For many of us, today, September 21st is more than just the final day before the start of the autumn season. It’s a day we reflect and celebrate the lives of our loved ones who are affected by Alzheimer’s disease by recognizing World Alzheimer’s Day. World Alzheimer’s Day is a chance to peer into the 100 year history and challenges of tackling this devastating condition.
Alzheimer's disease is a relentless and progressive neurological disorder, impacting millions of patients and families worldwide. As the most common form of dementia, Alzheimer’s primarily affects cognitive function, behaviors, and motor skills. People with Alzheimer’s have symptoms that alter memory, learning ability, decision making and personality. These hallmarks of disease interfere with their daily lives. As the disease progresses, people may start having hallucinations and encounter challenges being self-sufficient.
Despite advancements in medical science, Alzheimer’s remains a complex puzzle, with ongoing research striving to uncover its causes, prevention, detection, and treatment. The risk of developing Alzheimer's increases significantly with age, particularly after the age of 65. According to the Alzheimer’s Association, about 6.9 million people in that age group in the United States will have Alzheimer’s in 2024. The prevalence of the disease doubles approximately every five years after age 65. With the population demographic shifting, and the proportion of elderly individuals increasing, the incidence of Alzheimer’s disease is expected to rise. Without a medical breakthrough, 13.8 million people in the US may have the disease by 2060. While these statistics may feel daunting, advancements in both research science and technology are bringing a refreshed sense of hope to the mission to treat Alzheimer’s disease and improve the lives of those afflicted.
Early detection of Alzheimer's is crucial for managing the disease and improving the quality of life for those affected. Patients with early detection have a headstart on preserving mental function, slowing the disease, and gaining access to support. Conventional diagnosis techniques include psychiatric evaluation, clinical assessments, cognitive tests, lab tests, and brain imaging such as MRI, CT scan, PET scan. However, these methods often detect the disease only after significant brain change has occurred, which may be too late for early intervention.
However, recent advances in technology including AI have emerged as a key tool in helping physicians reach a diagnosis sooner. In particular, AI is able to analyze brain scans, detect subtle changes in brain structure, and identify patterns that may indicate early-stage Alzheimer's disease. Additionally, AI is helping identify biomarkers, such as proteins specific to Alzeheimer’s disease in the blood or cerebrospinal fluid. These breakthroughs are promising, suggesting that early detection leading to early intervention could be in our near future.
There is currently no cure for Alzheimer’s disease and unfortunately most research of the last several decades has led to dead ends. Current treatment focuses on managing symptoms and slowing disease progressions. Most medications approved by the FDA treat Alzheimer’s symptoms and are effective only for a limited time because they can’t slow the neuron damage.
There are a few medications that have been tried to slow disease progression, but none have been significant. Aduhelm was the first of this type of drug approved by FDA, but in early 2024 its drugmaker Biogen decided to discontinue the treatment . Eli Lilly also developed a drug, donanemab, which was approved by the FDA in June 2024. Donanemab is a monoclonal antibody treatment. These antibodies bind to the amyloid proteins which builds up in the brain in the early stages of Alzheimer’s disease. This treatment is less effective in the later stages of the disease.
The drug discovery and development process is long and costly. Further, the exact mechanism of Alzheimer's disease is not fully understood. These hurdles create a challenging path forward in rapidly discovering an effective treatment for Alzheimer’s.
A novel, step-function change in approach is needed if we are to make any real advance in treating Alzheimer’s disease.
At SandboxAQ, we have been developing a revolutionary platform to address drug discovery and development. We have trained Large Quantitative Models (LQM’s) which can help solve some of the most challenging drug discovery problems, like neurodegenerative diseases. We understand that unique problems deserve specialized technology and methodologies to drive those medical advancements. For these reasons, we have partnered with UCSF’s Institute for Neurodegenerative Diseases to accelerate their drug discovery efforts. Our free energy perturbation technology, AQ-FEP, has enabled the Institute to identify many novel neurodegenerative targets.
“Our collaboration with SandboxAQ is accelerating lead optimization and is on track to take several years off our discovery timelines,” said Dr. Stanley B. Prusiner, Nobel laureate and director of the Institute. “Our return on value from the SandboxAQ platform is substantial, as it is helping us get to clinical trials much faster with the best possible molecules for achieving a successful outcome.”
With this ongoing collaboration, SandboxAQ is committed to enabling the drug discovery efforts of those searching for treatments of neurodegenerative diseases, including Alzheimer’s disease.
Leveraging first principles of physics, our models are taking a novel approach to the challenges of addressing this disease. On this World Alzheimer’s Day we recommit ourselves to this important journey to improve the lives of patients and families affected by Alzheimer’s disease.
Authors:
Lauren Winkler is a Computational Chemistry Postdoctoral Fellow in the AISim Group at SandBoxAQ. Previously, Lauren completed her Ph.D. in Medicinal Chemistry at the University of Utah, with a focus on computational modeling of biomolecules. Her work at SandBox AQ centers on development and implementation of computational methods to enhance drug discovery efforts in the neurodegenerative disease space.
Atashi Basu is the Head of Products at SandboxAQ. She has a background in Computational Chemistry with a PhD in Chemistry from the University of Cologne and postdoctoral research experience in Chemical Engineering from Stanford University. She has more than 15 years of experience in developing products in data science applications, image processing, computational materials and process modeling.
