Symptoms evolve between consultations
Nausea, fatigue and gastrointestinal effects change week to week and are rarely captured in a structured form.
Lean Protocol Innovation
Building the Intelligence Layer for Safer Obesity Care
Lean Protocol is developing a clinician-supervised platform that unifies symptoms, adherence, lifestyle, laboratory information and treatment progress into one continuous obesity-care workflow.
- Clinician supervised
- Explainable decision support
- Designed for Indian care settings
The platform supports monitoring, prioritisation and care coordination. It does not independently diagnose, prescribe or change medication. Final clinical decisions remain with qualified healthcare professionals.
Positioned for institutional and clinical evaluation
DPIIT-recognised startup
Government of India
Clinician-supervised design
Human accountability retained
Explainable decision support
No unexplained scores
Built for Indian care settings
Urban, Tier-2 and Tier-3
The clinical gap
Obesity treatment continues between consultations. Most care systems do not.
Treatment for obesity is longitudinal. The information that determines whether it is working - and whether it is safe - accumulates in the weeks between appointments, where no system is watching.
Medication adherence may be inconsistent
Missed or delayed doses are often discovered at the next visit rather than when they happen.
Nutritional intake can become inadequate
Reduced appetite can quietly cross from intended restriction into insufficient intake.
Hydration may decline
Falling fluid intake is a common and under-reported contributor to avoidable side effects.
Side effects may go unreported
Patients frequently wait for a scheduled appointment instead of reporting a problem when it appears.
Information is fragmented
Doctors, dietitians, laboratories and patients each hold part of the record and none holds all of it.
Follow-up depends on manual communication
Coordination runs on phone calls and messages, and scales linearly with headcount.
Clinical escalation can occur late
Without prioritisation, the patient who needs attention first is not reliably the patient seen first.
Longitudinal outcomes are rarely structured
Programme-level learning is limited when outcomes are not captured in a comparable format.
Where the information sits today
- Patient
- Doctor
- Dietitian
- Laboratory
- Symptoms
- Medication
- Weight
- Activity
No unified longitudinal care layer
The challenge is not simply collecting more data. It is converting relevant patient information into timely, clinically governed action.
Product workflow
One continuous workflow from patient signal to clinician-approved action
Proposed R&D module
- 1
Collect
Symptoms, medication, meals, hydration, weight, activity and laboratory information.
- 2
Understand
Build a longitudinal view of the patient's treatment stage and changing context.
- 3
Score
Apply explainable adherence and risk logic.
- 4
Alert
Prioritise patients through reason-coded red, amber and green alerts.
- 5
Intervene
Allow qualified care professionals to review, approve and track actions.
The platform supports monitoring and triage. It does not independently diagnose or prescribe.
Product modules
A connected platform for patients and care teams
Four modules share one longitudinal record: what the patient reports, what the care team sees, and what happens next.
01Existing workflow
Patient Companion
A daily companion for people in active treatment, designed so that reporting takes seconds rather than effort.
- Daily care plan
- Meal and hydration logging
- Symptom reporting
- Medication adherence
- Weight and activity tracking
- Educational content
- Care-team connection
02Existing workflow
Symptoms and Adherence
Structured capture of side effects and dosing behaviour, so a deteriorating pattern is visible before it becomes an event.
- Structured symptom reporting
- Severity tracking
- Symptom trends
- Adherence monitoring
- Trigger identification
- Care-team notes
- Early escalation support
03Existing workflow
Clinician Command Centre
A prioritised queue that answers one question first: which patient needs a clinician today, and why.
- Prioritised patient queue
- Explainable alert factors
- Risk summaries
- Clinician approval workflow
- Intervention history
- Follow-up monitoring
04Proposed R&D module
Progress and Outcomes
Longitudinal outcome capture at patient and programme level, structured for review and research.
- Longitudinal weight trends
- Symptom burden
- Adherence trends
- Intervention outcomes
- Dropout-risk signals
- Aggregate programme insights
Technical distinctiveness
Not another generic health tracker
Proposed proprietary data and decision-support architecture.
India-specific diet and symptom ontology
Structures Indian meals, dietary habits, gastrointestinal triggers, hydration patterns and treatment behaviours into clinically useful information.
Longitudinal patient intelligence
Evaluates changing patterns across weeks rather than isolated daily entries.
Explainable decision support
Shows the contributing factors behind each risk signal rather than presenting an unexplained score.
Clinician feedback loop
Records reviewed interventions and outcomes so workflows can be refined over time.
Privacy by design
Uses consent-led collection, role-based access, auditable actions and limited health-data exposure.
Technical architecture
Designed as a modular and auditable healthcare platform
Proposed R&D module
Layer 1
Patient and clinical inputs
- Symptoms
- Medication adherence
- Weight
- Nutrition
- Hydration
- Activity
- Laboratory results
- Clinician notes
Layer 2
Secure data infrastructure
- Supabase PostgreSQL
- Longitudinal patient records
- Consent management
- Role-based access
- Audit logs
- Secure storage
Layer 3
Protocol and intelligence layer
- Clinical rules
- Risk stratification
- Adherence logic
- Trend detection
- Explainability
- Intervention workflows
Layer 4
User interfaces
- Patient application
- Doctor dashboard
- Dietitian dashboard
- Operations dashboard
- Outcomes dashboard
Proposed architecture subject to technical, clinical, security and regulatory validation.
Current stage
From an operating care workflow to a scalable technology platform
Existing operational learning
- Existing obesity-care delivery workflow
- Doctor and dietitian involvement
- Patient follow-up experience
- Symptom-management experience
- Medication-adherence experience
- Operational understanding of patient dropout
Product development underway
- Patient application
- Clinician dashboard
- Structured symptom workflows
- Data architecture
- Care-team coordination workflows
R&D and validation required
- Explainable risk engine
- Clinical-rule validation
- Prospective pilot
- Security testing
- Usability testing
- Multi-site deployment readiness
Proposed SBIRI R&D programme
Proposed Research and Development Programme
Proposed R&D module
Project title
Development and Initial Validation of an Explainable Clinical Decision-Support Platform for Obesity-Treatment Monitoring and Adherence
Objectives
- 1Develop a secure longitudinal patient-data platform
- 2Build patient and clinician interfaces
- 3Formalise protocol-led risk and escalation workflows
- 4Develop explainable adherence and symptom intelligence
- 5Conduct initial technical and clinical validation
- 6Prepare the platform for controlled multi-clinic deployment
Proposed endpointA validated prototype ready for prospective clinical and operational evaluation.
Pilot and validation
Validation focused on safety, adherence and clinical usability
Planned validation
Proposed parameters
Participants
[INSERT PROPOSED NUMBER]
Clinical sites
[INSERT PROPOSED NUMBER]
Duration
[INSERT PROPOSED PERIOD]
Primary outcomes
- Patient engagement
- Completeness of symptom reporting
- Medication-adherence tracking
- Alert response time
- Escalation completion
- Clinician usability
- Follow-up completion
- Disengagement or dropout signals
Secondary exploratory outcomes
- Change in symptom burden
- Intervention acceptance
- Continuity of follow-up
- Clinician time saved
- Patient understanding
The final protocol, endpoints, ethics requirements and statistical methodology will be developed with qualified clinical and research partners.
Accessible deployment
Designed for deployment beyond premium metropolitan care
Design intent, not current operations
The platform is being designed for scalable deployment across urban and underserved Tier-2 and Tier-3 clinical settings, where continuous specialist follow-up may be limited.
Mobile-first access
Built for the device patients already own.
Low-bandwidth readiness
Designed to remain usable on constrained connections.
Multilingual interface potential
Interface strings structured for translation.
Clinic-assisted onboarding
Staff can enrol patients who need help getting started.
Simple patient reporting
Short structured inputs rather than free-text diaries.
Deployment through smaller clinics
No dependence on large hospital IT infrastructure.
Tier-2 and Tier-3 applicability
Designed for settings with limited specialist density.
Care-team support
Extends supervision where specialist access is intermittent.
Development roadmap
Phased development from prototype to deployment readiness
Planned validation
Months 1-3
01Foundation
- Architecture
- Data schema
- Clinical workflow mapping
- UI flows
- Consent framework
Months 4-6
02Build
- Patient application MVP
- Clinician dashboard
- Initial clinical rules
- Internal deployment
- Quality assurance
Months 7-9
03Pilot
- Controlled pilot
- Data annotation
- Alert-quality review
- Usability feedback
- Model and workflow refinement
Months 10-12
04Validation
- Validation report
- Security testing
- IP documentation
- Technical documentation
- Clinic deployment package
End stateA demonstrable product with pilot evidence, clinician usability feedback and a roadmap to commercial deployment.
Clinical safety and governance
Clinical intelligence with human accountability
Clinician in the loop
Every escalation is reviewed and approved by a qualified professional before it reaches a patient.
Explainable alerts
Each alert shows the factors that produced it, so a clinician can agree or disagree on the evidence.
Defined escalation protocols
Thresholds and routes are written down in advance rather than decided case by case.
Auditable intervention history
Who saw what, when, and what they did is recorded and reviewable.
Scope and limitations
- The platform is not a substitute for emergency care.
- The platform does not independently diagnose.
- The platform does not independently prescribe.
- The platform does not change medication automatically.
- Clinical decisions must be reviewed by qualified professionals.
- Medical-device and regulatory classification will be evaluated as the product develops.
Team capability
Built at the intersection of clinical care, technology and patient operations
Roles without a confirmed appointment are marked as planned project roles.
Founder and CEO
Planned project role
Company direction, care operations and institutional partnerships.
Clinical lead
Planned project role
Clinical protocols, escalation thresholds and medical governance.
Product and technology lead
Planned project role
Platform architecture, security and delivery.
Nutrition and behavioural-care lead
Planned project role
Dietary protocols, adherence support and patient engagement.
AI and data-science advisor
Planned project role
Explainability, risk logic and evaluation methodology.
Regulatory or research advisor
Planned project role
Study design, ethics pathway and regulatory classification.
Collaboration
Collaborate on the future of obesity-care infrastructure
Clinical and research partners
For pilot design, protocol validation and clinical deployment.
Discuss a Clinical PilotTechnology collaborators
For secure health-data systems, explainable intelligence and healthcare integrations.
Explore Research CollaborationIncubators and institutions
For R&D mentorship, validation infrastructure and commercialisation support.
Contact the Innovation TeamContact
Contact the innovation team
Tell us how you would like to work together. Enquiries reach the innovation team directly.
Questions
Frequently asked questions
Is this a medical device?
Medical-device and regulatory classification will be evaluated as the product develops. The platform is designed as a monitoring and care-coordination layer that supports qualified professionals; it does not independently diagnose, prescribe or change medication.
Does the platform make clinical decisions?
No. It prioritises and explains. Every escalation is reviewed and approved by a qualified clinician before action is taken, and that review is recorded.
What stage is the product at today?
An obesity-care delivery workflow is already operating with clinicians and dietitians. The patient application, clinician dashboard and data architecture are under development. The explainable risk engine, clinical-rule validation and prospective pilot are proposed R&D.
Are the interfaces shown on this page live?
No. Every interface shown is labelled as an illustrative product interface or a prototype under development. None should be read as a deployed feature.
How is patient data protected?
The design uses consent-led collection, role-based access, audit logging and limited health-data exposure. Security testing is included in the proposed validation programme.
Where would the platform be deployed?
It is being designed for urban as well as Tier-2 and Tier-3 clinical settings, where continuous specialist follow-up may be limited. Deployment claims will be made only once sites are confirmed.