Peer-reviewed · Hormone Research in Paediatrics 2026

Specialist-grade insulin decisions, in every family's pocket.

DiaBuddy is a point-of-care decision support app for children and adolescents with insulin-treated diabetes. It turns validated paediatric endocrinology algorithms into exact meal doses, basal adjustments and sick-day plans that families can follow at home, between clinic visits.

See the evidence Request clinic access

Developed at Regency Centre for Diabetes, Endocrinology & Research, Kanpur

Can't see the video? Watch it on YouTube

301,000 children and adolescents under 20 in India live with type 1 diabetes (IDF Diabetes Atlas 2025)

6% vs 39% average insulin dose error, DiaBuddy versus families, against a blinded expert

94.5% of families' sick-day errors would have been prevented by following DiaBuddy

+12.6 points in quality of life (PedsQL) over three months, with HbA1c down 0.70 percentage points, in a single-arm pilot

01 · The need

A child with type 1 diabetes needs several insulin decisions a day. The specialist is there a few times a year.

In India, families make almost every one of those decisions alone: how much insulin for this meal, whether to change tonight's dose, what to do when the child is vomiting. Diabetes educators are scarce, clinic visits are months apart and many families live hours from a paediatric endocrinologist. Errors lead to hypoglycaemia, ketoacidosis and admissions that could have been avoided.

39% Average error in families' insulin doses Across 730 dosing decisions by 37 families, 57% of doses fell outside a ±20% safety margin.

52% Of sick-day decisions made wrongly 1,532 errors in 2,960 decisions, including 30% of choices about whether the child needed hospital.

22% Of families count carbohydrates regularly Those who did made smaller bolus errors and reported fewer ketosis episodes. Most need the arithmetic done for them.

Family figures: DiaBuddy preclinical validation, 37 families, 20 dosing and 20 sick-day vignettes each (Hormone Research in Paediatrics, 2026).

02 · What DiaBuddy does

The clinic's dosing logic, set up once by the care team and used by the family every day.

At enrolment the team enters the child's regimen, insulin types, doses and honeymoon status. DiaBuddy derives the insulin-to-carbohydrate ratio and sensitivity factor and applies ISPAD 2022-anchored rules to every decision after that.

HomeDosing, sick days, glucose and meals in one place
Indian mealsTwo rotis, rice, dal and raita: carbohydrates counted for you
Meal dosePre-meal sugar plus the meal gives the dose
Sick dayGlucose, ketones and symptoms decide home care or hospital

Meal bolus calculator

Combines pre-meal glucose with the meal's carbohydrate content to give an exact dose, with a clinician-adjustable target.

CarbCal Indian food database

10,245 foods, including regional Indian dishes, so families can count carbohydrates for the meals they actually eat.

Basal titration

Adjusts long-acting insulin from fasting glucose using graded multipliers, from 0.8× when low to 1.2× when high.

Correction with insulin on board

Corrects post-meal highs while subtracting insulin still active from earlier doses, so corrections don't stack into a hypo.

Sick-day guide

Takes symptoms, glucose and ketones and returns a full plan: whether to go to hospital, dose changes, extra insulin, and the type and volume of fluids.

Tracking, lifestyle and education

Sugar Tracker logs glucose with alerts; EatRite, PlayRite and SleepRite cover meals, activity and sleep; the Knowledge Base holds family education. Clinics can review the readings and doses families share.

STEP 1 The care team sets up the child's profile Regimen, doses and targets entered in clinic; ratios calculated automatically.

STEP 2 The family asks DiaBuddy at each decision Meals, high readings, illness: an exact, guideline-aligned answer in seconds.

STEP 3 Red flags go straight to the hospital Signs of ketoacidosis, blood ketones above 3.0 mmol/L or urine ketones 3–4+ trigger hospital referral instead of home management.

Available today as an Android app, installed under clinician supervision for about 50 families at the Regency clinic and free of charge to them. It is not yet in app stores; Play Store, iOS and Indian-language versions are on the roadmap below.

03 · Evidence

Peer-reviewed in two phases: accuracy on paper, then outcomes in children.

First page of the article, showing the title, authors and abstract

Original article · Hormone Research in Paediatrics · 2026 Development and Pilot Clinical Evaluation of DiaBuddy: A Point-of-Care Decision Support Tool for Children and Adolescents With Insulin-Treated Diabetes Mahapatra A, Paimode S, Banerjee S, Shukla P, Sachan N, Yadav V, Bajpai A. Horm Res Paediatr. Published online October 2026. DOI 10.1159/hrp/adaag032 · PMID 42821504 Read the paper

PHASE 1 · PRECLINICAL VALIDATION

DiaBuddy against 37 families and a blinded expert

Each family answered 20 dosing and 20 sick-day vignettes. An independent paediatric endocrinologist from another institution (PGIMER Chandigarh), blind to both, set the gold standard.

Average dose error versus the expert (lower is better)

Basal

5.0% DiaBuddy

24.2% families

Bolus

6.9% DiaBuddy

45.3% families

All doses

6.3% DiaBuddy

39.0% families

All comparisons P < 0.001. Absolute relative deviation from the gold-standard dose.

Sick-day management

DiaBuddy was at least 90% accurate in every domain. Families erred on 30% of hospital decisions, 74% of dose changes, 68% of extra-insulin doses and 35% of fluid choices. Following DiaBuddy would have prevented 94.5% of these errors, including every wrong hospital decision.

PHASE 2 · PILOT CLINICAL STUDY

Three months of use by 20 children, aged 5 to 18

Prospective single-arm pilot at Regency CDER, Kanpur. 65% of the children had ketoacidosis at diagnosis.

HbA1c 9.18 → 8.48% −0.70 points, P = 0.049; 55% fell by ≥0.5

Quality of life (PedsQL) 76.5 → 89.1 +12.6 points, P < 0.001

Family satisfaction 44.1 / 50 most families wished to keep using it

Time in range (CGM) 41.6 → 43.5% not significant at 3 months

A small, uncontrolled pilot. CGM metrics did not change, and without a control group the HbA1c and quality-of-life changes cannot be attributed to DiaBuddy alone. We report them as hypothesis-generating, to be tested in the multicentre randomised trial below.

04 · Key observations

What we learned

Experience is not enough Families who had managed diabetes for years still got about half of sick-day decisions wrong. The gap is arithmetic and rules, not motivation.
The biggest gains are in the riskiest moments DiaBuddy would have corrected every wrong decision about going to hospital, the error most likely to end in ketoacidosis.
Families feel the difference first Quality of life improved in 19 of 20 children within three months, while CGM metrics did not change: an early signal for the trial to test.
Built for Indian kitchens Only 22% of families counted carbohydrates regularly. A database of 10,245 foods in familiar portions, with the dose arithmetic done for them, is designed to close that gap.

05 · Future plan

From one clinic to every family that needs it

DONE · 2026

Algorithms validated against families and expert
Pilot outcomes published in HRP
AI companion MedEDiabuddy validated and presented at APPES 2026

NEXT · 6 MONTHS

MedEDiabuddy chat built into the DiaBuddy app
Google Play release
Hindi interface, then other Indian languages
Copyright and trademark protection

2027 · TRIAL

Five-centre randomised trial of DiaBuddy with MedEDiabuddy
ICMR ANVESHAN funding application submitted
Trial designed as regulatory evidence for CDSCO software-as-medical-device review

SCALE

iOS and offline mode for low-connectivity areas
Core dosing and sick-day support kept free or subsidised for families; clinic and state programme contracts
Adaptation for countries with similar diets and care gaps

Help us reach more families: we are looking for partners in state diabetes programmes, insulin-access charities and health-AI governance, and support for the iOS build, Indian languages and the trial. Partner with us

06 · Developers

Built by the clinicians who use it

Dr Anurag Bajpai

Co-developer and principal investigator · FRACP

Consultant Paediatric and Adolescent Endocrinologist at Regency Centre for Diabetes, Endocrinology & Research, Kanpur, and President of the Indian Society for Pediatric and Adolescent Endocrinology (ISPAE) 2025–26. Trained at AIIMS New Delhi and the Royal Children's Hospital, Melbourne.

Founder of MedEClasses Private Limited (2018, DPIIT-recognised) and the GROW Society; leads a two-year hybrid paediatric endocrinology fellowship with 180 doctors enrolled, including 30 medical college faculty
MedEClasses courses have reached more than 1,700 health professionals in over 50 countries
Series Editor, Advanced Pediatric Endocrinology; Section Editor, Indian Journal of Pediatrics
h-index about 24, more than 1,800 citations; developer of a suite of validated decision-support tools for paediatric endocrinology

Development and research team