Feeling drained and lethargic is common: A 2022 national survey found that 13.5% of U.S. adults said they felt “very tired” or “exhausted” most days or every day over a three-month period.

Women ages 18 to 44 had the highest rate of fatigue – just over 20%.

Being tired is linked to something deeper than just overwork or a sign of the times. I’m a registered dietitian and nutritional neuroscientist. My research, along with the work of others in the field, shows that your diet and lifestyle choices may contribute to your struggles. These two factors are closely interconnected and could be the key to understanding what’s holding you back.

In particular, not getting enough of three essential nutrients – vitamin D, vitamin B12 and omega-3 fatty acids – is linked to low energy levels.

Vitamin D

More than 40% of adult Americans are deficient in vitamin D. Low levels are linked to fatigue, bone pain, muscle weakness, mood disorders and cognitive decline.

Foods high in vitamin D include fatty fish like salmon, sardines, freshwater rainbow trout, fortified dairy products and egg yolks. Among the sources for vegetarians and vegans are fortified plant-based milks and cereals and some kinds of mushrooms.

The U.S. government’s recommended daily amount of vitamin D is 400 international units, or IU, for infants up to 12 months, 600 IU for people ages 1 to 70 and 800 IU for people over 70. Just over 5 ounces (150 grams) of sockeye salmon fillet has about 800 IU of vitamin D. If you are low in a vitamin, your doctor may prescribe you a higher dose than the recommended daily amount to elevate your blood levels to normal.

Vitamin B12

About 20% of Americans have inadequate vitamin B12 levels, which can impair energy production and lead to anemia, resulting in fatigue.

Low levels of B12 are notably higher in older people, pregnant and lactating women, people with gastrointestinal disorders like inflammatory bowel disease, those who take certain medications like proton-pump inhibitors, and people with alcohol use disorder.

Because vitamin B12 is primarily found in meat, fish, dairy and eggs, vegetarians and vegans should consider taking a vitamin B12 supplement. The recommended daily amount for anyone ages 4 and older is 2.4 micrograms, about what’s found in 3 ounces of tuna or Atlantic salmon. Pregnant and breastfeeding women require slightly more.

Taking B12 supplements can be as effective as getting the vitamin from food – and taking the supplement with food may enhance its absorption.

That said, here’s a note on supplements in general: While they can be beneficial, they shouldn’t replace whole foods.

Not only are supplements less strictly regulated by the Food and Drug Administration compared to prescription and over-the-counter drugs, making their potency uncertain, but real food also provides a complex array of nutrients that work in a synergistic way. Many supplements on the market boast multiple servings of vegetables, but nothing beats the actual food.

Omega-3 fatty acids

About 87% of adults ages 40 to 59, and about 80% of those 60 and older, don’t get enough omega-3 fatty acids to meet dietary recommendations. Neither do many pregnant women.

Omega-3 fatty acids are crucial for brain health, and a deficiency can lead to higher anxiety and depression levels and impaired cognitive function. Taken together, these deficiencies can add to fatigue.

The best sources of omega-3 fatty acids are fatty fish, but if you’re strictly vegan, flaxseeds, chia seeds and walnuts can be great alternatives. However, it’s worth noting the omega-3s in fish are absorbed better in the body than plant sources – and that determines how efficiently the body can use the omega-3.

Also, whole flaxseed has a tough outer shell, which makes it more difficult to digest and absorb its nutrients. But ground flaxseed has been broken down, making the omega-3s and other nutrients more available for absorption.

The role of alcohol

Although alcohol may provide a sense of relaxation in the moment, it actually contributes to fatigue after the buzz wears off. Alcohol is a toxin; it forces your body to prioritize its metabolism over that of nutrients, which means the body reduces the use of carbohydrates and fat for energy.

Alcohol also reduces the absorption of B vitamins, which consequently affects energy production. The bottom line: If you drink alcohol, ultimately you will feel tired.

Lifestyle factors

Diet isn’t everything. Sunlight, exercise, better sleep and stress management are all critical factors for reducing fatigue.

Your body can make vitamin D from sunlight, and you don’t need a lot. A few minutes up to a half hour of sun exposure can help most people get what they need. The amount of time can vary depending on where you live, how much clothing you wear and what time of year you get the exposure. You’ll reach your vitamin D daily quota much faster on a sunny day during the summer than a cloudy day in winter.

And it may sound counterintuitive, but the more you exercise, the more energy you will produce; working out doesn’t drain you. Instead, it boosts energy, along with mood, by improving blood flow and helping to release endorphins, which are hormones produced by the body to relieve pain or stress.

Without exercise, the human body becomes less efficient at producing energy, which leads to lethargy. Coupled with erratic blood sugar levels – often caused by diets high in refined sugars and low in nutrients – these energy dips and spikes can leave you feeling irritable and drained.

Aim for at least 150 minutes of moderate exercise each week through activities like brisk walking, cycling, swimming and strength training.

Poor sleep makes things even worse. Not getting enough rest disrupts the body’s natural recovery processes and will leave you with diminished energy and focus.

So you should try to get seven to nine hours of quality sleep each night. For some people this is not easy; creating a calming bedtime routine helps, and limiting screen time is key.

Avoid phones, computers and other screens for at least 30 to 60 minutes before bed. The blue light emitted from screens can interfere with your body’s production of melatonin, a hormone that helps regulate sleep. Conversely, activities like reading, meditation or gentle stretching help signal to your body that it’s time to sleep.

In short, there are things you can do about your fatigue. Smart choices help optimize mood, energy levels and overall health, and reduce the surges of sluggishness you feel throughout the day.

Make no mistake: Your diet and lifestyle can make all the difference between being alert or wiped out.

Lina Begdache, Associate Professor of Health and Wellness Studies, Binghamton University, State University of New York

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

The potential of using artificial intelligence in drug discovery and development has sparked both excitement and skepticism among scientists, investors and the general public.

“Artificial intelligence is taking over drug development,” claim some companies and researchers. Over the past few years, interest in using AI to design drugs and optimize clinical trials has driven a surge in research and investment. AI-driven platforms like AlphaFold, which won the 2024 Nobel Prize for its ability to predict the structure of proteins and design new ones, showcase AI’s potential to accelerate drug development.

AI in drug discovery is “nonsense,” warn some industry veterans. They urge that “AI’s potential to accelerate drug discovery needs a reality check,” as AI-generated drugs have yet to demonstrate an ability to address the 90% failure rate of new drugs in clinical trials. Unlike the success of AI in image analysis, its effect on drug development remains unclear.

We have been following the use of AI in drug development in our work as a pharmaceutical scientist in both academia and the pharmaceutical industry and as a former program manager in the Defense Advanced Research Projects Agency, or DARPA. We argue that AI in drug development is not yet a game-changer, nor is it complete nonsense. AI is not a black box that can turn any idea into gold. Rather, we see it as a tool that, when used wisely and competently, could help address the root causes of drug failure and streamline the process.

Most work using AI in drug development intends to reduce the time and money it takes to bring one drug to market – currently 10 to 15 years and US$1 billion to $2 billion. But can AI truly revolutionize drug development and improve success rates?

AI in drug development

Researchers have applied AI and machine learning to every stage of the drug development process. This includes identifying targets in the body, screening potential candidates, designing drug molecules, predicting toxicity and selecting patients who might respond best to the drugs in clinical trials, among others.

Between 2010 and 2022, 20 AI-focused startups discovered 158 drug candidates, 15 of which advanced to clinical trials. Some of these drug candidates were able to complete preclinical testing in the lab and enter human trials in just 30 months, compared with the typical 3 to 6 years. This accomplishment demonstrates AI’s potential to accelerate drug development.

On the other hand, while AI platforms may rapidly identify compounds that work on cells in a Petri dish or in animal models, the success of these candidates in clinical trials – where the majority of drug failures occur – remains highly uncertain.

Unlike other fields that have large, high-quality datasets available to train AI models, such as image analysis and language processing, the AI in drug development is constrained by small, low-quality datasets. It is difficult to generate drug-related datasets on cells, animals or humans for millions to billions of compounds. While AlphaFold is a breakthrough in predicting protein structures, how precise it can be for drug design remains uncertain. Minor changes to a drug’s structure can greatly affect its activity in the body and thus how effective it is in treating disease.

Survivorship bias

Like AI, past innovations in drug development like computer-aided drug design, the Human Genome Project and high-throughput screening have improved individual steps of the process in the past 40 years, yet drug failure rates haven’t improved.

Most AI researchers can tackle specific tasks in the drug development process when provided with high-quality data and particular questions to answer. But they are often unfamiliar with the full scope of drug development, reducing challenges into pattern recognition problems and refinement of individual steps of the process. Meanwhile, many scientists with expertise in drug development lack training in AI and machine learning. These communication barriers can hinder scientists from moving beyond the mechanics of current development processes and identifying the root causes of drug failures.

Current approaches to drug development, including those using AI, may have fallen into a survivorship bias trap, overly focusing on less critical aspects of the process while overlooking major problems that contribute most to failure. This is analogous to repairing damage to the wings of aircraft returning from the battle fields in World War II while neglecting the fatal vulnerabilities in engines or cockpits of the planes that never made it back. Researchers often overly focus on how to improve a drug’s individual properties rather than the root causes of failure.

The current drug development process operates like an assembly line, relying on a checkbox approach with extensive testing at each step of the process. While AI may be able to reduce the time and cost of the lab-based preclinical stages of this assembly line, it is unlikely to boost success rates in the more costly clinical stages that involve testing in people. The persistent 90% failure rate of drugs in clinical trials, despite 40 years of process improvements, underscores this limitation.

Addressing root causes

Drug failures in clinical trials are not solely due to how these studies are designed; selecting the wrong drug candidates to test in clinical trials is also a major factor. New AI-guided strategies could help address both of these challenges.

Currently, three interdependent factors drive most drug failures: dosage, safety and efficacy. Some drugs fail because they’re too toxic, or unsafe. Other drugs fail because they’re deemed ineffective, often because the dose can’t be increased any further without causing harm.

We and our colleagues propose a machine learning system to help select drug candidates by predicting dosage, safety and efficacy based on five previously overlooked features of drugs. Specifically, researchers could use AI models to determine how specifically and potently the drug binds to known and unknown targets, the level of these targets in the body, how concentrated the drug becomes in healthy and diseased tissues, and the drug’s structural properties.

These features of AI-generated drugs could be tested in what we call phase 0+ trials, using ultra-low doses in patients with severe and mild disease. This could help researchers identify optimal drugs while reducing the costs of the current “test-and-see” approach to clinical trials.

While AI alone might not revolutionize drug development, it can help address the root causes of why drugs fail and streamline the lengthy process to approval.

Duxin Sun, Associate Dean for Research, Charles Walgreen Jr. Professor of Pharmacy and Pharmaceutical Sciences, University of Michigan and Christian Macedonia, Adjunct Professor in Pharmaceutical Sciences, University of Michigan

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