Oia Manifesto To End All (Preventable) Human Diseases, Today!

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At Oxford Immune Algorithmics (OIA) we firmly believe that it is our obligation to do our best to promote the use of the most advanced scientific and technological tools and methods  currently available in the fight against human disease. We believe that most, if not all, diseases are curable if detected soon enough, and that current science and technology  can deliver this goal not sometime in the future, but today!

Unfortunately, human priorities are often lopsided. We just saw a Hollywood movie break records last month making 1 billion USD in only a week, with some people spending as much as 500 USD, according to certain sources, for a single cinema ticket. With 1 billion USD, OIA would have been able to distribute devices to about 20 million households and equip about 100 million people with a state-of-the-art AI-based device to monitor their health,  which would have given us a good shot at eradicating some of the greatest health challenges that humanity has faced, such as cancer and antibiotic resistance, which if not solved can send us back to the Middle Ages.

Written in the late 1920s, this notebook records Alexander Fleming’s experiments with bacteria and antibiotics (penicillin). While medicine is driven by technology some practices haven’t changed much in 100 years. Today, the same screening test in a petri dish is still used to study and diagnose antibiotic resistance. OIA is disturbing old practices with modern science and new technology to help solve some of these world challenges.

At a rate of 100 million people a week we could cover the entire world population in about a year. But even 1% of that would produce enough data and traction to significantly improve human health and probably crack cancer and other leading causes of death. That money, however, is channelled to other places, not where it may mean more and have a more lasting impact. We also know that politicians, sportsmen and actors are given extraordinary public and media attention, but not scientists, who may be losing the fight against mysticism and misinformation. We can see how even diseases that were considered under control or eradicated are making a comeback due to political regression.
Unfortunately, we can do very little to dictate or influence human priorities when it comes to what people decide to fund. However, we have assembled a small but strong team that combines decades of academy and industry experience and is capable of transforming healthcare with state-of-the-art technology and science that we have introduced and continue to develop.


Current medicine relies heavily on what overburdened medical staff can do. Today, medicine can be characterised as driven mostly by what we lack: doctors’ time, patients’ data, new approved drugs, lower-cost machinery, etc. We need to change this model. More precise and quantitatively and qualitatively superior objective diagnosis and prognosis is possible, but we need to get it right, and get it done. Current machine learning (ML) methods can help, and can accurately profile diseases, and even sometimes predict patient progress and outcomes.  However, some of these AI methods are often not suitable for medical purposes because they do not explain why certain specific features or markers may make sense in practice, or why a particular prediction is made instead of another. Take as an example the classification of dogs and cats. A black-box ML approach may do a perfect job but when you dig a bit further you may find that the feature separating dogs from cats according to your ML application

is that all pictures of dogs were taken outdoors, and so ML concluded that grass and clouds were the best markers for classifying dogs, getting it right 100% of the time.

While medicine is still far from using even basic AI, the lack of explanations and generative models about which features and causes drive the observed data and results may hinder the adoption of these technologies in making diagnoses and decisions based on cause and effect. This problem currently prevents scientists from understanding the true causes of natural phenomena from first principles. We seek to overcome these limits by bringing brilliant minds and machines together to cooperate in delivering a new kind of model-based AI rooted in the research we have performed at the best universities (the University of Oxford, and the Karolinska Institute–the institution that awards the Nobel Prize in Physiology or Medicine). 


We have built a small but committed team: risk takers, and doers; and we try to avoid the bluffers. At OIA we aim at understanding key health markers in a vertical fashion in order to provide each patient with their own cellular and, eventually, molecular deep temporal profile, to help us help them identify causes and effects in time for super early detection by using non-traditional model-driven machine learning suitable for medical exploration that OIA owns and continues to develop. This is how OIA plans to change medicine, healthcare, and ultimately the human condition.

We’ve set out on a journey to revolutionise healthcare, bringing it from the equivalent of the dial-up to fibre optics by radically enhancing the way in which data is generated, understood, and exploited. There are some different paths that may be taken, and we may sometimes get off track, but you can help us get back on track and achieve our goals faster by investing in our cause or contributing in kind, as a volunteer, or as an ambassador. If our vision resonates with yours and you share our values, you should join us and help us achieve our goals

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