Diagnostic technologies are currently one of the most explored studies in medical biotechnology, where research areas such as genomic sequencing are greatly advancing our current approach to diagnosing and treating human disease and conditions. By uncovering greater knowledge about the diversity of human health, Seragon is delivering better outcomes for patients by harnessing technologies like Artificial intelligence to develop better precision therapies and approaches.
Diagnostic research
We aim to make breakthroughs in patient care with diagnostic outcomes that integrate clinical and real-world data to present targeted, actionable information about patients' health. Our research leads to greater insight about the genetic basis of disease, and how we can use this information to create more personalised patient care with better diagnostic technologies.
Areas like genetic testing can help people identify inherited disorders- including mutations that drive cancer progression- and are a valuable approach to disease research to characterise where genetically inherited conditions can be possibly treated. We aim to make diagnostic information more accurate, precise, and actionable for patients to understand their personal health needs and obtain the best method of care.
One of Seragon Pharmaceuticals' technologies is an advanced artificial intelligence analytic tool that seeks to enlighten the patient on the epigenetic changes going on within their cells. Not only does such technology serve to enhance patient outcomes, but it also supports health care professionals with greater insight into individual health assessments and provide the best method of care.
GenomeScore™
Based on algorithms that continuously improve through machine learning, GenomeScore™'s epigenetic interface analyses your genome from a number of non-intrusive sources including saliva or blood samples to reveal your genome's personal performance.
The system's findings compare your results to the general population to reveal your genome's personal performance. Its algorithms generate a customised report of a patient's personalized health assessment, which can be privately and conveniently accessed and shared with health providers to deliver a qualitative assessment backed by clinical judgment.
Artificial intelligence analysis
Genomics is a comprehensive field which bridges small-scale modifications at the genetic level with large-scale implications. With the growing power and advancements of artificial intelligence (AI), we can streamline research through deep learning and data analysis from collections of human-reviewed data to develop algorithms that allow us to interpret trends and predict outcomes with greater accuracy.
The strength of AI-driven genomics is apparent where a trained AI network’s pattern recognition abilities can be utilized. The combination of genomic analysis systems with computer vision algorithms has been used to guide diagnostics of cancer treatment and genetic disorders, providing a more efficient way of processing and classifying data points to improve predictions in genome analysis and weigh in human factors that influence our results.
Using data
The vast quantity of data being generated today has huge potential to increase access to integrated datasets and medical data storage that are critical to advancing personalised healthcare. Fully harnessing our potential to generate and analyse these data insights can strengthen the viability of patient insights and outcomes in addition to contributing to greater value in predictive knowledge about the human condition. Seragon's focus in genomic data aims to take drug therapy and treatments into an individualised approach to learn more about patients, ultimately make accurate predictions about preventing and treating for all kinds of chronic and inherited diseases & conditions.
Personalising impact
With increasing value patient-focused research, Seragon is interested in further developing:
- Patient databases that measure genetic outcomes, biomarkers, and disease biology to assess possible treatment strategies.
- Platforms that aggregate those databases to provide a more holistic view of a patient's health, and other tools to pinpoint improvements in patient care.
- Partnerships that invest in data mining, studies, and trials that research genotypic and phenotypic data.
- Genetic studies such as genomic sequencing, genetic testing, and genomic research.
We prioritise innovation and quality to advance the tools that will support and improve diagnostic research as one of the most impactful ways that we accelerate patient care and enhance human quality of life around the world.