The future of personal genomics with Pregenic

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Genetic testing with respect to personal genomics is an emerging technology which has started to gain a solid foothold throughout the past decade. Improvements in precision, safety and costs have unlocked usage to a much broader audience, and stakeholders sit eager with anticipation to explore the purported huge potential unlocked through fierce innovation in genetic analysis. To date, more than 26 million people have purchased a personal DNA test to gain novel insights into tailored disease risk profiles, nutrigenomics or ancestry. While results from tests are associated with a varying degree of uncertainty, the technology employs a self-reinforcing feedback loop which over time improves accuracy.  But where will this lead us? What is the future for genetic testing?

The big picture

At Pregenic we envision a future where secure personal genetic profiles constitute the core of the healthcare system, and consultation of underlying genetic profiles precedes diagnostics and treatments. Better understanding of personal disease risk, pharmacogenomics and nutrigenomics will thus serve as an important supplementary role in the physicians’ arsenal and ultimately lead to longer and healthier lives.

In the future, the large number of data points will pave the way for a transition from relative to absolute risk scores, which offers a more tangible understanding of underlying risk. This may raise awareness of symptoms and lead to earlier discovery of diseases which in many cases is essential to successful treatment.

ADVANTAGES OF PERSONAL GENOMICS

Pharmacogenomics will allow personalised medicine to gain traction within treatments. Knowing genetic associations with drug responses will have an incredible influence on the way we treat people, helping us to avoid adverse responses and predicting the correct drugs with the highest likelihood of succeeding in treatment of the patient.

Nutrigenomics will have an influence on people’s everyday life and wellness, allowing creation of personalised diet that will improve our general health and decrease our disease susceptibilities. Generating knowledge about individual metabolic polymorphisms will be an important contribution towards this goal.

When we want to create holistic knowledge about an individual, we need to take their lifestyle into account as well. Understanding the environmental impact on disease development will be key towards e.g. generating absolute disease risk values, which will contribute to disease prevention and earlier discovery.

The influence of AI on genetic analyses

Considering the vast amounts of data to be analysed, Pregenic believes that the best approach to analysing genetics in the future, is using the one the greatest computational tools of our time, artificial intelligence. By creating intricate machine learning algorithms and feeding them the right training data, we believe we will be able to predict genetic associations and discover new interactions, previously unknown to science. This will enable collaboration with pharmaceutical companies in developing new therapies and improve life for all of humanity.

Dream big or go home

We dream big. We will not lock ourselves in to just developing genotyping analysis for disease risk assessments. We want to create a company that will provide insights into pharmacogenomics, nutrigenomics, disease risks, ancestry and every other meaningful insight we can derive from genetic data. In the future, genotyping will be just one tool in the toolbox. We want to provide a wide array of approaches of generating knowledge including but not limited to whole genome sequencing, DNA methylation analysis, and microbiome analyses.

The improvement of gene therapies using methods such as CRISPR-Cas9 and other tools will further increase the importance of the knowledge that can be derived from individual genomics. The possibilities will be endless.

This is the future we envision.

1 thought on “The future of personal genomics with Pregenic”

  1. Hey, thanks for the update… it would also be interesting if you could refer to published studies that are using AI applications to better “predict genetic associations and discover new interactions, previously unknown to science” that are relevant or are inspiring your efforts. To me, it’s always interesting to find out what types of studies that knowledgeable people like you are tracking/appreciating. So any tips on such papers would be much appreciated. All the best, Mats -> https://www.researchgate.net/profile/Mats-Larsson-6

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