C. Michael White, University of Connecticut

In just a few years, brand-name injectable drugs such as Ozempic, Wegovy, Mounjaro and Zepbound have rocketed to fame as billion-dollar annual sellers for weight loss as well as to control blood sugar levels and reduce the risk of heart disease.

But the price of these injections is steep: They cost about US$800-$1,000 per month, and if used for weight loss alone, they are not covered by most insurance policies. Both drugs mimic the naturally occurring hormone GLP-1 to help regulate blood sugar and reduce cravings. They can be taken only with a prescription.

The Food and Drug Administration announced an official shortage of the active ingredients in these drugs in 2022, but on Oct. 2, 2024, the agency announced that the shortage has been resolved for the medicine tirzepatide, the active ingredient in Mounjaro and Zepbound.

Despite the soaring demand and limited supply of these drugs, there are no generic versions available. This is because the patents for semaglutide – the active ingredient in Ozempic and Wegovy, which is still in shortage – and tirzepatide don’t expire until 2033 and 2036, respectively.

As a result, nonbrand alternatives that can be purchased with or without a prescription are flooding the market. Yet these products come with real risks to consumers.

I am a pharmacist who studies weaknesses in federal oversight of prescription and over-the-counter drugs and dietary supplements in the U.S. My research group recently has investigated loopholes that are allowing alternative weight loss products to enter the market.

High demand is driving GLP-1 wannabes

The dietary supplement market has sought to cash in on the GLP-1 demand with pills, teas, extracts and all manner of other products that claim to produce similar effects as the brand names at a much lower price.

Products containing the herb berberine offer only a few pounds of weight loss, while many dietary supplement weight loss products contain stimulants such as sibutramine and laxatives such as phenolphthalein, which increase the risk of heart attacks, strokes and cancer.

The role of compounding pharmacies

Unlike the dietary supplements that are masquerading as GLP-1 weight loss products, compounding pharmacies can create custom versions of products that contain the same active ingredients as the real thing for patients who cannot use either brand or generic products for some reason.

These pharmacies can also produce alternative versions of brand-name drugs when official drug shortages exist.

Since the demand for GLP-1 medications has far outpaced the supply, compounding pharmacies are legally producing a variety of different semaglutide and tirzepatide products.

These products may come in versions that differ from the brand-name companies, such as vials of powder that must be dissolved in liquid, or as tablets or nasal sprays.

Just like the brand-name drugs, you must have a valid prescription to receive them. The prices range from $250-$400 a month – still a steep price for many consumers.

Compounding pharmacies must adhere to the FDA’s sterility and quality production methods, but these rules are not as rigorous for compounding pharmacies as those for commercial manufacturers of generic drugs.

In addition, the products compounding pharmacies create do not have to be tested in humans for safety or effectiveness like brand-name products do.

Proper dosing can also be challenging with compounded forms of the drugs.

Companies that work the system

For people who cannot afford a compounding pharmacy product, or cannot get a valid prescription for semaglutide or tirzepatide, opportunistic companies are stepping in to fill the void. These include “peptide companies,” manufacturers that create non-FDA approved knockoff versions of the drugs.

From November 2023 to March 2024, my team carried out a study to assess which of these peptide companies are selling semaglutide or tirzepatide products. We scoured the internet looking for these peptide companies and collected information about what they were selling and their sales practices.

We found that peptide sellers use a loophole to sell these drugs. On their websites, the companies state that their drugs are for “research purposes only” or “not for human consumption,” but they do nothing to verify that the buyers are researchers or that the product is going to a research facility.

By reading the comments sections of the company websites and the targeted ads on social media, it becomes clear that both buyers and sellers understand the charade. Unlike compounding pharmacies, these peptide sellers do not provide the supplies you need to dissolve and inject the drug, provide no instructions, and will usually not answer questions.

Peptide sellers, since they allegedly are not selling to consumers, do not require a valid prescription and will sell consumers whatever quantity of drug they wish to purchase. Even if a person has an eating disorder such as anorexia nervosa, the companies will happily sell them a semaglutide or tirzepatide product without a prescription. The average prices of these peptide products range from $181-$203 per month.

Skirting regulations

Peptide sellers do not have to adhere to the rules or regulations that drug manufacturers or compounding pharmacies do. Many companies state that their products are 99% pure, but an independent investigation of three companies’ products from August 2023 to March 2024 found that the purity of the products were far less than promised.

One product contained endotoxin – a toxic substance produced by bacteria – suggesting that it was contaminated with microbes. In addition, the products’ promised dosages were off by up 29% to 39%. Poor purity can cause patients to experience fever, chills, nausea, skin irritation, infections and low blood pressure.

In this study, some companies never even shipped the drug, telling the buyers they needed to pay an additional fee to have the product clear customs.

If a consumer is harmed by a poor-quality product, it would be difficult to sue the seller, since the products specifically say they are “not for human consumption.” Ultimately, consumers are being led to spend money on products that may never arrive, could cause an infection, might not have the correct dose, and contain no instructions on how to safely use or store the product.

Will prices for brand-name products come down?

To combat these alternative sellers, pharmaceutical company Eli Lilly began offering an alternative version of its brand-name Zepbound product for weight loss in September 2024.

Instead of its traditional injection pen products that cost more than $1,000 for a month’s supply, this product comes in vials that patients draw up and inject themselves. For patients who take 5 milligrams of Zepbound each week, the vial products would cost them $549 a month if patients buy it through the company’s online pharmacy and can show that they do not have insurance coverage for the drug.

After a grilling on Capitol Hill in September 2024, pharmaceutical company Novo Nordisk came under intense pressure to offer patients without prescription coverage a lower-priced product for its brand-name Wegovy as well.

In the next few years, additional brand-name GLP-1 agonist drugs will likely make it to market. As of October 2024, a handful of these products are in late-phase clinical trials, with active ingredients such as retatrutide, survodutide and ecnoglutide, and more than 18 other drug candidates are in earlier stages of development.

When new pharmaceutical companies enter this market, they will have to offer patients lower prices than Eli Lilly and Novo Nordisk in order to gain market share. This is the most likely medium-term solution to drive down the costs of GLP-1 drugs and eliminate the drug shortages in the marketplace.

C. Michael White, Distinguished Professor of Pharmacy Practice, University of Connecticut

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Veera Sundararaghavan, University of Michigan

John J. Hopfield and Geoffrey E. Hinton received the Nobel Prize in physics on Oct. 8, 2024, for their research on machine learning algorithms and neural networks that help computers learn. Their work has been fundamental in developing neural network theories that underpin generative artificial intelligence.

A neural network is a computational model consisting of layers of interconnected neurons. Like the neurons in your brain, these neurons process and send along a piece of information. Each neural layer receives a piece of data, processes it and passes the result to the next layer. By the end of the sequence, the network has processed and refined the data into something more useful.

While it might seem surprising that Hopfield and Hinton received the physics prize for their contributions to neural networks, used in computer science, their work is deeply rooted in the principles of physics, particularly a subfield called statistical mechanics.

As a computational materials scientist, I was excited to see this area of research recognized with the prize. Hopfield and Hinton’s work has allowed my colleagues and me to study a process called generative learning for materials sciences, a method that is behind many popular technologies like ChatGPT.

What is statistical mechanics?

Statistical mechanics is a branch of physics that uses statistical methods to explain the behavior of systems made up of a large number of particles.

Instead of focusing on individual particles, researchers using statistical mechanics look at the collective behavior of many particles. Seeing how they all act together helps researchers understand the system’s large-scale macroscopic properties like temperature, pressure and magnetization.

For example, physicist Ernst Ising developed a statistical mechanics model for magnetism in the 1920s. Ising imagined magnetism as the collective behavior of atomic spins interacting with their neighbors.

In Ising’s model, there are higher and lower energy states for the system, and the material is more likely to exist in the lowest energy state.

One key idea in statistical mechanics is the Boltzmann distribution, which quantifies how likely a given state is. This distribution describes the probability of a system being in a particular state – like solid, liquid or gas – based on its energy and temperature.

Ising exactly predicted the phase transition of a magnet using the Boltzmann distribution. He figured out the temperature at which the material changed from being magnetic to nonmagnetic.

Phase changes happen at predictable temperatures. Ice melts to water at a specific temperature because the Boltzmann distribution predicts that when it gets warm, the water molecules are more likely to take on a disordered – or liquid – state.

In materials, atoms arrange themselves into specific crystal structures that use the lowest amount of energy. When it’s cold, water molecules freeze into ice crystals with low energy states.

Similarly, in biology, proteins fold into low energy shapes, which allow them to function as specific antibodies – like a lock and key – targeting a virus.

Neural networks and statistical mechanics

Fundamentally, all neural networks work on a similar principle – to minimize energy. Neural networks use this principle to solve computing problems.

For example, imagine an image made up of pixels where you only can see a part of the picture. Some pixels are visible, while the rest are hidden. To determine what the image is, you consider all possible ways the hidden pixels could fit together with the visible pieces. From there, you would choose from among what statistical mechanics would say are the most likely states out of all the possible options.

Hopfield and Hinton developed a theory for neural networks based on the idea of statistical mechanics. Just like Ising before them, who modeled the collective interaction of atomic spins to solve the photo problem with a neural network, Hopfield and Hinton imagined collective interactions of pixels. They represented these pixels as neurons.

Just as in statistical physics, the energy of an image refers to how likely a particular configuration of pixels is. A Hopfield network would solve this problem by finding the lowest energy arrangements of hidden pixels.

However, unlike in statistical mechanics – where the energy is determined by known atomic interactions – neural networks learn these energies from data.

Hinton popularized the development of a technique called backpropagation. This technique helps the model figure out the interaction energies between these neurons, and this algorithm underpins much of modern AI learning.

The Boltzmann machine

Building upon Hopfield’s work, Hinton imagined another neural network, called the Boltzmann machine. It consists of visible neurons, which we can observe, and hidden neurons, which help the network learn complex patterns.

In a Boltzmann machine, you can determine the probability that the picture looks a certain way. To figure out this probability, you can sum up all the possible states the hidden pixels could be in. This gives you the total probability of the visible pixels being in a specific arrangement.

My group has worked on implementing Boltzmann machines in quantum computers for generative learning.

In generative learning, the network learns to generate new data samples that resemble the data the researchers fed the network to train it. For example, it might generate new images of handwritten numbers after being trained on similar images. The network can generate these by sampling from the learned probability distribution.

Generative learning underpins modern AI – it’s what allows the generation of AI art, videos and text.

Hopfield and Hinton have significantly influenced AI research by leveraging tools from statistical physics. Their work draws parallels between how nature determines the physical states of a material and how neural networks predict the likelihood of solutions to complex computer science problems.

Veera Sundararaghavan, Professor of Aerospace Engineering, University of Michigan

This article is republished from The Conversation under a Creative Commons license. Read the original article.

Jane Tavares, UMass Boston and Marc Cohen, UMass Boston

Vice President Kamala Harris outlined a proposal to allow Medicare to expand its coverage of home health care for older Americans. The Democratic presidential nominee announced this plan on the television talk show “The View.”

Harris explained that she aimed to take the burden off members of the “sandwich generation,” who are taking care of their kids and aging parents at the same time. She said the cost of this additional paid care could be paid for with the money the government will save by negotiating with pharmaceutical companies to reduce what Medicare pays for prescription drugs.

The Conversation U.S. asked Jane Tavares and Marc Cohen, scholars of long-term care, to assess what’s known so far about the plan.

Why is long-term care significant?

Long-term services and supports are one of the most significant expenses for older adults. They range from nonmedical assistance with food preparation, bathing, dressing and other activities of daily living to medical care in a skilled nursing facility.

Today‘s 65-year-olds have a 70% chance of eventually needing some kind of long-term care as they age, and 20% will need long-term care for more than five years.

The costs associated with even one year of long-term care can prove to be unaffordable for most people. In 2023, the median yearly cost of a private room in a nursing home was US$116,796 and that of a home health care aide was $33 per hour. That’s $96,360 yearly for eight hours of daily in-home care.

The National Council on Aging has found that 80% of older adults would be unable to absorb a financial shock — such as the need for long-term care — without impoverishing themselves. The council noted that 20% of older adults had no assets at all, and another 60% would not be able to afford more than two years of either nursing home care or care in their own homes. The average length of a long-term care stay is just over three years.

Medicare currently does not cover any long-term care, but it does cover short-term professional in-home care for recovery after a qualifying illness or injury for up to 21 days and a maximum of 100 days in a skilled nursing facility after a qualifying hospital stay.

Medicaid currently covers about 61% of the country’s total long-term care costs, over 70% of which are for home-based services. However, Medicaid has strict income and asset eligibility requirements. Although Medicaid eligibility and coverage vary by state, those who qualify for the program are at or near the federal poverty level and have less than $2,000 in individual assets, or $3,000 as a couple.

Only 15% of Americans who were 65 and older were covered by Medicaid as of 2022.

Adding to the challenge, there is a shortage of long-term care workers. In 2022, about 700,000 people were on Medicaid waitlists for home- and community-based services, and 10% of those with skilled medical needs were waiting in hospitals for spots to open in nursing homes.

What would be the impact of increasing the number of older people getting care?

An estimated 77% of older Americans desire to stay in their homes as they age, but 1 in 5 need assistance with activities of daily living. With the high costs of long-term care and few coverage options, unpaid family caregivers typically provide this care.

Expanding Medicare coverage to include professional in-home long-term care, as Harris proposes, would make it easier for older adults to stay in their homes without impoverishing themselves. It could also help alleviate burdens born by unpaid family caregivers.

Although it will depend on details that weren’t immediately available, expanding long-term care coverage beyond the people who are enrolled in Medicaid has the potential to help many vulnerable older adults.

For example, getting professional assistance with eating or bathing could prevent health complications associated with malnutrition or poor hygiene. And this care would not be at the expense of a family caregiver who might otherwise have to leave their job or take on additional physical and mental stress to provide that care.

How much will this cost the government?

Clearly, the costs associated with any new program depend on many factors. The most important are who qualifies for the program, the circumstances under which they can get benefits, and how generous those benefits are.

Harris has indicated that the new Medicare home care benefit she’s proposing would be paid for by the savings from reductions in Medicare drug costs. A relatively recent estimate for that savings in 2026 is $6.3 billion. If this is the primary way to pay for the program, it could finance only a very modest home-care benefit.

Other long-term care proposals put forward by researchers and policymakers look at increasing the Medicare tax to pay for expanding access to this benefit. Here again, how much money needs to be raised depends on how comprehensive the program would be. Researchers at the Brookings Institution estimated that making long-term care more widely available to people covered by Medicare would probably cost about $40 billion.

Why hasn’t Medicare covered in-home care until now?

When it was originally launched in 1966, the Medicare program was intended to cover acute medical care services. At that time, life expectancy was lower than it is today – meaning that fewer Americans over 65 were eligible for its benefits and would live long enough to require long-term care.

In the following six decades, no public insurance program like Medicare has emerged to help people pay for this care.

But as far back as 1994, lawmakers were drafting proposals to cover long-term care. More recently, legislators have introduced bills that could fill this gap. However, many prior efforts have failed due to a lack of agreement on how to pay for these benefits and whether everyone should be eligible, or just low-income people.

Because the federal government hasn’t stepped up, some states have introduced their own policies.

Washington state is the furthest along in this effort. It has created a public long-term care insurance program where working Washington residents contribute a small percentage of their income into the fund and can then access earned benefits to pay for services. However, due to a ballot measure that Washington voters will weigh in on during the November 2024 elections, the program may become voluntary. We believe that letting people opt out would likely make that program unsustainable.

California has also made headway, completing two feasibility studies to examine the potential of a statewide long-term care insurance program. In 2024, California also eliminated the financial asset limits for Medicaid eligibility to help expand the program so it can cover more of the state’s older residents.

Jane Tavares, Senior Research Fellow and Lecturer of Gerontology, LeadingAge LTSS Center @UMass Boston, UMass Boston and Marc Cohen, Mel King Fellow, MIT CoLab; Clinical Professor of Gerontology and Co-Director LeadingAge LTSS Center, UMass Boston

This article is republished from The Conversation under a Creative Commons license. Read the original article.