Origins of the Crisis in Insulin Affordability and Practical Advice for Clinicians on Using Human Insulin

Quantifying the Human Mortality Costs of Patent-based Intellectual Property: How Many Premature Deaths are due to Patents?

Patent-based intellectual property (IP) has come under progressively substantiative attack in the peer-reviewed literature as many studies have shown it retards innovation. In addition, the monopoly period no longer fits the innovation cycle. Although the vast majority of patents are not useful, patent proponents argue monopoly-based economic incentives are specifically necessary to fund medical technologies. Rather than use simple economics, quantifying human deaths has also been proposed as a means to guide public policies. Such an approach can be applied to patents by investigating the lives saved by patents as well as those lost in the current IP systems. This study is the first to provide such a theoretical approach to quantifying human mortality costs of patent-based IP systems. To illustrate the mechanism by which patents are responsible for premature deaths, a case study of the 100-year-old innovation of insulin is provided. The U.S. and Canada were selected to compare because the approach to drug costs in the two countries allows for a fraction of the additional costs of IP to be quantified. By comparing the different death rates of diabetics in U.S. and Canada, it was found that insulin-related patents result in over 94,000 American premature deaths annually (in 2021). The results also make it clear that many human deaths are related to price increases and lack of accessibility to needed medications due to the current monopolistic IP system. These findings require patent proponents to defend the continued existence of patents in the medical innovation space.

Application of machine learning in affordable and accessible insulin management for type 1 and 2 diabetes: A comprehensive review

Proper insulin management is vital for maintaining stable blood sugar levels and preventing complications associated with diabetes. However, the soaring costs of insulin present significant challenges to ensuring affordable management. This paper conducts a comprehensive review of current literature on the application of machine learning (ML) in insulin management for diabetes patients, particularly focusing on enhancing affordability and accessibility within the United States. The review encompasses various facets of insulin management, including dosage calculation and response, prediction of blood glucose and insulin sensitivity, initial insulin estimation, resistance prediction, treatment adherence, complications, hypoglycemia prediction, and lifestyle modifications. Additionally, the study identifies key limitations in the utilization of ML within the insulin management literature and suggests future research directions aimed at furthering accessible and affordable insulin treatments. These proposed directions include exploring insurance coverage, optimizing insulin type selection, assessing the impact of biosimilar insulin and market competition, considering mental health factors, evaluating insulin delivery options, addressing cost-related issues affecting insulin usage and adherence, and selecting appropriate patient cost-sharing programs. By examining the potential of ML in addressing insulin management affordability and accessibility, this work aims to envision improved and cost-effective insulin management practices. It not only highlights existing research gaps but also offers insights into future directions, guiding the development of innovative solutions that have the potential to revolutionize insulin management and benefit patients reliant on this life-saving treatment.

Insulin's Legacy: A Century of Breakthroughs and Innovation

The clinical use of insulin to treat diabetes started just over 100 years ago. The past century has witnessed remarkable innovations in insulin therapy, evolving from animal organ extracts to bioengineered human insulins with ultra-rapid onset or prolonged action. Insulin delivery systems have also progressed to current automated insulin delivery systems. In this review, we discuss the history of insulin and the pharmacology and therapeutic indications for a variety of available insulins, especially newer analog insulins. We highlight recent advances in insulin pump therapy and review evidence on the therapeutic benefits of automated insulin delivery. As with any form of progress, there have been setbacks, and insulin has recently faced an affordability crisis. We address the challenges of insulin accessibility, along with recent progress to improve insulin affordability. Finally, we mention research on glucose-responsive insulins and hepato-preferential insulins that are likely to shape the future of insulin therapy.

Open-source 3-D printable autoinjector: Design, testing, and regulatory limitations

Autoinjectors have become popular modern injectable medical devices used as drug delivery systems. Due to their ease, capability and reliability compared to other conventional injectable medical devices, the market and manufacturing demand for autoinjector devices are increasing rapidly and expected to reach a market of $37.5 billion globally by 2025. Although autoinjectors can offset healthcare treatment costs through self-administered medication, they can be expensive for consumers, which limit their accessibility. This study describes the design and manufacture of a spring-driven and 3-D printed autoinjector to overcome this economic accessibility challenge. The digitally replicable device is released as open-source hardware to enable low-cost distributed manufacturing. The bill of materials and assembly instructions are detailed, and the effectiveness of the autoinjector is tested against the current standard (ISO 11608-1:2022) for needle-based injection systems. The safety and dosing accuracy was tested by measuring the weight of 100% ethyl alcohol expelled from six BD Insulin syringes with varying capacities or needle lengths. A one-way analysis assessed the variability between the dose delivery efficiency of 1mL, 0.5mL, and 0.3mL syringes. Testing indicated that the entire dose was delivered over 97.5% of the time for 1mL and 0.5mL syringes, but the autoinjector's loaded spring force and size exceeded structural limitations of 0.3mL or smaller syringes. Components can be manufactured in about twelve hours using an open-source desktop RepRap-class fused filament 3-D printer. The construction requires two compression springs and 3-D printed parts. The total material cost of CAD$6.83 is less than a tenth of comparable commercial autoinjectors, which makes this approach promising. The autoinjector, however, is a class two medical device and must be approved by regulators. Future work is needed to make distributed manufacturing of such medical devices feasible and reliable to support individuals burdened by healthcare costs.

Multi-Level High-Throughput Screening for Discovery of Ligands That Inhibit Insulin Aggregation

We have developed a multi-level virtual screening protocol to identify lead molecules from the FDA inactives database that can inhibit insulin aggregation. The method is based on the presence of structural and interaction specificity in non-native aggregation pathway protein-protein interactions. Some key challenges specific to the present problem, when compared with native protein association, include structural heterogeneity of the protein species involved, multiple association pathways, and relatively higher probability of conformational rearrangement of the association complex. In this multi-step method, the inactives database was first screened using the dominant pharmacophore features of previously identified molecules shown to significantly inhibit insulin aggregation nucleation by binding to its aggregation-prone conformers. We then performed ensemble docking of several low-energy ligand conformations on these aggregation-prone conformers followed by molecular dynamics simulations and binding affinity calculations on a subset of docked complexes to identify a final set of five potential lead molecules to inhibit insulin aggregation nucleation. Their effect on aggregation inhibition was extensively investigated by incubating insulin under aggregation-prone aqueous buffer conditions (low pH, high temperature). Aggregation kinetics were characterized using size exclusion chromatography and Thioflavin T fluorescence assay, and the secondary structure was determined using circular dichroism spectroscopy. Riboflavin provided the best aggregation inhibition, with 85% native monomer retention after 48 h incubation under aggregation-prone conditions, whereas the no-ligand formulation showed complete monomer loss after 36 h. Further, insulin incubated with two of the screened inactives (aspartame, riboflavin) had the characteristic α-helical dip in CD spectra, while the no-ligand formulation showed a change to β-sheet rich conformations.

National Trends in Out-of-Pocket Costs Among U.S. Adults With Diabetes Aged 18-64 Years: 2001-2017

OBJECTIVE

To assess national trends in out-of-pocket (OOP) costs among adults aged 18-64 years with diabetes in the U.S.

RESEARCH DESIGN AND METHODS

Using data from the 2001-2017 Medical Expenditure Panel Survey, we estimated total per person annual OOP costs (insurance premiums, prescription drug costs, inpatient and outpatient deductibles, copays, and other payments not covered by insurance) and high OOP cost rate, defined as the percentage of people with OOP spending >10% of their family's pretax income. We examined trends overall, by subgroup (insurance type, income level, insulin use, size of patient's employer, and whether the patient was enrolled in a high deductible health plan), and by type of service. Changes in trends were identified using joinpoint analysis; costs were adjusted to 2017 U.S. dollars.

RESULTS

From 2001 to 2017, OOP costs decreased 4.3%, from $4,328 to $4,139, and the high OOP cost rate fell 32%, from 28 to 19% (P < 0.001). Changes in the high OOP cost rate varied by subgroup, declining among those with public or no insurance and those with an income <200% of the federal poverty level (P < 0.001) but remaining stable among those with private insurance and higher income. Drug prescription OOP costs decreased among all subgroups (P < 0.001). Decreases in total (-$58 vs. -$37, P < 0.001) and prescription (-$79 vs. -$68, P < 0.001) OOP costs were higher among insulin users than noninsulin users.

CONCLUSIONS

OOP costs among U.S. nonelderly adults with diabetes declined, especially among those least able to afford them. Future studies may explore factors contributing to the decline in OOP costs and the impact on the quality of diabetes care and complication rates.

Trends in Insulin Types and Devices Used by Adults With Type 2 Diabetes in the United States, 2016 to 2020

IMPORTANCE

Despite rising costs and public scrutiny devoted to insulin, less is known regarding recent trends in its ambulatory use in the United States.

OBJECTIVE

To characterize trends in ambulatory insulin use, overall and based on insulin characteristics, among adults with type 2 diabetes in the United States from January 1, 2016, through December 31, 2020.

DESIGN, SETTING, AND PARTICIPANTS

This serial cross-sectional study included patients whose data were collected in IQVIA's National Disease and Therapeutic Index (NDTI), a 2-stage, all-payer, nationally representative audit of outpatient care. Approximately 4800 physicians each calendar quarter completed a form for 2 consecutive days regarding visits for each of their patients, including diagnoses, treatments, and demographic information. Data were collected from January 2016 through December 2020.

EXPOSURES

Ambulatory use of insulin.

MAIN OUTCOMES AND MEASURES

Nationally representative projections for ambulatory use of insulin (ie, treatment visits), overall and aggregated by insulin molecule (insulins regular, neutral protamine Hagedorn [NPH], lispro, glulisine, glargine, detemir, degludec, and aspart), delivery devices (vials/syringes or pens), therapeutic class (short-acting, rapid-acting, long-acting, intermediate-acting, and premixed insulin), insulin type (human, analog, and biosimilar), and date of approval (newer: before 2010; and older: after 2010).

RESULTS

There were 27 860 691 insulin treatment visits between 2016 and 2020. Among all patient encounters that indicated use of insulin in 2020, 1 989 154 (43.9%) were among those aged 60 to 74 years; 2 372 629 (52.4%) among men; 2 646 247 (58.4%) among White patients; 811 639 (17.9%) among Black patients; and 701 912 (15.5%) among Hispanic patients. Insulin glargine was the most frequently used insulin from 2016 to 2020, accounting for approximately half of treatment visits (eg, 2020: 2.6 of 4.9 million visits; 95% CI, 2.1-3.1 million). Among insulin classes, long-acting insulin accounted for approximately two-thirds of treatment visits during this period (eg, 2020: 3.7 million visits; 95% CI, 3.0-4.4 million). Treatment visits for insulin pens increased from 36.1% in 2016 (2.2 of 6.0 million visits; 95% CI, 1.7-2.7 million) to 58.7% in 2020 (2.9 million visits; 95% CI, 2.3-3.5 million), while use of insulin vials/syringes declined in parallel. Analog insulin use predominated and accounted for more than 80% of total treatment visits across all years (eg, 2020: 4.3 million visits; 95% CI, 3.4-5.1 million). Newer insulins were increasingly used, from 18.1% of total treatment visits in 2016 (1.1 million visits; 95% CI, 0.8-1.4 million) to 40.9% in 2020 (2.0 million visits; 95% CI, 1.5-2.5 million). The use of biosimilar insulin, which was first approved in 2015, increased from 2.6% in 2017 (0.1 of 5.3 million visits; 95% CI, 0.04-0.2 million) to 8.2% in 2020 (0.4 million visits; 95% CI, 0.2-0.6 million) of total insulin treatment visits. The total number of insulin treatment visits declined from a peak of 6.0 million visits in 2016 to a nadir of 4.9 million visits in 2020 (approximately 18% decline).

CONCLUSIONS AND RELEVANCE

In this study, ambulatory insulin use in the United States during the past 5 years remained dominated by the use of insulin analogs and insulin pen delivery devices, with increasing uptake of newer products as they have been brought to market.

Prescription drug coverage satisfaction, cost-reducing behavior, and medication nonadherence among Medicare beneficiaries with type 2 diabetes

BACKGROUND: Medication nonadherence in individuals with type 2 diabetes can lead to poor glycemic control, resulting in increased risk for diabetes-related complications. OBJECTIVE: To examine associations between factors (ie, drug coverage satisfaction and cost-reducing behavior) and medication nonadherence among Medicare beneficiaries with type 2 diabetes. METHODS: We analyzed the 2016 Medicare Current Beneficiary Survey Public Use File for beneficiaries aged 65 years and older with reported type 2 diabetes (n=1,430; weighted n=5,846,943). Medicare beneficiaries were considered to have medication nonadherence if they reported skipping doses or taking smaller doses than prescribed. A survey-weighted logistic model, adjusted for sociodemographics and comorbidities, was conducted to examine associations of drug coverage satisfaction and cost-reducing behavior with medication nonadherence. RESULTS: Among Medicare beneficiaries aged 65 years and older with type 2 diabetes, 10.3% reported medication nonadherence. In the adjusted analysis, the risk for medication nonadherence was higher among those who were dissatisfied with the amount paid for medications (OR = 2.43; P = 0.002) compared with those who were satisfied, and those who spent less on basic needs to save for medications were more likely to report medication nonadherence (OR = 2.23; P = 0.011) than those who did not. CONCLUSIONS: Our findings suggest that medication nonadherence among Medicare beneficiaries with type 2 diabetes is associated with dissatisfaction with the amount paid for medications and cost-reducing behavior. Interventions that lower medication costs for Medicare beneficiaries may help to improve medication adherence among this at-risk population. DISCLOSURES: No outside funding supported this study. The authors have no conflicts of interest to disclose.

Estimates of insulin needs and dispensation given wastage, alternative glycemic targets, and non-insulin therapies in US populations with type 2 diabetes mellitus: A microsimulation study

AIMS

Registries and health plans estimate insulin need for population health metrics. We sought to identify how such estimates affect population- and individual-level estimates of over- and under-treatment.

METHODS

We developed a microsimulation comparing estimated insulin need to dispensation using the National Health and Nutrition Examination Survey (NHANES, 2005-2016, N= 2832) and Medical Expenditure Panel Survey (MEPS, 2005-2016, N = 29,615).

RESULTS

From NHANES, ~21.6% of people with type 2 diabetes would require insulin to achieve a HbA1c target of 7% after maximum titration of two non-insulins (60.7 IU/person/day, or 84,629,833 vials of 1000 IU in the US). From MEPS, we observed 57.4 IU/person/day of insulin dispensed (81,585,842 vials). About 29% of people were dispensed at least two standard deviations less than their estimated need, and 22% at least two standard deviations more than estimated need. Population-level need estimates reduced 39.4% if liberalizing HbA1c targets to 8% for people ≥75 years old.

CONCLUSIONS

Estimated insulin needs of people with type 2 diabetes in the U.S. are consistent with their dispensed insulin at the population level, but are sensitive to HbA1c targets for older adults, and conceal under- and over-treated subpopulations.