Institutional Review Board (IRB), and requests will be considered on a case-by-case basis. General summary statistics of the study population and aggregate results will be shared through peer-reviewed manuscript publication.
Study at a glance
From the registry record, last updated by the sponsor on 17 Feb 2026. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Clinical Decision Support for Total Parenteral Nutrition Constituents in Neonatal Intensive Care Unit (NICU) Patients: A Pilot Study
- ClinicalTrials.gov ID
- NCT07414576
- Acronym / sponsor ID
- 74413
- Conditions
- Intestinal Failure
- Keywords
- parenteral nutrition
- Study type
- Interventional
- Recruitment status
- Recruiting
- Enrolment
- 260 participants (estimated)
- Lead sponsor
- Takeoff41, Inc.Industry (pharma, biotech, devices)
- Collaborators
- Stanford University
- Study start
- 21 Jan 2026 (actual)
- Primary completion
- 21 Feb 2027 (estimated)
- Study completion
- 21 Feb 2027 (estimated)
- First posted
- 17 Feb 2026 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
Detailed description
Our AI-driven TPN (TPN2.0) platform is a combination of AI and a premade set of TPN units. The AI is used to formulate and assign the optimal TPN unit to each infant, given their daily profile and lab test values. It is driven by decades of data, including our published morbidity risks, basic demographics, and routinely collected lab test values. The approach will save staff time and eliminate high errors in the current TPN ordering process.
Our pilot will be deployed as a clinical decision support tool that only makes recommendations, and doctors can always override it. As such, this minimally affects the current practice. We aim to enroll 260 neonates in this pilot study. The primary outcome is physician acceptance rate of TPN2.0 recommendations. Secondary outcomes include time to complete TPN orders, change in weight z-score, days on TPN, lab value abnormalities (values outside normal range), provider satisfaction, and a composite morbidity index comprising rates of bronchopulmonary dysplasia, necrotizing enterocolitis, retinopathy of prematurity, respiratory distress syndrome, congenital heart disease, sepsis, anemia, intraventricular hemorrhage, cholestasis, jaundice, pulmonary hemorrhage, pulmonary hypertension, readmission during the study, and mortality.
Study design
- Primary purpose
- Health services research
- Allocation
- Non-randomised
- Intervention model
- Sequential
- Masking
- None (open label)
- Number of arms
- 2
- Model description
- Single-arm sequential design. Patients (participants) are assigned to one arm based on their admission timing: those admitted during Period 1 (first half of the study) receive care from providers using standard TPN ordering, while those admitted during Period 2 (second half) receive care from providers using AI-assisted ordering. Since the average patient stay is ~14 days, patients are exposed to only one condition. A sequential design is necessary because in the NICUs each patient is cared for by multiple rotating providers depending on the day of the week and shift coverage, making parallel randomization impractical-if some providers had AI assistance while others did not, the same patient could receive inconsistent care. This design ensures uniform exposure within each period.
| Arm | Type | Receives |
|---|---|---|
| Standard TPN Ordering (Control) | No intervention | –Patients admitted during Period 1. Providers use current standard TPN ordering practice without AI assistance. Serves as baseline comparison. |
| AI-driven total parenteral nutrition (TPN) | Experimental | Device: AI-driven total parenteral nutrition (TPN)Patients admitted during Period 2. Providers use the AI-assisted TPN decision support tool integrated with Epic to order TPN. Providers may opt out and use traditional ordering if needed. |
Who may qualify
- Ages
- Up to 6 months
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Child
Key inclusion criteria (4 listed)
- Any newborns or infants requiring total parenteral nutrition in a neonatal ICU that performs daily laboratory tests
- 6-month old at the time of admission
- Any gestational age or birthweight
- Any race or sex
Key exclusion criteria (1 listed)
- Infants deem unfit for the suggested TPN due to safety concerns by physicians
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Interventions
| Intervention | Type | Arms |
|---|---|---|
| AI-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). | Device | AI-driven total parenteral nutrition (TPN) |
Primary outcome
System Acceptance Rate
Time frame: 10 months
Percentage of AI-generated recommendations that are accepted or modified by providers for each ingredient of TPN. Measured by retrospective comparison between AI suggestion and actual TPN order submitted.
4 secondary outcomes
Change in Weight Z-Score
Time frame: 10 months
Days on TPN
Time frame: 10 months
Composite Clinical Outcome
Time frame: 13 months
Rate of Laboratory Value Abnormalities
Time frame: 10 months
Results and safety
This study is still under way. Results are not available in the source record yet.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 17 Feb 2026.
- Individual participant dataSharing planned: No. Sharing of individual participant data, even de-identified, is subject to approval by the Stanford Privacy Office and Institutional Review Board (IRB), and requests will be considered on a case-by-case basis. General summary statistics of the study population and aggregate results will be shared through peer-reviewed manuscript publication.
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part.
David Stevenson, MD principal investigator
Stanford University
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
A study testing AI-driven total parenteral nutrition (TPN) in people with Intestinal Failure, run by Takeoff41, Inc. at 1 site in United States.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: looking for participants now, as of the sponsor's last update on 17 Feb 2026. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in United States. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
This study is still under way. Results are not available in the source record yet.
How can a doctor refer a patient or contact the research team?
Contact Thanaphong Phongpreecha, PhD (551-482-4827, joe@takeoff41.com), or a site near the patient. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
System Acceptance Rate (time frame: 10 months). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 17 Feb 2026.