| 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 |