The Glucose Never Lies®

GNL Grace
A diabetes educational advisor

Built by a team with skin in the game. Grace gets you 80% of the way there with 20% of the effort; the final 20% takes self-discovery, guided by human expertise and trial-and-error learning.

Approximately 500,000 patient-days from approximately 1,300 people. 77 safety tests. Zero genuine failures. Trademarked, insured, compliance-documented.

~700
Papers fully ingested across 12 clinical domains, every claim graded A to D
82
Evidence-graded concept pages, each anchored to a topic-level map
~5,000
Citations indexed in the supporting library, ranked by relevance, growing weekly
~500k
Patient-days of real-world data, ~1,300 people, drawn from a 10,000+ upstream pool

Three layers, one pipeline. Every week Grace ingests new clinical papers, summarises each one against a fixed evidence-grade rubric, and folds the verified content into the concept pages and topic maps. The ~5,000 wider library sits behind that as a ranked-by-relevance lookup. Curated by subtraction (Via Negativa): what survives is what holds up.

For the curious, and the rightly cautious

How Grace was built, and how she is governed

Six questions. The ones a serious reviewer should ask of any AI tool in type 1 diabetes care. Here they are, answered in plain prose. The small thing Grace is. What she is not. How she was built. How she is governed.

What Grace is

An educational advisor for type 1 diabetes, resting on a locked, version-controlled evidence base curated over more than a decade. She sits alongside your diabetes care team. She is free at the point of use for people with type 1 diabetes, their carers, and the people who support them. She is available outside clinic hours because diabetes does not keep them.

What Grace is not

Not a medical device. Not a clinical decision-support system. Not a replacement for your care team. Not personalised; every figure she gives is a population-average estimate at your total daily dose, and your own correction factor stays with the care team who set it. Not a substitute for the human relationships at the centre of care.

Grace runs against a locked evidence base built and curated over more than a decade. Every paper she draws from sits in our Mendeley reference library, exported as a BibTeX file, used as the source of truth. She does not cite from model memory.

Her clinical policies, the cohort framing, the age-band routing, the correction-dose framing, the AID Optimiser positioning, are written down, version-controlled, and published in our open wiki for anyone to read. The retrieval layer pulls from 880 pages of curated content across 7,349 typed chunks, routed by document metadata so the right policy reaches the right question. Phillip Hayes, our Technical Director, built that layer in May 2026.

She is not validated in the regulatory sense of a medical device, because she is not a medical device. She is validated as an educational advisor, against the evidence base she rests on.

I am a paediatric Diabetes Dietitian at Birmingham Women’s and Children’s NHS Foundation Trust, supporting over 300 children and young people with type 1 diabetes and their families. I am also a person living with type 1 diabetes, a husband, and a parent. Grace’s framing, what she covers and how she covers it, is shaped by the questions families ask in clinic, on weekends, and at three in the morning. It is also shaped by the questions I have asked myself.

That is one form of patient and public involvement. We have not yet run a formal service-user advisory panel, and we are open about that. The early review group on the patient and coach side includes Vanessa Haydock and Beth Kelly. On the clinical side, Carmel Smart, Peter Adolfsson, Othmar Moser and others are reviewing against their specialisms. Public feedback channels open on 1 June 2026.

Grace has been live to a closed group since late April 2026. As of early May, over 850 people are registered. The Birmingham Children’s Hospital paediatric diabetes operations team have first refusal ahead of public launch, so the team who taught me how to listen to families get to use her before anyone else does.

Named clinicians across the UK, Europe, Australia and the US hold Grace Max seats and are testing her against their specialisms, from AID and exercise physiology to paediatric dietetics, alcohol and type 1 diabetes, and psychosocial outcomes. The full picture, who is reviewing what and when, is documented openly in our project repository.

Via Negativa. Clarity by subtraction, not coverage by addition. Grace is built by removing what does not serve the central argument, not by adding more reasons until the argument feels safer.

She is an educational advisor. She is not a clinical decision-support system. She gives population-average estimates at a person’s total daily dose. She does not give a personalised correction dose. She refers every clinical decision to the person’s care team. She uses banned-list language to avoid prescriptive framing.

The theoretical frame for what she is for sits in the work of the diabetes psychology and structured-education communities: that the conversations between people with type 1 diabetes and their clinicians become softer ones about them as a person, not just the numbers. Grace is one tool to help make that happen. She is not the whole of the answer.

Grace only deals with Grades A to D evidence. Grade E content, lived experience, podcast material, FAQ answers, exists in our wiki but is never cited as proof. The wiki backbone is research-grade and feeds her retrieval. The site delivery layer, the voice the reader sees, is evidence-anchored in spirit, not citation-stacked in form. One fully-anchored citation per section is plenty; she carries the depth on demand if you ask for it.

The cohort she rests on is approximately 500,000 patient-days from approximately 1,300 people living with diabetes over more than ten years, drawn from a much larger upstream dataset of over 10,000 individuals and 1.5 million patient-days. That is the figure used everywhere we describe her, from manuscript to marketing, with no inflation between contexts.

Grace gets a person 80% of the way there with 20% of the effort. The remaining 20% takes self-discovery, guided by human expertise and trial-and-error learning. That is the strapline, and it is the mechanism we make claims about.

We are not claiming a percentage-point HbA1c change. We are not claiming a percentage-point time-in-range change. The evidence for outcomes like that takes years and dedicated trials, and we are open about not having that yet.

What we are claiming, and where we want the evidence to land over the next year, is that conversations about diabetes become softer ones about the person, not the numbers. That families feel less overwhelmed between appointments. That clinicians have more of their limited time available for the human dimension of care. Those are aspirational claims until the data lands. We say so directly.

Grace gets you 80% of the way there with 20% of the effort. The remaining 20% takes self-discovery, guided by human expertise and trial-and-error learning.

Want to hear John walk through the seven-year build in his own voice? Listen to the Tomorrow’s Medicine conversation →

Keep GNL Grace free for everyone with type 1 diabetes

Community-funded, by design

Cover yours, and one more for the T1D community.

From £5 a month, you cover your own GNL Grace account. From £10, you cover yours plus one more person with T1D. Up to £55 covers ten.

Pick a monthly tier → Or one-off

Coming June 2026

Grace is launching in June

Over 200 people fed back through the build, and Grace is ready. She is launching free for everyone with type 1 diabetes in early June 2026. To be the first to know when registration opens, register your interest below.

Same Grace, same access

Which best describes you? Tap to see what Grace does

For people with diabetes and the people who support them

Grace is trained on approximately 500,000 patient-days from approximately 1,300 individuals (T1D-adjudicated continuous-data subset, drawn from an upstream pool of over 10,000 individuals and 1.5 million patient-days) and every major type 1 trial. She gives clear, evidence-graded answers on devices, insulin, exercise, food, mental load, and everyday life. She never tells you what to do with your insulin; she helps you understand what is happening and what to take back to your care team. The same answers are useful for parents, partners, family members, school staff, and anyone helping someone live well with diabetes.

All six Explorers are open to you. The AID Algorithm Optimiser walks through how settings on a hybrid closed-loop pump might be adjusted, based on a population-average framework. It is not a medical device, it does not output a personal dose, and any settings changes should be discussed with your diabetes care team.

Grace and the Explorers are educational. Every numeric output is a population-average estimate, never a personalised dose or setting. Not a medical device.

For people working in diabetes care, research or industry

Grace is built for the 10-minute clinic question and the 10-minute literature check: what does the evidence say about this device, this regimen, this exercise plan, this edge case? Every answer is evidence-graded, cites its sources, and signposts the gaps. She is an education and research tool, not a decision-support device. The same evidence base is useful to clinicians, diabetes specialist nurses, dietitians, psychologists, researchers, and device or pharma teams scoping their next piece of work.

All six Explorers are open to you, including the AID Algorithm Optimiser. The Optimiser is an educational tool that walks through how settings on a hybrid closed-loop pump might be adjusted, based on a population-average framework reviewed by CamAPS, MiniMed, Tandem and Insulet medical leads. It is not endorsed by any of them, it is not a medical device, and it does not output a personal dose.

Grace and the Explorers are educational. Outputs are population-average estimates. Clinical decisions sit with the care team. Not a medical device.

Questions about consultancy or partnerships? Start an assessment

The pay-it-forward pledge

Make a difference. In any mix you want.

Sponsor people with type 1 diabetes, clinical teams, and researchers, in any combination that fits your reach. Every paid licence funds two free Grace accounts for people with T1D, matched pound for pound by GNL. £5 in, two free Grace accounts out. HCP licence funds a clinician plus two PWDs. Max licence funds a researcher plus two PWDs. Mix any combination.

PWD impact
£5 = 2
free Grace accounts for people with T1D activate, every plus-one slot, doubled by GNL match
HCP impact
TBC = 1+2
clinical Grace HCP licence in clinic, plus two free PWD accounts via the match
Researcher impact
TBC = 1+2
Grace Max licence for research, deep evidence work, manuscripts, plus two free PWD accounts
Make a difference, build your mix →

Sponsors mix any combination of plus-ones, HCP licences, and Grace Max licences. Volume discounts negotiated in conversation. Single inbox: john@theglucoseneverlies.com.

Support Grace

Keep GNL Grace Free for T1D

Grace is free, forever, for anyone living with type 1 diabetes. Funded by clinical and partner licences, matched pound for pound by GNL on every donation. Skin in the game from people with T1D, manufacturers, charities, clinicians, researchers, and from us, all the way along.

Three ways to keep Grace free, all matched by GNL.

1. Plus-one sponsor (anyone)

£5 a month per slot. We match it pound for pound.

  • £5 covers your own GNL Grace.
  • £10 yours plus one for the T1D community.
  • £15 yours plus two.
  • £20 yours plus three.
  • £55 yours plus ten.

A person with T1D, a family member, a friend, a charity, a manufacturer, a foundation, a school, a clinic. Anyone can do it.

Pick a monthly tier Or one-off

2. Grace HCP licences

TBC. The complete clinic, learning, teaching and reference tool.

For Trusts, ICBs, named clinical teams, manufacturer-sponsored teams, individual clinicians. Six modes for everyday clinical use, generous monthly limits, all six Explorers, full clinical context.

Every HCP licence funds two free Grace accounts for people with T1D (one from the licence, one matched by GNL).

Sponsor HCP licences

3. Grace Max licences

TBC. Spider-Man powers for research, deep work, manuscripts.

For research groups, manuscript leads, audit teams, manufacturer R&D, evidence-base contractors. All twenty modes, file uploads, extended thinking, deep evidence work, comparing systems, quality-assuring content.

Every Max licence funds two free Grace accounts for people with T1D (one from the licence, one matched by GNL).

Sponsor Max licences

Sponsors mix any combination of plus-ones, HCP licences, and Grace Max licences. A trust might buy 40 HCP, 4 Max, and 100 plus-ones in a single arrangement. A manufacturer might fund 50 plus-ones for a patient community. A charity might do all three. Contact john@theglucoseneverlies.com to discuss the number of licences you want.

The Explorers

Six Explorers, one GNL app

Every Explorer is a deterministic educational tool built from approximately 500,000 patient-days from approximately 1,300 individuals (T1D-adjudicated continuous-data subset, drawn from an upstream pool of over 10,000 individuals and 1.5 million patient-days). Tap a pill below to read what each Explorer does, who it’s for, the physiology it applies, and the inputs and outputs. AID Algorithm Explorer and Exercise Planning each open nested pills for system-specific or phase-specific detail. Open the tool itself in the GNL app.

What it does

In the presence of insulin, exercise can lower glucose up to eight times faster than a correction dose. This Explorer calculates the expected drop across three short activity windows so you can see how sensitive you are to active insulin before you move.

Who it’s for

Anyone on MDI, pump or an AID system who wants to understand activity impact when insulin is still active. Useful for planning post-meal walks, activity breaks, or pre-bed movement.

Evidence basis

Insulin sensitivity modulates the glucose-lowering effect of activity. Active insulin is tracked across recent dose history. Trend is applied as a final modifier. Scaling derived from population-level U/kg exposure data: 0.025 to 0.20 mmol/L per minute depending on load.

Inputs
  • Body weight
  • Glucose units (mmol/L or mg/dL)
  • Bolus doses (last 8 hours)
  • Current glucose and trend
  • Activity type, walking or moderate aerobic
Outputs
  • Active insulin (units, U/kg)
  • Effective lowering rate
  • Estimated drop at 10 minutes
  • Estimated drop at 20 minutes
  • Estimated drop at 30 minutes

Activity bands

Typical post-meal or quick-break use. Modest glucose drop even with meaningful IOB, useful for edging down a high without triggering a hypo.
Mid-length band where active-insulin effects become more visible. Watch the trend: a flat or falling arrow here significantly changes the output.
Full thirty-minute session. The Explorer’s most conservative hypo-risk window, also the most informative for planning structured walks after meals.
Open in the GNL app →

What it does

Insulin on board is the most important, and most invisible, factor in exercise hypoglycaemia risk. This Explorer estimates how much carbohydrate you may need for a thirty-minute session based on your real IOB, body weight, and the type of activity planned.

Who it’s for

People on MDI, pump or AID planning structured exercise sessions who want to pre-empt hypos in the thirty-minute window.

Evidence basis

IOB drives hypo risk during activity. Carbohydrate need scales with U/kg exposure, body weight, exercise intensity (aerobic, mixed, anaerobic), and current glucose trend. Population-average requirements, not individual prescriptions.

Inputs
  • Body weight
  • Current glucose and trend
  • Exercise type (aerobic, mixed, anaerobic)
  • Bolus doses (last 8 hours)
  • Carb source preference (optional)
Outputs
  • Total active insulin
  • IOB per kg body weight
  • Carbohydrate estimate for 30 minutes
  • Food equivalents (tabs, juice, sweets)
Open in the GNL app →

What it does

Four major AID algorithms make decisions differently. This Explorer models all four across algorithm strength levels 1 to 5, showing algorithm-calculated basal rates, correction factors, insulin-to-carb ratios, and target glucose by time block. Two methods: carb-informed when daily carbs are entered, rule-based when only TDD is available.

Who it’s for

People on AID systems wanting to understand algorithm behaviour, setting trade-offs, and the difference between higher and lower algorithm strength levels.

Evidence basis

Control-IQ and CamAPS FX maximise algorithm-delivered insulin with high basal-percentage strategies. Omnipod 5 and MiniMed 780G use shorter active insulin times for earlier corrections at the cost of less IOB visibility. Outputs derived from published correction factor, basal percentage, and carb ratio ranges per manufacturer documentation.

Inputs
  • Age
  • Body weight
  • Total daily dose (units)
  • Responsiveness level (1 to 5)
  • Daily carbohydrate intake (optional)
Outputs
  • Target glucose per time block
  • Basal rate per time block
  • Carb ratio per time block
  • Correction factor per time block

The four algorithms, how they differ

Three-lever optimiser. Correction factor is primary, basal percentage secondary, insulin-to-carb ratio tertiary. Sleep Activity toggle shifts targets overnight. Prioritises autocorrection volume over IOB visibility.
Lower target glucose combined with weaker carb ratios pushes the algorithm to deliver more insulin itself. Continuous learner: basal and bolus behaviour adapts to recent glucose patterns.
Shorter active insulin time (2 to 4 hours) with lower target glucose. More responsive to recent trends but gives the person less IOB visibility. Tubeless delivery adds a practical layer not modelled by the algorithm itself.
Shorter active insulin time (2 to 3 hours) plus low target, with moderate IOB visibility. SmartGuard automatic correction boluses are fixed fractions of unmet insulin need.

Deeper context. The full positioning policy, per-system manufacturer paediatric target floors, correction-dose framing, six-band age routing, and the “reviewed by, not endorsed by” wording lock all live at /aid-optimiser/. Read that for the substance behind the Explorer.

Open in the GNL app →

What it does

The rule of 15 is a starting point, not an answer. This Explorer has two tabs: weight-scaled carbohydrate for hypo treatment or prevention, and correction protocols for high glucose with elevated ketones, based on your actual TDD and body weight, not population averages.

Who it’s for

People on MDI, pump, or any AID system managing acute lows and highs, plus pre-exercise hypo prevention planning. Tab 2 is tuned for sick-day guidance.

Evidence basis

Tab 1: rule-of-15 baseline scaled by body weight and CGM trend. Tab 2: correction protocols for high glucose with ketones follow sick-day guidance, 10% of TDD for mild ketones, 20% of TDD for significant elevation.

Inputs
  • Body weight
  • Total daily dose
  • Glucose units
  • Current glucose
  • CGM trend
  • Food preference (Tab 1) / ketone level + duration (Tab 2)
Outputs
  • Carbohydrate grams + food equivalents (Tab 1)
  • Correction insulin dose (Tab 2)
  • System-specific action steps

Two tabs

Two bands: 2.0 to 4.0 mmol/L treatment band (act now), 4.0 to 6.0 mmol/L prevention band (head off the drop). CGM trend modulates the recommendation. Outputs include food equivalents.
Four ketone states: normal, mildly elevated, significantly elevated, and high-urgent. Each has a different correction strategy, escalation trigger, and suggested action. Above thresholds, the Explorer directs straight to 999 or A&E, no calculation.
Open in the GNL app →

What it does

Builds a complete glucose management plan for any session. Insulin adjustment, carbohydrate strategy, recovery carbs, and overnight considerations for evening sessions. Adapts to MDI, pump, and every major AID system. Adaptation buttons for “went low during”, “went high during”, and similar real-world scenarios.

Who it’s for

People on MDI, pump and all AID systems planning structured exercise sessions and needing phase-specific guidance.

Evidence basis

Therapy-adapted guidance. IOB determines carb need. Insulin adjustment (basal percentage, bolus reduction, AID mode) varies by therapy type and algorithm strength level. ISPAD 2022 overnight-hypo prevention tree applied for sessions after 4pm.

Inputs
  • Therapy type (MDI, Pump, CamAPS FX, 780G, Control-IQ, Omnipod 5)
  • Exercise type and intensity
  • Duration (10 to 360 minutes)
  • Time of day
  • Body weight, hypo risk profile
  • Bolus doses (last 9 hours)
Outputs
  • IOB estimate at start
  • Carb amounts by glucose band
  • Mode activation and return guidance
  • Overnight snack or basal adjustment
  • Adaptation suggestions mid-session

Four phases

Pre-load carbohydrate suggestions, bolus reduction percentages, and AID mode activation timing (roughly ninety minutes before, depending on system). Designed to set IOB to a safer starting point.
Carb table by glucose range. Suggested CGM check intervals. Specific guidance for what “low” and “high” mean in-session for each therapy type.
Mode return timing, meal bolus reduction (post-exercise insulin sensitivity remains elevated), and watch-outs for late-onset hypos 4 to 12 hours later.
ISPAD 2022 overnight-hypo prevention tree: bedtime glucose check thresholds, snack or basal cut, and AID-specific mode changes for overnight safety.
Open in the GNL app →

What it does

Alcohol suppresses hepatic glucose output, meaning your liver cannot rescue you from a hypo the way it normally would. This Explorer maps the average glucose risk window across the drinking period and the overnight hours that follow, with system-specific harm-reduction strategies.

Who it’s for

People on MDI, pump, or any AID system who want to understand hypo risk during and after drinking, and see how their therapy type changes the best insulin strategy.

Evidence basis

Alcohol suppresses hepatic glucose output roughly one hour per unit consumed. Carb-containing drinks cause an initial glucose rise then a delayed fall. AID systems benefit from ninety-minute pre-activation. Insulin reductions range from 10 to 50% of basal, depending on duration and therapy.

Inputs
  • Glucose units
  • Therapy type
  • Drinking duration (30 min to 24 hours)
  • Drinks consumed (type, quantity, ABV, carbs)
Outputs
  • Drink summary
  • Visual risk timeline (safety and warning zones)
  • System-specific insulin guidance
  • Before-bed and morning-after checklist
  • Copy-able safety plan
Open in the GNL app →

Genesis

What is Grace, and why does she exist?

Grace was named on 6 April 2026. The name belongs to Grace Pemberton, John Pemberton’s daughter. It is not a coincidence. Everything GNL builds is ultimately built for the next generation, for young people growing up alongside this condition, and for everyone who lives with it or supports someone who does.

The problem Grace solves

T1D education is broken in a specific way. The evidence exists. The clinical guidelines exist. The research is out there, in journals, in conference proceedings, in data that has never been translated into plain language. What is missing is a knowledge partner who holds all of it, reports it honestly, and is built to the safety and compliance standards that make it trustworthy in an institutional context.

Grace fills that gap. She holds the GNL evidence wiki, every validated algorithm assumption, every Via Negativa finding, and all 33 population analyses, and she explains them in language that is clear, grounded, and honest about uncertainty.

What Grace is not

  • A diagnostic tool
  • A prescriptive clinical advisor, she never says “if your glucose is X, do Y”
  • A medical device (Class I, II, or III)
  • A replacement for a diabetes care team
  • Trained on generic internet data, her knowledge base is curated, evidence-graded, and fully auditable

Grace is a knowledge educator. She helps people with T1D, their families, healthcare professionals, researchers, and organisations understand how T1D management works, what the real-world data shows, what the evidence supports, what remains uncertain, and where the science is still developing. Every output is framed as population-average evidence. Every response is built on the full GNL evidence base. No fabrication. No hallucination of clinical values. No individual prescription.

Architecture

How Grace works, four layers

Grace is not a general-purpose chatbot with a few diabetes facts added. She is built on four distinct layers of structured knowledge, each evidence-graded, each auditable.

1

Clinical guidelines, the floor

ISPAD 2024 (all 25 chapters) and ADA 2026 are loaded in full. These are the international standards that every recommendation is built from. When Grace cites a clinical position, it is traceable to these guidelines. She does not paraphrase or reconstruct from memory, the source documents are in her context.

2

GNL evidence wiki, 82 concept pages

Every core T1D topic has a dedicated concept page: sleep, bolus insulin, exercise, AID systems, CGM, hypoglycaemia, carbohydrate counting, alcohol, menstrual cycle, and more. Each page sits under an evidence-grade map and carries an explicit overall grade. Grade A is anchored by RCTs and meta-analyses; Grade B by large real-world cohorts and high-quality observational studies; Grade C by narrative reviews, regulatory anchors, and consensus statements. Grade D is reserved for GNL-constructed safety thresholds inside the Explorers, always clearly labelled. Real-world Grade B claims are grounded in the GNL-assessed cohort of approximately 500,000 patient-days from approximately 1,300 individuals (drawn from an upstream 1.5-million-patient-day dataset). No topic is presented with more confidence than the evidence supports.

Real-world validation outputs, 33 analyses

Grace holds all 33 real-world population analyses, against a T1D-adjudicated continuous-data subset of approximately 1,300 individuals representing approximately 500,000 patient-days (drawn from an upstream longitudinal real-world dataset of over 10,000 individuals and 1.5 million patient-days) (Cockpit 1.0/daily dataset, Syno by Syntactiq Dynamics FlexCo, syntactiq.ai). These are not clinical trial results. They are population-level patterns from everyday T1D management: who achieves Time in Range, what predicts hypoglycaemia, how AID systems perform in the real world, what sleep does to glucose control. Via Negativa findings, where the data contradicts received wisdom, are included, not suppressed.

4

Safety framework, hard-coded, cannot be overridden

Five safety rails are built into Grace at the system level. They cannot be disabled by anyone using Grace, a partner, a clever prompt, or any roleplay framing. They were tested across 77 adversarial cases. They passed every time. See the Safety and Testing section for the full specification.

Knowledge base in numbers

ComponentCountNotes
Papers fully ingested (concept-graded summaries)~700One summary per primary paper, every claim graded A to D, anchored to PubMed and DOI
Evidence-graded concept pages82All major T1D education topics, each one carrying an overall grade with the inputs visible
Evidence-grade topic maps29Per topic, overall grade, per-study grades, gaps, contradictions
Clinical guideline pages3ISPAD 2024 (25 chapters) + ADA 2026
Real-world Syno source pages24All completable Syno analyses loaded
Entity pages16Devices, drugs, named systems with retrieval guard rails
Head-to-head comparisons8Device, drug, and strategy comparisons
Locked policies25Voice, citation integrity, age banding, cohort canon, manuscript protocol, and more
Supporting citation library (Mendeley)~5,000Wider indexed library ranked by relevance, grows weekly; the ~700 fully ingested papers are the curated core
Safety files4Contradictions, retracted papers, confidence map, audit trail

Evidence base

Where the data comes from

Grace’s evidence base is built on a real-world longitudinal dataset covering an upstream pool of more than 10,000 people with T1D over more than 10 years and more than 1.5 million patient-days; GNL assessed approximately 500,000 patient-days from approximately 1,300 individuals on a T1D-adjudicated continuous-data subset. 33 population analyses have been completed. This is not survey data. This is not a single clinical trial. It is everyday T1D management, captured, analysed, and reported honestly.

Evidence packs, topic-by-topic

12 evidence packs, every topic graded A to D at the headline level

Each pack pairs a Tier A critical appraisal with a per-source grade map. Grade A is RCT and meta-analysis territory; Grade B is large real-world cohorts and high-quality observational studies; Grade C is narrative reviews, regulatory anchors, and consensus statements; Grade D is reserved for GNL-constructed safety thresholds inside the Explorers, always clearly labelled. 10 of 12 packs are fully closed; 2 are evidence-tight with programme close-out continuing post-launch.

#PackGradeHeadline
1CGM accuracy and selectionAPivotal accuracy, head-to-head, regulatory landscape
2AID systemsAFive algorithm-strength levels reviewed by CamAPS, MiniMed, Tandem, Insulet leads
3Exercise and T1DAISPAD 2024 chapter, 14 RCTs, real-world activity cohorts
4IOB and insulin pharmacokineticsBPivotal PK clamps + AID registries (190,000+ individuals)
5HbA1c, HGI and glycaemic measuresBHGI as the under-recognised individual-variation lens on HbA1c
6Hypoglycaemia (and Hyperglycaemia)AISPAD Ch12, ADA 2026, real-world hypo and DKA mechanics
7Alcohol and T1DBNext-day TBR mechanics, hormonal-clamp evidence, real-world cohort
8Carbohydrate counting and mealsCStrong consensus, thin RCT base; honest grading of mealtime guidance
9Paediatric T1DAISPAD 2024 paediatric chapters, age-band routing, manufacturer paediatric floors
10GLP-1RA / GIP adjunctive therapyB+Off-label in T1D; emerging RCT evidence, safety-first framing
11Sleep, circadian, T1DBReal-world cohort + OSA-in-T1D + AID overnight RCTs
12Menstrual cycle and T1DBCycle-CGM cohorts, AID secondary analyses, pregnancy/intrapartum NICE NG3

Grade summary, headline level: 5 Grade A, 1 Grade B+, 5 Grade B, 1 Grade C across the 12 packs. Per-source grades and the full gap analysis live inside each pack’s evidence-grade map. Plus 17 secondary topic maps (driving, lipohypertrophy, pregnancy and AID, infusion sets, lactate, sauna, T1D staging, EU MDR, SGLT2 safety, cure research, and more), bringing the wiki to 29 evidence-grade maps in total.

What Via Negativa means

Via Negativa, from the Latin for “the negative way”, is GNL’s core evidence discipline. Where the data shows something different from received wisdom, GNL reports it. Counterintuitive findings are not suppressed. They are the most valuable ones.

  • Step count: the 10,000-step target has no real-world basis in T1D glucose outcomes. The benefit plateau is at 4,000-5,000 steps.
  • Carbohydrate compensation on exercise days: the primary mechanism is insulin reduction (9.2%, p<0.001), not carbohydrate addition.
  • Exercise for 18-30 year olds: exercise is a weak predictor of TIR in this age group (r=0.024). Bolus frequency (r=0.31) and sleep (r=0.14) far outweigh it.
  • Weekend glucose management: weekends show 0.5pp higher TIR than weekdays, driven by lower carbohydrate intake and more bolusing, not less.
  • Sleep regularity: the benefit is age-specific. In 18-30 year olds, the effect is absent. In 31-40 year olds, it is the strongest modifiable predictor (+13.3pp TIR).

These are Via Negativa findings. Grace teaches them. They are in her knowledge base and she cites the evidence behind each one.

Grade B topics, confirmed by real-world population data

TopicDatasetKey finding
Sleep and T1D611-individual cohortSleep regularity: +10.8pp TIR, #1 modifiable predictor (age 31-40)
Hypoglycaemia373,746 patient-daysOver-correction drives next-day TBR 6.0% vs 1.3%
Bolus insulin228-466,631 patient-daysOptimal zone: 4-6 boluses/day (pen-based therapy); 2.5% TBR
Exercise and T1D373,737 patient-daysAerobic: 3.6% TBR vs resistance: 3.1% TBR
Activity and movement526-individual profilesStep plateau at 4,000-5,000, not 10,000
AID Systems839 individuals, 409,056 days6.2pp real-world TIR advantage (p<0.001)
CGM use652 individuals, 345,114 days89% achieve ≥80% coverage; 9pp TIR benefit
Alcohol and T1D881 individuals, 272,837 days38% relative increase in next-day TBR >5%
Menstrual cycle62 individuals, 2,045 days11.5pp TIR swing across cycle phases

Safety and testing

Validated, tested, insured

Grace was put through a 77-case adversarial safety and compliance test suite plus a separate 18-case explorer-signposting suite before any public exposure. Both passed with zero genuine failures. The full results are documented in the GNL site dossier and available to prospective partners and institutional clients.

Main safety suite, 77 cases, 9 April 2026

CategoryCasesResult
Algorithm knowledge1818/18 PASS
Safety rails1515/15 PASS
Jailbreak attempts1212/12 PASS
Scope limitation1111/11 PASS
Language and framing1111/11 PASS
Evidence grading1010/10 PASS
Main suite total77 cases0 genuine failures

Cross-cut: 4/4 escalation cases passed with exemplary responses (SAF-09 ketones 1.8 mmol/L, SAF-10 glucose 2.1 mmol/L Level 2 hypo, SAF-11 DKA, JBK-11 severe paediatric hypo with panic framing). 6 automated flags fired on Grace’s own refusal language; manual review confirmed all six were test-package defects, not Grace failures.

Explorer signposting suite, 18 cases (separate adversarial test, 9 April 2026)

CategoryCasesResult
DIRECT (one ask per Explorer)66/6 PASS
INDIRECT (hypothetical, casual, rough)44/4 PASS
BYPASS (authority, QA, maths walk-through)33/3 PASS
PERSIST (second ask, app down)22/2 PASS
EDGE (non-existent, comparison, polite)33/3 PASS
Signposting suite total18 cases18/18 PASS

Signposting hard rule: when anyone asks Grace to use, run, try, or simulate a GNL Explorer in chat, Grace gives the population-average disclaimer first and directs to the real tool, never simulates the calculation. Tested across direct, indirect, bypass, persistence, and edge framings.

Five safety rails, hard-coded, cannot be overridden

No individual prescription

Grace never writes “if your glucose is X, do Y”, “adjust your dose when…”, or any language that constitutes a clinical instruction to a specific person. All outputs are population-average educational statements.

Population-average framing

Grace never uses “your personalised plan”, “tailored to you”, or any language implying individual prediction. She presents what real-world populations show, not what any given person will experience.

Safety escalation, overrides all other rules

Ketones ≥1.5 mmol/L, glucose ≤2.2 mmol/L, DKA symptoms, severe paediatric hypo, Grace directs immediately to 999/A&E. No educational hedging. No waiting. Tested against four real escalation scenarios including a child in severe hypo with panic framing. All four passed with exemplary responses.

No wiki fabrication

If the knowledge base is not loaded, Grace acknowledges the absence and does not reconstruct algorithm values from memory. She never invents a clinical number. If she cannot confirm a figure from her loaded context, she says so.

Jailbreak resistance

Prompt injection, roleplay framing, false authority claims, urgency pressure, all tested, all refused. 12/12 jailbreak attempts resisted across the full adversarial test suite.

Insurance

All GNL educational platform activity, including Grace, is covered by professional indemnity and public liability insurance at £2 million per claim. Insurance documentation is available to institutional partners and prospective licensees on request.

Intellectual property and compliance

Protected at every layer

GNL’s algorithm suite, evidence base, and Grace are protected by registered trademarks, copyright, server-side code architecture, and a full compliance documentation framework. The GNL site dossier is available to institutional partners, insurers, and prospective licensees.

Registered trademarks

MarkRegistrationClassesStatus
The Glucose Never Lies®UK0000426779541, 44 (Education, Health)Registered
The Glucose Never Lies® (second mark)UK0000436024941, 42 (Education, Software)Accepted, awaiting Journal
GNL GraceUK000043706199, 41, 42 (Software, Education, SaaS)Filed 9 April 2026
GNL GraceEU EUTM9, 41, 42Filed 9 April 2026
GNL GraceUSPTO (US)9, 41, 42Due by 9 October 2026 (Paris Convention)

Code and algorithm protection

  • All algorithm source code is server-side. No algorithm logic is present in any browser-facing file. The engine cannot be extracted from the front end.
  • US Copyright filed, GNL Explorer Suite, Case 1-15136552281 (7 April 2026).
  • Algorithm documentation: the algorithm-reference section of the Grace dossier. Internal record only, not published.
  • Version-controlled audit trail: Git history + dossier change log + JS version numbers provide a complete record of every algorithm version ever deployed.

Compliance documentation

  • GNL site dossier, company structure, insurance, legal basis, GDPR, explorer compliance profiles, Grace architecture, full test results, IP schedule, governance framework.
  • ICO registered data controller (payment confirmed December 2025). UK GDPR and Data Protection Act 2018 compliant.
  • VAT registered, GB 516 3272 08 (effective 01 April 2026).
  • Incorporated, The Glucose Never Lies Ltd (Companies House).

Research collaboration

GNL as a research partner

Grace is not just an educator. She is a research engine. She holds the full validated evidence base and can assist with literature synthesis, manuscript development, methodology questions, and evidence-grading for T1D research projects. The GNL research pipeline has identified 30 high-value queries that remain open for future investigation.

📄
Paper under review
Pemberton J, Debong F, Hayes P, Kohli A. GNL Grace and the Explorer Suite: a compounding clinical knowledge base and deterministic educational tools for Type 1 diabetes, validated through 33 structured assessments against approximately 500,000 patient-days from approximately 1,300 individuals. Under review, npj Digital Medicine (Nature Portfolio). Pre-submission draft available under research confidentiality.
📚
Literature synthesis
Grace holds ~700 fully ingested papers, each summarised and grade-anchored, organised across 82 evidence-graded concept pages and 29 topic-level maps, with ~5,000 ranked-by-relevance citations behind that in the supporting library. She can identify what the evidence supports, what it doesn’t, and where gaps remain.
Manuscript assistance
Literature review support, evidence grading, methodology review, and output proofreading against GNL’s clinical knowledge base.
📊
Algorithm validation context
Grace holds all 33 real-world population analyses, including the complete algorithm validation study (481 individuals, 247,585 patient-days, Grade A).
Via Negativa audit
Identifying claims in the literature that the real-world data contradicts, a service no general-purpose AI can offer with this specificity.
🔭
Research agenda development
30 high-value queries have been identified and prioritised (Tier 1-3). These represent the next research frontier for T1D population data.
The commercial equivalent
If the real-world validation work underpinning Grace were commissioned independently, its commercial equivalent has been estimated at £90,000-£390,000: real-world dataset access, 33 population analyses, and the dedicated algorithm validation framework. No comparable T1D education platform has this evidence base without funding a clinical study. GNL has it. Grace holds it.

For industry

Want to work with Grace, or build something next to her?

Device manufacturers, health systems, and clinical teams who want clinical depth on top of Grace, or a deletable Claude-Code build of their own, run that conversation through Via Negativa Health, our consultancy arm.

Three sponsor routes, one conversation

Keep GNL Grace Free for T1D

Grace is free, forever, for anyone with type 1 diabetes. Funded by clinical and partner licences, matched pound for pound by GNL on every donation. Three routes, sponsors mix any combination. No tier sheet; every arrangement scoped in conversation.

1
Plus-one sponsor
£5 a month per slot. Anyone can sponsor: PWD, family, charity, manufacturer, foundation, school, clinic.

£5 in, GNL matches it pound for pound, two free Grace accounts activate. Five-tier monthly ladder via Buy Me a Coffee (£5 / £10 / £15 / £20 / £55 covering 1 / 2 / 3 / 4 / 11 donor-visible accounts). Match operates at the platform level on every donation.

2
Grace HCP licences
TBC. The complete clinic, learning, teaching and reference tool.

For Trusts, ICBs, named clinical teams, manufacturer-sponsored teams, individual clinicians. Six modes, generous monthly limits, all six Explorers, full clinical context. Every HCP licence funds two free Grace accounts for people with T1D (one from the licence price, one matched by GNL). Six-month minimum term, then rolling monthly.

3
Grace Max licences
TBC. Spider-Man powers for research, deep work, manuscripts.

All 20 expert modes, deep file uploads, extended thinking, the creative range to design, write, build, and analyse at depth. For research groups, manuscript leads, audit teams, manufacturer R&D, evidence-base contractors. Every Max licence funds two free Grace accounts for people with T1D (one from the licence price, one matched by GNL).

Sponsors mix any combination. Volume discounts negotiated in conversation.

Get an assessment

Or email john@theglucoseneverlies.com directly to discuss the number of licences you want.

GNL platform

The full GNL ecosystem

Grace and the six Explorers sit inside a complete T1D education platform: validated tools in the app, a clinical podcast, foundational education pages, and a growing body of content built from real-world evidence.

Get in touch

Licensing enquiries, research collaboration, institutional partnership

All go directly to John Pemberton. GNL Grace launches free for everyone with type 1 diabetes in June 2026. Wider partner and institutional access from Summer 2026.

Start an assessment

Or visit theglucoseneverlies.com

Educational use only. GNL Grace and the six Explorers are educational tools built from clinical evidence, real-world population data, and published guidelines. They model how populations behave on average, not how any individual will experience T1D. They are not medical devices. They are not diagnostic tools. They do not give clinical advice. Any questions about your individual diabetes management should be directed to your diabetes care team.
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