Month: January 2023

Leqembi (lecanemab-irmb), a medication for treating Alzheimer’s, received approval from the U.S. Food and Drug Administration via the Accelerated Approval pathway on January 6th, 2023. Leqembi is the second drug in a newly approved class for Alzheimer’s that addresses the illness’s basic pathophysiology. These drugs are a significant step forward in the ongoing endeavor to find an effective treatment for the disease.

The Accelerated Approval pathway allows the FDA to approve medications for life-threatening illnesses when there is an unmet medical need and that medicine has shown to have an impact on a surrogate endpoint that is relatively likely to predict a clinical benefit for patients.

According to the press release, Billy Dunn, MD, head of the neuroscience division of the FDA’s Center for Drug Evaluation and Research, stated, “This treatment option is the latest therapy to target and affect the underlying disease process of Alzheimer’s, instead of only treating the symptoms of the disease.”

The approval came following a review of Phase III randomized controlled clinical trial data published in The New England Journal of Medicine in November 2022. The findings demonstrated that Leqembi (lecanemab-irmb, Eisai) lowered amyloid markers in early Alzheimer’s and resulted in less cognitive and functional decline. According to the news release, the agency would soon receive the trial’s results to verify the drug’s clinical benefit. Eisai R&D Management Co., Ltd. received approval for Leqembi.

Results of the Clinical Trials for Leqembi

Researchers assessed the efficacy of Leqembi in a double-blind, placebo-controlled, parallel-group, dose-finding study comprising 856 Alzheimer’s patients. Patients with mild cognitive impairment (MCI) or mild dementia stage of the disease and confirmed presence of amyloid beta pathology underwent treatment.

Patients who received the recommended dose of lecanemab, 10 mg/kilogram every two weeks, saw a considerable time- and dose-dependent reduction in the amount of amyloid beta plaque. It demonstrated a statistically significant decrease in brain amyloid plaque from baseline to Week 79 when compared to the placebo arm, which showed no decline in amyloid beta plaque.

These findings support Leqembi’s Accelerated approval, which is justified by the reported decline in amyloid-beta plaque levels, a sign of Alzheimer’s disease. Researchers quantified the amyloid beta plaque via positron emission tomography (PET) imaging to compare the levels of amyloid beta plaque in a composite of brain regions expected to be severely affected by the pathology of Alzheimer’s to a brain region expected to be spared from such pathology.

Prescribing Information for Leqembi

Leqembi comes with a warning for amyloid-related imaging abnormalities (ARIA), which are known to happen with the antibodies from this class. ARIA is typically asymptomatic, though severe and life-threatening events are rare.

Although some patients may experience symptoms like headache, disorientation, dizziness, altered vision, nausea, and seizures, the most common sign of ARIA is transient swelling in brain regions that often goes away with time.

Besides, there is also a possibility of infusion-related responses, which can cause flu-like symptoms, nausea, vomiting, and changes in blood pressure. Leqembi’s most frequent adverse effects included headache, ARIA, and infusion-related problems.

Leqembi is intended for Alzheimer’s treatment, as stated in the prescribing information. According to the labeling, Leqembi treatment should begin in patients with mild cognitive impairment or mild dementia stage of disease, the population in whom treatment was evaluated in clinical trials. Additionally, the labeling states that there are no safety or efficacy data regarding starting the treatment at earlier or later stages of the disease than were investigated.

References

1. FDA Grants Accelerated Approval for Alzheimer’s Disease Treatment. FDA News Release. Published online: 6th Jan, 2023. https://www.fda.gov/news-events/press-announcements/fda-grants-accelerated-approval-alzheimers-disease-treatment. Accessed: 10th Jan, 2023.
2. van Dyck, C.H., Swanson, C.J., Aisen, P., Bateman, R.J., Chen, C., Gee, M., Kanekiyo, M., Li, D., Reyderman, L., Cohen, S. and Froelich, L., 2022. Lecanemab in early Alzheimer’s disease. New England Journal of Medicine. https://www.nejm.org/doi/full/10.1056/NEJMoa2212948
3. FDA grants accelerated approval for Leqembi. European Pharmaceutical Review. Published online: 9th Jan, 2023. https://www.europeanpharmaceuticalreview.com/news/178331/fda-grants-accelerated-approval-for-leqembi-alzheimers/. Accessed: 10th Jan, 2023.
4. FDA grants accelerated approval for Alzheimer’s treatment. Healio.com. Published online: 6th Jan, 2023. https://www.healio.com/news/neurology/20230106/fda-grants-accelerated-approval-for-alzheimers-treatment. Accessed: 10th Jan, 2023.

According to researchers, the artificial intelligence that powers the chatbot program ChatGPT—famous for its capacity to produce human-like responses when instructed—could aid in the early detection of Alzheimer’s.

Recent research from Drexel University’s School of Biomedical Engineering, Science, and Health Systems has revealed that the GPT-3 program from OpenAI can recognize cues from spontaneous speech that are 80% accurate in identifying the early stages of dementia.

The Drexel study is the most recent in a line of efforts to demonstrate the efficacy of natural language processing programs for Alzheimer’s early detection by drawing on recent findings that language impairment may serve as an early sign of neurodegenerative diseases.

Detecting an Early Sign

Doctors usually perform a thorough assessment of medical history and a battery of physical and neurological examinations and tests as part of the standard procedure for diagnosing Alzheimer’s today. The illness still has no known cure, but early discovery can give patients more therapeutic and support options.

Language deterioration is a symptom in 60-80% of people with dementia. Therefore, researchers have focused on programs that can detect subtle clues, such as hesitation, grammar and pronunciation errors, and forgetting the meaning of words, as a quick test that could imply whether or not a patient should undertake a complete examination.

Hualou Liang, Ph.D., a co-author of the research, stated that in addition to cognitive tests, the most commonly used tests for early detection of Alzheimer’s look at acoustic features such as pausing, articulation, and vocal quality. The researchers believe that advancements in natural language processing programs may provide another avenue for supporting early Alzheimer’s detection.

GPT-3: A Program that Listens and Learns

The third generation of OpenAI’s General Pretrained Transformer (GPT), GPT-3, employs a deep learning algorithm trained by analyzing extensive amounts of internet data with an emphasis on word usage and linguistic construction. Through this training, it can produce a human-like response to any language-related task, including answering straightforward questions and crafting poetry or essays.

GPT-3 excels in “zero-data learning,” the ability to respond to queries without any need for external knowledge that is usually required. For instance, asking the program to write “Cliff’s Notes” on a text would necessitate an explanation that this means a summary. However, GPT-3 has received enough training to understand the reference and adjust itself to generate the expected response.

According to Felix Agbavor, the lead author of the study, because of its systematic approach to language analysis and production, GPT3 is a good contender for figuring out the minute speech cues that could indicate the beginning of dementia. Training GPT-3 with a colossal dataset of interviews, some of which are with Alzheimer’s patients, would give it the information it needs to extract speech patterns, which could help identify markers in future patients.

Looking for Speech Cues

The researchers tested their theoretical hypothesis by feeding the algorithm a collection of transcripts from a sample of a dataset of voice recordings compiled to evaluate natural language processing programs’ capacity to predict dementia. The computer tool extracted significant word usage, sentence construction, and meaning traits from the text to create what academics refer to as an “embedding”—a distinctive profile of Alzheimer’s speech.

They then retrained the software using the embedding, converting it into a device for diagnosing Alzheimer’s. To test it, they instructed the program to examine dozens of transcripts from the dataset and determine whether or not each one was written by an individual who was developing Alzheimer’s.

The team tested two of the best natural language processing tools side by side and discovered that GPT-3 outperformed both in terms of accurately identifying Alzheimer’s examples, identifying Alzheimer’s non-examples, and with rarer missed cases than both programs.

A second test used textual analysis from the GPT-3 to predict patients’ results on the Mini-Mental State Exam, a standard test for assessing the degree of dementia (MMSE).

The research team then compared the accuracy of the GPT-3 forecast to that of an analysis that predicted the MMSE score only based on the acoustic characteristics of the recordings, such as voice strength, pauses, and slurring. GPT-3 was nearly 20% more accurate in predicting MMSE scores in patients.

What do the results imply?

According to the researchers, the results showed that the text embedding produced by GPT-3 could be consistently utilized to distinguish between people who have Alzheimer’s and healthy controls and to infer the subject’s cognitive assessment score, both exclusively based on speech data.

They also demonstrated that text embedding performs better than the traditional acoustic feature-based method and even competes with tuned models. These findings collectively imply that GPT-3 based text embedding is a promising method for assessing Alzheimer’s and has the potential to enhance early diagnosis of dementia.

The researchers intend to build on these encouraging findings by creating a web application that people might use as a pre-screening tool at home or a doctor’s office.

References

1. Agbavor, F. and Liang, H., 2022. Predicting dementia from spontaneous speech using large language models. PLOS Digital Health, 1(12), p.e0000168. https://journals.plos.org/digitalhealth/article?id=10.1371/journal.pdig.0000168.
2. Can the AI Driving ChatGPT Help to Detect Early Signs of Alzheimer’s Disease?. Science Daily. https://www.sciencedaily.com/releases/2022/12/221222162415.htm. Accessed: 6th Jan, 2023.
3. Can the AI Driving ChatGPT Help to Detect Early Signs of Alzheimer’s Disease?. Neuroscience.com. https://neurosciencenews.com/chatgpt-dementia-ai-22133/. Accessed: 6th Jan, 23.

The prevalence of neurodegenerative conditions like Alzheimer’s disease rises as the population ages. Proteinopathies, abnormal protein buildups in the brain that impede neuronal function, distinguish these disorders. For instance, the accumulation of beta-amyloid and tau proteins is responsible for Alzheimer’s. Trying to lessen amyloid-beta peptide and tau protein aggregation in neurons is the most extensively researched therapeutic method for developing medications to treat Alzheimer’s.

However, the medications must first pass across the blood-brain barrier (BBB) to reach their targets in the brain. Endothelial cells, which line the smallest blood vessels in the brain, regulate the exchange of blood and the brain. They maintain a balance that enables vital molecules like glucose to pass through while restricting the entry of most pharmaceuticals, including the latest and much-hyped drug, lecanemab.

The equilibrium becomes disturbed when these brain endothelial cells acquire a disease. The brain fights to get the molecules it needs back into the bloodstream and rejects those that could harm it. The brain and other body organs are thus constantly communicating, whether in health or disease.

Insulin and the Brain

The hormone insulin is necessary for life. It continues to be a crucial component of diabetes pharmaceutical treatment because of its impact on blood sugar management, for which it is best recognized. Researchers have discovered vascular and metabolic problems in a sizable proportion of dementia patients in recent years.

Indeed, Type 2 diabetes, in which insulin resistance occurs in the later stages, is a significant Alzheimer’s risk. Some published data point to reduced insulin sensitivity in the Alzheimer’s brain. While some other studies have indicated that insulin can enhance memory, leading to the initiation of clinical trials on insulin’s impact on Alzheimer’s.

However, we are still unaware of the cell types and mechanisms responsible for insulin’s effect on the brain and its lack of action. The pancreas produces the majority of insulin and secretes it into the blood. For insulin to affect the brain, it must first interact with the BBB and its endothelial cells, which are in direct touch with the blood and have receptors for insulin.

The Insulin Receptors and Alzheimer’s

According to a cohort study, the site of insulin-binding receptors is predominantly in the microvessels, so BBB itself. Additionally, people with Alzheimer’s have less of this receptor overall. A decline of insulin responsiveness in the Alzheimer’s brain could result from this decline.

The researchers also tested their hypothesis in mice to more precisely regulate the experimental factors and gauge the insulin receptor’s reaction. In situ cerebral perfusion involves injecting insulin directly into the carotid artery, a neck artery, to ensure it fully reaches the brain. They claim that microvessels in the brain are where circulating insulin primarily stimulates receptors.

Despite the widespread belief that insulin penetrates the BBB to reach deeper-lying brain tissue cells like neurons, their findings indicated that only a tiny percentage of insulin does so. Thus, these two findings support the idea that the bulk of insulin must interact with BBB cells before affecting the brain.

The researchers also treated transgenic genetically altered to imitate Alzheimer’s using the same approach. They discovered that in these diseased mice, there was no activation of the insulin receptor, and the response to insulin at the BBB was defective.

Thus, the research established that the brain insulin receptor is present predominantly at the BBB in both humans and animals, and Alzheimer’s impairs its capacity to respond to blood insulin.

A Substantial Advancement

In conclusion, the findings imply that changes in insulin receptor quantity, conformation, and function at the level of BBB endothelial cells may be a factor in the cerebral insulin resistance seen in Alzheimer’s.

The researchers further proposed a study alternative with two chief advantages by focusing on metabolic dysfunction in the brain instead. The first is that since the endothelial cells become the therapeutic target, they can use treatments that do not need to pass the BBB barrier. The second strategy is “drug repurposing,” which entails leveraging the extraordinary treatment arsenal already authorized to combat diabetes and obesity in the setting of Alzheimer’s.

It should be kept in mind that the few medications we have only slightly improve symptoms. Trying to combat insulin resistance in the brain would allow researchers to break the vicious circle between neuropathology (brain disease) and diabetes, potentially slowing the disease’s progression.

Reference

1. Biessels, G.J. and Despa, F., 2018. Cognitive decline and dementia in diabetes mellitus: mechanisms and clinical implications. Nature Reviews Endocrinology, 14(10), pp.591-604.
2. Arnold, S.E., Arvanitakis, Z., Macauley-Rambach, S.L., Koenig, A.M., Wang, H.Y., Ahima, R.S., Craft, S., Gandy, S., Buettner, C., Stoeckel, L.E. and Holtzman, D.M., 2018. Brain insulin resistance in type 2 diabetes and Alzheimer disease: concepts and conundrums. Nature Reviews Neurology, 14(3), pp.168-181.
3. Kellar, D. and Craft, S., 2020. Brain insulin resistance in Alzheimer’s disease and related disorders: mechanisms and therapeutic approaches. The Lancet Neurology, 19(9), pp.758-766.
4. Leclerc, M., Bourassa, P., Tremblay, C., Caron, V., Sugère, C., Emond, V., Bennett, D.A. and Calon, F., 2021. Cerebrovascular insulin receptors are defective in Alzheimerˈs disease. bioRxiv.
5. Why does the Alzheimer’s brain become insulin-resistant?. The Conversation. https://theconversation.com/why-does-the-alzheimers-brain-become-insulin-resistant-196016. Accessed: 28/12/2022.