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Related Concept Videos

Alzheimer's Disease: Treatment01:22

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Alzheimer's Disease (AD), a neurodegenerative disorder, is pathologically identified by amyloid plaques and neurofibrillary tangles composed of tau protein. AD pharmacotherapy aims to manage cognitive symptoms, delay disease progression, and treat behavioral symptoms. The treatment is primarily symptomatic and palliative, with no definitive disease-modifying therapy available. Cholinesterase inhibitors, including donepezil (Aricept), rivastigmine (Exelon), and galantamine (Razadyne), are...
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Alzheimer's Disease (AD) is a continually advancing neurodegenerative disorder, distinguished by escalating memory loss, cognitive dysfunction, and dementia. The disease unfolds in three stages: preclinical, mild cognitive impairment (MCI), and dementia. Its onset is insidious, and the progression gradual, with the cause not well explained by other disorders.
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Dementia is a collective term for cognitive disorders primarily affecting memory, thinking, and reasoning. It is not a specific disease but a syndrome, with Alzheimer's disease being the most common cause, accounting for approximately 60-80% of cases. Other types include vascular dementia, Lewy body dementia, and frontotemporal dementia. Dementia affects millions worldwide, particularly older adults, though it is not a normal part of aging.
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Cognitive enhancers, also known as "smart drugs," are substances used to enhance memory, mental alertness, and concentration. These can be natural or synthetic and improve cognition in conditions like Alzheimer's disease (AD) and other neurodegenerative diseases. Some common examples include caffeine, amphetamines, methylphenidate, modafinil, arecoline, donepezil, vortioxetine, and piracetam. These enhancers work on the principle of synaptic plasticity and altered circuit function.
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Related Experiment Video

Updated: Jul 19, 2025

A Machine Learning Approach to Design an Efficient Selective Screening of Mild Cognitive Impairment
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Artificial intelligence for dementia drug discovery and trials optimization.

Thomas Doherty1,2, Zhi Yao3, Ahmad A L Khleifat4

  • 1Eisai Europe Ltd, Hatfield, UK.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|August 17, 2023
PubMed
Summary

Machine learning and big data analytics can accelerate dementia drug discovery and clinical trial design. Overcoming challenges requires a multidisciplinary approach to harness data-driven insights for therapeutic advancements.

Keywords:
Alzheimer's Diseaseartificial Intelligencebig dataclinical trialsdementiadrug discoverymachine learning

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Area of Science:

  • Neuroscience
  • Computational Biology
  • Clinical Trials

Background:

  • Dementia drug discovery and clinical trial design face significant hurdles due to patient variability, disease duration, and target accessibility.
  • Historical challenges have slowed therapeutic progress in neurodegenerative diseases.

Purpose of the Study:

  • To review the current applications of machine learning (ML) in dementia drug discovery and clinical trial design.
  • To identify opportunities and propose recommendations for overcoming implementation barriers.

Main Methods:

  • Review of existing literature on ML applications in drug discovery and clinical trial design.
  • Analysis of big data analytics potential in addressing therapeutic challenges.

Main Results:

  • ML and big data offer potential to accelerate dementia therapy development by improving target identification and trial design.
  • Large medical datasets enable data-driven insights for key clinical and therapeutic questions.

Conclusions:

  • A multidisciplinary approach is crucial for effective data-driven decision-making in dementia research.
  • Addressing current challenges will unlock the full potential of ML and big data in dementia drug discovery and clinical trials.