Creating medicines that are specific to individual patients requires a lot of data that must be both available and secure, reports Greg Hookings, Director of Business Development, EMEA, at Stratus Technologies
The future of medicine is personalised. Sometimes referred to as precision medicine, it differs from regular treatment approaches by tailoring decisions and medications to an individual person — rather than taking a one-size-fits-all approach.
Traditionally, when a new medicine is brought to market, it goes through rigorous testing processes with multiple levels of studies ending in a final stage of human trials.
Following a successful trial, it is then put into production where it must follow strict validation protocols that ensure that each batch is manufactured in exactly the same way.1
The standard process in the marketplace for drug use requires patients to report symptoms; a professional then prescribes a suitable proven medicine that’s currently on the market.
One drawback with this approach is that those medicines are [only] proven in a trial setting … and although that drug may have successfully treated a certain issue, the results might only apply to that specific situation.
For example only 40% of patients benefit from common asthma and diabetes drugs.2 And, back in 2015 — in a pre-COVID world— 6.5% of NHS hospital admissions were from adverse drug reactions; an issue that accounted for the use of more than 8000 beds at a time when capacity was stretched to breaking point.
The drugs involved were, of course, rigorously tested and assessed, but can’t fully account for side-effects in an individual patient.
Personalised medicine works in the opposite way. Although symptoms are reported in the same way, each patient is then reviewed according to their level of risk.
They are then assessed based on genetic factors — with doctors being able to suggest the best form of treatment from a growing database of information derived from actual results.
The traditional method is essentially a trial and error approach, whereas personalised medicine considers the individual needs of each patient based on genetic factors — rather than estimations — providing the right treatment at the right dose at the right time.
Personalised medicine will not only benefit the patient with increased well-being and fewer side-effects, but also promises to reduce the overall drug budget for the NHS.
Always on availability
For medicine manufacturers and healthcare professionals, the first step in personalised medicine is human genome sequencing. At inception, this was an extremely costly process; even 10 years ago it used cost approximately $10,000 to complete but, today, the cost is about $600 and falling.3
This is the first critical dataset that is imperative to offering personalised medicine and it is being generated at an ever-increasing rate. Meanwhile, personal smart devices and digital medical records mean that there is an influx of other useful data.
However, healthcare providers face the huge task of creating an expandable Big Data infrastructure and analytical methods to make the provision of personalised medicine practical.
The next critical data set is testing. As mentioned, this has to be done on those with specific genetic factors, thereby reducing sample sizes and rapidly decreasing the time to deliver treatment. For personalised medicine to work, both critical datasets must be always available on both sides of the production line.
Both healthcare providers and medicine manufacturers need the ability to collect, store and process huge amounts of data, all of which can be achieved with edge computing.
By moving computing power to where it’s needed, rather than costly storage in a traditional data centre, healthcare professionals and manufacturers will have the information they need immediately to hand.
On the healthcare side, a doctor may need to assess the patient’s history and compare symptoms with previous treatments; manufacturers may need to alter the production process to eliminate a single ingredient that the patient is allergic to.
And, in both examples, the data must be available at a moment’s notice to be able to provide a treatment rapidly.
There are still ongoing discussions about the best way to make use of this large dataset; but, even if artificial intelligence (AI)-empowered smart data is the future of personalised medicine, it will still require high amounts of computing power … making it ideal edge computing.4
For healthcare providers and medicine manufacturers to effectively offer personalised medicine, there has to be a level of data sharing.
This always comes as a big worry for companies as healthcare data is strictly protected … and companies that don’t adhere to GDPR regulations will face huge fines of up to €20 million or 4% of worldwide turnover for the preceding financial year (whichever is higher).
Edge Computing again offers a solution here by having the computing power, either in the manufacturing facility or in the office of the healthcare provider, to keep critical data secure and stored locally.
Never being sent to the cloud of a data centre, any information sharing occurs between two secure locations, reducing the attack plane for hacking. The right deployment also enables “Always On” availability, which is critical to secure data from cyberthreats and dreaded data loss.
Achieving this high level of cyberprotection can ease the worries on healthcare providers and manufacturers, leading to more effective personalised medicine that can be delivered quickly. Moreover, there are a multitude of benefits that edge computing can provide to manufacturers of pharmaceuticals.5
Taking it to the edge
Personalised medicine is the future of healthcare, not only for patients but also for manufacturers and the NHS. The main stumbling block to making this possible is the proper collection, storage and analysis of data that is always available and always protected.
Edge computing is a key steppingstone to providing personalised medicine because vital datasets are more inherently secure. Having the right computing infrastructure is a vital first step for the healthcare industry to start really exploring the full potential of personalised medicine as they seek a scalable solution, and edge computing is exceptionally well placed to deliver the flexible, reliable and secure platform it needs.