| 1. | EXECUTIVE SUMMARY | 
| 1.1. | Executive introduction | 
| 1.2. | Background: Introduction to diabetes | 
| 1.3. | Background: The cost of diabetes | 
| 1.4. | Diabetes management process | 
| 1.5. | Scope of the report | 
| 1.6. | Diabetes management device roadmap:  Glucose sensors | 
| 1.7. | Test strips and glucometers: introduction | 
| 1.8. | Anatomy of a glucose test strip | 
| 1.9. | Continuous glucose monitors: introduction | 
| 1.10. | Anatomy of a typical CGM device | 
| 1.11. | CGM continues to gain momentum | 
| 1.12. | Non-invasive glucose monitoring | 
| 1.13. | Non-invasive glucose monitoring: conclusions | 
| 1.14. | Diabetes management device roadmap:  Insulin delivery | 
| 1.15. | Insulin pens: overview | 
| 1.16. | Insulin pumps: overview | 
| 1.17. | Hybrid closed-loop: introduction | 
| 1.18. | Status of the insulin delivery industry hinges on the development of closed-loop systems | 
| 1.19. | Alternative insulin delivery methods have yet to gain a foothold | 
| 1.20. | Digital health is driven by increasing device connectivity | 
| 1.21. | Digital health is a growing option for diabetes management | 
| 1.22. | Managing side effects accounts for 90% of the total cost of diabetes | 
| 1.23. | Outlook for diabetes complication management | 
| 1.24. | Advanced therapies for diabetes: roadmap | 
| 1.25. | Advanced therapies: conclusions | 
| 1.26. | List of 108 companies mentioned in this report | 
| 1.27. | Diabetes management devices: annual revenue 2010-2021 | 
| 1.28. | Evaluation of the overall diabetes device industry from 2010-2032 | 
| 1.29. | CGM: annual revenue forecast 2022-2032 | 
| 1.30. | Test strip market forecast 2022-2032 | 
| 1.31. | Insulin pumps revenue forecast 2022-2032 | 
| 2. | INTRODUCTION | 
| 2.1. | Background: Introduction to diabetes | 
| 2.2. | The prevalence of diabetes | 
| 2.3. | Background: Diabetes on the rise | 
| 2.4. | Background: The cost of diabetes | 
| 2.5. | Type 1 vs Type 2 | 
| 2.6. | Background | 
| 2.7. | Self-Management Devices | 
| 2.8. | Diabetes management device roadmap: Summary | 
| 2.9. | Diabetes management device roadmap:  Glucose sensors | 
| 2.10. | Diabetes management device roadmap:  Insulin delivery | 
| 3. | GLUCOSE SENSORS | 
| 3.1.1. | History of glucose monitoring | 
| 3.1.2. | Players in glucose monitoring | 
| 3.1.3. | Diabetes management device roadmap:  Glucose sensors | 
| 3.1.4. | Key criteria for assessing accuracy | 
| 3.2. | Test strips and glucometers | 
| 3.2.1. | Glucose monitoring through test strips and associated readers | 
| 3.2.2. | Test strips: business model | 
| 3.2.3. | Anatomy of a glucose test strip | 
| 3.2.4. | Electrode deposition: screen printing vs sputtering | 
| 3.2.5. | Lifescan uses multiple manufacturing methods | 
| 3.2.6. | An introduction to glucose sensing:  glucose oxidase | 
| 3.2.7. | Glucose sensing via GOx: mechanism | 
| 3.2.8. | Glucose dehydrogenase: introduction | 
| 3.2.9. | Glucose dehydrogenase: sensing methods | 
| 3.2.10. | A comparison of GDH and GOx mechanisms | 
| 3.2.11. | GDH-FAD have potential for development of "third-generation" sensors | 
| 3.2.12. | Comparison of GDH and GOx in glucose sensing | 
| 3.2.13. | Overview of several test strips and enzymes used | 
| 3.2.14. | Roche: Overview | 
| 3.2.15. | Roche: Accu-Chek Guide | 
| 3.2.16. | Roche / Glytec: cobas pulse | 
| 3.2.17. | Abbott Laboratories: Introduction | 
| 3.2.18. | Abbott: coulometric methods for test strips | 
| 3.2.19. | EasyMax Diabetes Care | 
| 3.2.20. | Innovation shifts from test strip development to increasing digitization | 
| 3.2.21. | Comparing test strip costs with CGM | 
| 3.2.22. | Test strips: market outlook | 
| 3.3. | Continuous glucose monitoring  (CGM) | 
| 3.3.1. | Continuous glucose monitors: introduction | 
| 3.3.2. | Anatomy of a typical CGM device | 
| 3.3.3. | CGMs are superseding test strips | 
| 3.3.4. | CGM: Technology | 
| 3.3.5. | CGM sensor chemistry | 
| 3.3.6. | CGM technologies: glucose dehydrogenase | 
| 3.3.7. | CGM miniaturization and "green" diabetes | 
| 3.3.8. | CGM sensor manufacturing and anatomy | 
| 3.3.9. | Sensor filament structure | 
| 3.3.10. | Foreign body responses to CGM devices | 
| 3.3.11. | Calibration of glucose monitoring devices | 
| 3.3.12. | Comparison metrics for CGM devices | 
| 3.3.13. | Example: Accuracy of CGM devices over time | 
| 3.3.14. | Interference of medication with CGM accuracy | 
| 3.4. | CGM: Markets and Key Players | 
| 3.4.1. | CGM: Overview of key players | 
| 3.4.2. | Abbott Laboratories: CGM business | 
| 3.4.3. | Abbott: Freestyle® Libre | 
| 3.4.4. | Abbott: "Wired enzyme" | 
| 3.4.5. | Abbott: Device and sensor structure | 
| 3.4.6. | Dexcom: Introduction | 
| 3.4.7. | Dexcom: CGM products | 
| 3.4.8. | Dexcom: Sensor structure | 
| 3.4.9. | Medtronic: Introduction | 
| 3.4.10. | Medtronic: Diabetes & CGM business | 
| 3.4.11. | Roche: Patents in CGM | 
| 3.4.12. | Ascensia, POCTech and Yuwell | 
| 3.4.13. | Medtrum | 
| 3.4.14. | Medtrum: Sensing technology | 
| 3.4.15. | Medtrum: Outlook | 
| 3.4.16. | AgaMatrix & WaveForm Technologies | 
| 3.4.17. | Infinovo | 
| 3.4.18. | Sano | 
| 3.5. | Implantable glucose sensors | 
| 3.5.1. | Implantable glucose sensors: Introduction | 
| 3.5.2. | Key Players in Implantable Glucose Monitoring | 
| 3.5.3. | Fluorescence-based glucose detection | 
| 3.5.4. | Senseonics | 
| 3.5.5. | Senseonics: Financials and Partnerships | 
| 3.5.6. | GlySens: Eclipse 3 | 
| 3.5.7. | GluSense | 
| 3.6. | CGM: conclusions | 
| 3.6.1. | Focus shifts from test strips to CGM | 
| 3.6.2. | Global CGM reimbursement | 
| 3.6.3. | CGM markets in Asia | 
| 3.6.4. | Outlook for smaller test strip companies | 
| 3.6.5. | CGM reimbursement for type 2 is currently limited | 
| 3.6.6. | CGM usage in hospitals | 
| 3.7. | Non-invasive glucose monitoring | 
| 3.7.1. | Non-invasive glucose monitoring | 
| 3.7.2. | Assessment of different analytes for glucose monitoring | 
| 3.7.3. | In Context: FDA requirements | 
| 3.7.4. | Non-Invasive Blood and ISF | 
| 3.7.5. | Non-invasive glucose monitoring: approaches | 
| 3.7.6. | Companies Using Each Technique | 
| 3.7.7. | Near-Infrared Spectroscopy | 
| 3.7.8. | Near-Infrared Spectroscopy - Recent Academic Studies | 
| 3.7.9. | NIR Companies | 
| 3.7.10. | CNOGA | 
| 3.7.11. | Mid Infrared Spectroscopy | 
| 3.7.12. | MIR Companies | 
| 3.7.13. | DiaMonTech | 
| 3.7.14. | Terahertz Spectroscopy | 
| 3.7.15. | Dielectric Spectroscopy | 
| 3.7.16. | Alertgy | 
| 3.7.17. | Know Labs | 
| 3.7.18. | Afon Technology | 
| 3.7.19. | Zedsen | 
| 3.7.20. | Zedsen | 
| 3.7.21. | Raman Spectroscopy | 
| 3.7.22. | Kaligia Biosciences | 
| 3.7.23. | Quantum Operation | 
| 3.7.24. | RSP Systems | 
| 3.7.25. | Samsung | 
| 3.7.26. | Optical Rotation | 
| 3.7.27. | Transdermal Techniques | 
| 3.7.28. | Reverse Iontophoresis | 
| 3.7.29. | Reverse Iontophoresis Companies | 
| 3.7.30. | Nemaura Medical | 
| 3.7.31. | PKvitality | 
| 3.7.32. | Cygnus | 
| 3.8. | Non-invasive glucose monitoring:  other fluids | 
| 3.8.1. | Companies Using Each Technique (Other Fluids) | 
| 3.8.2. | Measuring glucose in sweat | 
| 3.8.3. | Measuring glucose in tears | 
| 3.8.4. | Measuring glucose in saliva | 
| 3.8.5. | Measuring glucose in breath | 
| 3.8.6. | Measuring glucose in urine | 
| 3.9. | Non-invasive glucose monitoring: conclusions | 
| 3.9.1. | When will non-invasive glucose monitoring be commercialised? | 
| 3.9.2. | Notable Quotes on Non-Invasive Glucose Monitoring | 
| 4. | INSULIN DELIVERY | 
| 4.1.1. | Insulin: introduction | 
| 4.1.2. | Delivering insulin is a critical part of diabetes management | 
| 4.1.3. | Comparison of different types of insulin* | 
| 4.1.4. | Short-acting (bolus) insulin | 
| 4.1.5. | Long-acting (basal) insulin | 
| 4.1.6. | Different types of insulin have different use cases | 
| 4.1.7. | Insulin Delivery Devices | 
| 4.1.8. | History of insulin delivery methods | 
| 4.1.9. | Technological roadmap from two separate perspectives | 
| 4.2. | Insulin pens | 
| 4.2.1. | Insulin Pens | 
| 4.2.2. | Smarter insulin delivery informing decisions | 
| 4.2.3. | Smart pens are driven by a growing CGM market | 
| 4.2.4. | Partnership ecosystem for smart insulin pens | 
| 4.2.5. | Overview of commercial smart pen devices* | 
| 4.2.6. | Novo Nordisk | 
| 4.2.7. | Novo Nordisk: NovoPen | 
| 4.2.8. | Eli Lilly | 
| 4.2.9. | Eli Lilly: Tempo Smart | 
| 4.2.10. | Ypsomed | 
| 4.2.11. | Ypsomed smart devices | 
| 4.2.12. | Bigfoot Unity Diabetes Management System | 
| 4.2.13. | Companion Medical / Medtronic: InPen | 
| 4.2.14. | Outlook for insulin pens | 
| 4.3. | Insulin pumps | 
| 4.3.1. | Insulin Pumps | 
| 4.3.2. | Insulin patch pumps | 
| 4.3.3. | Pricing models for patch pumps vs traditional options | 
| 4.3.4. | Insulin pumps currently available | 
| 4.3.5. | Insulin pump breakdown | 
| 4.3.6. | Accu-Chek Solo by Roche | 
| 4.3.7. | DANA-I by SOOIL | 
| 4.3.8. | Insulin pump market | 
| 4.3.9. | Insulin pump players and market share | 
| 4.3.10. | Markets: Patch pumps vs traditional infusion pumps | 
| 4.3.11. | Comparing insulin pumps and CGM | 
| 4.3.12. | Insulin pump technology roadmap | 
| 4.3.13. | Outlook for insulin pumps | 
| 4.4. | Linking insulin pumps and CGM: Towards closed loop and the artificial pancreas | 
| 4.4.1. | Today: Hybrid closed loop systems | 
| 4.4.2. | Hybrid closed-loop to match mealtime surge | 
| 4.4.3. | The objective: Closing the feedback loop | 
| 4.4.4. | Example: Progress from Medtronic | 
| 4.4.5. | Partnership ecosystem for hybrid closed-loop systems | 
| 4.4.6. | Ultra-fast acting insulin: introduction | 
| 4.4.7. | The case of ultra-fast insulin in hybrid closed -loop | 
| 4.4.8. | Actual results: ultra-fast insulin have yet to show significant improvements to hybrid closed-loop | 
| 4.4.9. | Comparison of hybrid closed-loop systems | 
| 4.4.10. | Medtronic: Towards closed loop | 
| 4.4.11. | Medtronic: MiniMed 780G | 
| 4.4.12. | Dexcom-Tandem partnership: Control-IQ | 
| 4.4.13. | Insulet: Omnipod 5 | 
| 4.4.14. | CamDiab: CamAPS FX | 
| 4.4.15. | Beta Bionics: iLet | 
| 4.4.16. | Tidepool: Tidepool Loop | 
| 4.4.17. | The ForgetDiabetes Project | 
| 4.4.18. | Unanswered questions about device security | 
| 4.5. | Alternative insulin technologies | 
| 4.5.1. | Non-invasive insulin delivery methods | 
| 4.5.2. | Comparison of various routes for non-invasive insulin delivery | 
| 4.5.3. | Inhaled insulin: introduction | 
| 4.5.4. | MannKind: Afrezza | 
| 4.5.5. | Inhaled insulin faces challenges in the market | 
| 4.5.6. | Inhaled insulin: outlook | 
| 4.5.7. | Oral insulin delivery | 
| 4.5.8. | Buccal insulin delivery | 
| 4.5.9. | Transdermal insulin delivery: introduction | 
| 4.5.10. | Companies looking at transdermal insulin delivery | 
| 4.5.11. | Non-invasive insulins face several barriers to market adoption | 
| 4.5.12. | The road towards non-invasive insulin delivery is paved with failure | 
| 4.5.13. | Some reasons why non-invasive insulin delivery continues to be looked at | 
| 4.5.14. | Glucose-responsive insulin | 
| 4.5.15. | Glucose sensing: the Ziylo approach | 
| 5. | DIABETES MANAGEMENT VIA DIGITAL HEALTH | 
| 5.1.1. | The scope of digital health in diabetes management | 
| 5.1.2. | Diabetes is an Early Adopter of Digital Healthcare Initiatives | 
| 5.1.3. | Diabetes digital health landscape* | 
| 5.1.4. | Diabetes management ecosystem | 
| 5.1.5. | Digital health: regulations, legality and privacy | 
| 5.2. | Blood glucose data in mobile apps | 
| 5.2.1. | Diabetes Apps | 
| 5.2.2. | Digital health is driven by increasing device connectivity | 
| 5.2.3. | CGM integration with mobile apps | 
| 5.2.4. | Dexcom: retrospective and real time APIs | 
| 5.2.5. | The Level 2 program leverages the Dexcom app-in-app module | 
| 5.2.6. | WellDoc: BlueStar | 
| 5.2.7. | Roche: SugarView | 
| 5.3. | Apps for lifestyle management | 
| 5.3.1. | Diabetes management: focal points | 
| 5.3.2. | Diet for diabetes management has two avenues | 
| 5.3.3. | Nemaura Medical: MiBoKo | 
| 5.3.4. | Fitscript: GlucoseZone | 
| 5.3.5. | SNAQ | 
| 5.3.6. | SNAQ: machine learning techniques | 
| 5.4. | Telehealth in diabetes  management | 
| 5.4.1. | Telehealth in diabetes: introduction | 
| 5.4.2. | Ecosystem of a digital health program for diabetes | 
| 5.4.3. | Telehealth programs often follow the same recipe | 
| 5.4.4. | Glooko | 
| 5.5. | Digital health in diabetes:  Conclusions | 
| 5.5.1. | Prediabetes via digital health? | 
| 5.5.2. | Digital Health Programs: Evidence for Type 2 Diabetes | 
| 5.5.3. | Digital health and diabetes: outlook | 
| 6. | TECHNOLOGY FOR MANAGING DIABETES COMPLICATIONS | 
| 6.1.1. | Managing side effects accounts for 90% of the total cost of diabetes | 
| 6.1.2. | Scope of this report | 
| 6.2. | Diabetic Ketoacidosis | 
| 6.2.1. | A severe lack of insulin can lead to diabetic ketoacidosis | 
| 6.2.2. | Ketone monitoring via electrochemical sensors | 
| 6.2.3. | Ketone monitoring via urine | 
| 6.2.4. | Ketone monitoring: outlook | 
| 6.3. | Diabetic neuropathy | 
| 6.3.1. | Diabetic neuropathy: introduction | 
| 6.3.2. | Diabetic foot ulcers | 
| 6.3.3. | Impeto Medical: Sudoscan | 
| 6.3.4. | Basic requirements of a diabetic footwear | 
| 6.3.5. | Smart options for diabetic footwear | 
| 6.3.6. | Orpyx | 
| 6.3.7. | Siren Care Denmark IVS | 
| 6.3.8. | Flextrapower | 
| 6.3.9. | Flextrapower | 
| 6.3.10. | Diabetes foot ulcers: outlook | 
| 6.4. | Diabetic retinopathy | 
| 6.4.1. | Diabetic retinopathy: introduction | 
| 6.4.2. | Diabetic retinopathy has seen developments in diagnosis and management | 
| 6.4.3. | Artelus: Detecting DR by ensuring image quality | 
| 6.4.4. | Wearable vision aids | 
| 6.4.5. | Diabetic retinopathy: outlook | 
| 7. | ADVANCED THERAPIES FOR DIABETES TREATMENT | 
| 7.1. | Advanced therapies for diabetes: roadmap | 
| 7.2. | Advanced therapies: introduction | 
| 7.3. | Regenerative medicine is currently rarely used to treat diabetes | 
| 7.4. | Regenerative medicine for type 1 diabetes: introduction | 
| 7.5. | Cell Therapy Devices | 
| 7.6. | Cell encapsulation devices | 
| 7.7. | Cell therapy devices: clinical trials | 
| 7.8. | Kriya Therapeutics | 
| 7.9. | Diamyd Medical: preventive medicine for type 1 | 
| 7.10. | Regenerative medicine for type 2 diabetes: introduction | 
| 7.11. | Mito Biopharma | 
| 7.12. | Regenerative medicine: conclusion | 
| 8. | AI IN DIABETES | 
| 8.1. | Machine learning in diabetes management | 
| 8.2. | AI in healthcare: Existing regulations | 
| 8.3. | AI can show varying levels of intelligence | 
| 8.4. | Various neural networks and use cases of each for diabetes management | 
| 8.5. | Overview of various methods for AI | 
| 8.6. | AI-enabled coaching | 
| 8.7. | AI image recognition | 
| 8.8. | AI for non-invasive glucose sensing | 
| 9. | FORECASTS | 
| 9.1. | Forecast: introduction | 
| 9.2. | Forecast method: Company revenue in diabetes management | 
| 9.3. | Diabetes device industry market forecast 2022-2032 | 
| 9.4. | Diabetes device industry market forecast 2022-2032 | 
| 9.5. | Diabetes device industry historic and forecast data 2010-2032 | 
| 9.6. | Diabetes management devices by proportion of total market revenue 2010-2032 | 
| 9.7. | CGM: annual revenue forecast 2022-2032 | 
| 9.8. | CGM: methodology and assumptions | 
| 9.9. | CGM: forecasted uptake by type 2 and prediabetes | 
| 9.10. | CGM: Milestones | 
| 9.11. | CGMs by population adoption proportion | 
| 9.12. | Insulin pumps revenue forecast 2022-2032 | 
| 9.13. | Insulin pumps: forecast methodology | 
| 9.14. | Infusion pumps revenue forecast 2022-2032 | 
| 9.15. | Patch pumps revenue forecast 2022-2032 | 
| 9.16. | Test strip market forecast 2022-2032 | 
| 9.17. | Glucometers revenue forecast 2022-2032 | 
| 9.18. | Insulin pens revenue forecast 2022-2032 | 
| 10. | COMPANY PROFILES | 
| 10.1. | Links to 16 company profiles |