We are developing a novel blood-test that predicts all-cause mortality risk and risk of developing specific age-related diseases.
Aging is the predominant risk factor for most diseases and conditions that limit health span. Due to the exponentially increasing proportion of the world’s elderly population, developing novel and effective therapies for treating and preventing age-related diseases has become essential.
We can help reduce the cost and the duration of clinical trials.
By applying 21st century machine learning techniques on large epigenetic datasets spanning 45 years back in time.
We create the prediction algorithm by combining genome wide microarrays, high-performance computing, statistics and machine learning.
At the core of our approach lies an algorithm trained on the DNA methylation patterns from thousands of people where lifespan and cause of death is known. We train our algorithm on large unique datasets from Norwegian and international biobanks.
Shortening trial duration's and lowering the number of patients needed.
The problem: The cost of developing a new drug roughly doubles every nine years. The average cost of developing a new cancer drug is €556m, the median time to approval is 7.3 years and only 10% pass all three phases and receive approval. The main drivers of time and costs are the number of patients, the trial duration and the low likelihood of success.
The solution: Using our blood-test in clinical trials can help reduce cost, trial duration or the number of patients needed through:
We have founded several successful companies, and have a deep understanding in aging, genetics and predictive analytics. We collaborate closely with world-leading experts on building prediction algorithms based on epigenetics and DNA methylation measurement techniques and have gathered an interdisciplinary team of accomplished researchers and developers.