Cancer claims millions of lives worldwide every year, yet a staggering third of cancers can be prevented by the use of World Health Organisation (WHO).according to the
Malignant mutations present an interesting challenge for those working on providing solutions to treat cancer. Specific solutions are needed to combat drug-resistant bacteria and cancer.
is key to research
Neil Hunt from Netflix observes that “most cancer have several molecular pathways that influence the disease.”
Altogether there are 10,000 pair wise combinations and a million triple combinations that then have to be blocked using a specific combination of drugs, this can lead to huge amounts of big data.
“The number of combinations is immense”, says Hunt.
Every day, across the world, doctors are experimenting with combinations to treat their patients. These low-level trials often just involve the patient – one person – and are seen as an anecdote rather than a result from a large clinical trial.
Yet these n=1 trials contain a wealth of data, that at the moment, present a catastrophe of lost learning.
Sharing big data, and crowdsourcing personalised treatments, has the potential for doctors to examine patterns and similarities between specific genetic mutations, patient histories and treatments.
The analysis of big data can lead to survival of patients
Doctors stand to learn a tremendous amount, and prescribe a particular combination of drugs that would otherwise not be possible in a classical clinical trial.
“Big data techniques offer a way to analyze data pooled across many patients: their specific disease mutations, biological markers, the treatments, and outcomes — in order to identify unexpected ways that existing therapies can be applied and combined to create personalized treatments that dramatically improve the chances of survival.”
In this way, big data and probability models can be used to overcome genetic mutations that are malignant, and cover the spectrum of patients who do not necessarily fall into the ‘average’ quartile.
Neil Hunt’s full speech at TEDxBeaconStreet lasting 18 minutes can be viewed here: