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Our Science

Seragon aims its transformational medical advancements towards a simple goal: discovering long-term solutions for human & animal life.

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Home/Our Science/Our Focus Areas/Aging

Aging

Overview

Overview
Overview

Aging

Focus

Longevity is just within our reach with better technology and modern medicine. Aging is a natural consequence of cells as they undergo replication. Occasionally, coding errors may occur within the human genome and the processes responsible for maintaining the body’s normal function become dysfunctional. Body systems decline as individuals age, leading to age-associated health conditions such as Alzheimer’s Disease and Type II Diabetes. These conditions pose a difficult burden on the world’s health systems, thus we strive to find a solution by reversing the decline caused by the aging process.

As we identify cellular targets that can be modulated to restore metabolic function, we hope to indirectly reduce the physical and financial burden presented by these health conditions. We work towards achieving methods encompassing metabolism, genomics, and gene therapy, including genomic analysis and developing gene therapy vectors to restore their functions.

By understanding the ways in which mTOR and other genes are involved in the regulation of metabolic pathways, we aim to develop novel techniques toward slowing the human biological clock.

Research

Our techniques include determining biomarkers correlating with age and developing gene therapy vectors to restore their functions in genomic analysis. Our investigations additionally address research in molecules and mechanisms associated with metabolism, such as regulators of the mammalian target of rapamycin (mTOR) and nicotinamide adenine dinucleotide (NAD+) pathways. By understanding how these different areas of the human condition relate, we can expand our understanding of these age-related conditions.

Genomics

Through an extensive database of our research on human genomes, we developed machine learning algorithms that can assess an individual’s genome and identify markers of gene expression correlated with metabolic disorders and abnormal aging. This acts as an early predictive tool for health diagnostic purposes, and we believe the use of artificial intelligence may yield novel and accurate solutions to age-associated health conditions on a hereditary level.

Metabolism

Body systems decline as individuals age, leading to age-associated health conditions such as Alzheimer’s Disease and Type II Diabetes. These conditions pose a difficult burden on the world’s health systems and thus we strive to find a solution by reversing the decline caused by the aging process.

Our research on aging directly involves addressing the ways in which cellular metabolism changes over time. As we investigate controllers of mitochondrial function and cellular repair machineries, our findings suggest that a number of mTOR modulators may serve to improve age-associated health conditions with more research underway.

We are also actively investigating a class of proteins called sirtuins, which can be modulated by the presence of compounds such as nicotinamide adenine dinucleotide (NAD+). Deficiencies in sirtuin function can lead to large-scale repercussions such as the development of insulin resistance, a key symptom in the diagnosis of Type II diabetes. Our investigations aim to find efficient ways to replenish available NAD+ supply within cellular mitochondria, so that cells of older individuals may function at a renewed level.

Gene Therapy

Using data acquired from our genomics database, we can assess genes that can be targeted for modification.

Using AI-driven genomic platforms to compare an individual’s genome with a target population, we can identify early symptoms of altered homeostasis resulting from aging or metabolic conditions to develop a method which corrects this detrimental downregulation and upregulation changes, and restore corresponding biological functions with advanced gene delivery techniques.

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Metabolism

Understanding the underlying mechanisms behind metabolic disorders.

AI Bioinformatics

Artificial intelligence guiding the future of diagnostics.

Immunology

Discovering the central defence mechanism of the human body.

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Metabolism

Understanding the underlying mechanisms behind metabolic disorders.

AI Bioinformatics

Artificial intelligence guiding the future of diagnostics.

Immunology

Discovering the central defence mechanism of the human body.

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