The Digital Transformation in the Healthcare sector is accelerating, also under the stress and pressure induced by the pandemic.
Digital Transformation in Healthcare comes in several ways:
- automation of processes/activities by moving as much as possible to the cyberspace (including diagnostic, testing, monitoring)
- Tele-whatever to support medical care from remote
- drugs design
- mirroring of resources in the cyberspace
- monitoring of communities to detect weird phenomena that may raise a red flag (data analytics, insight)
- mirroring of “people” in the cyberspace
Data are clearly the fabric supporting digital activities and all researchers leading to more accurate data harvest are crucial. In this lline we see the development of sensors, of smart materials that can support implants and wearables, of body area networks to connect body sensors to a gateway, sensors embedded in drugs, sensors in ambient and so on.
Clearly, gathering data is just the first step. The next one is to make sense of data, through spatial (correlating different data streams) and temporal correlation (analysing the evolution of a single data stream). Making sense of data often requires their contextualisation, that is having a model that can simulate the expected values and comparing those values against the real values detected (or derived).
This is where Digitall Twins come handy. They can be used to model a hospital, a process, a person. These latter are called Personal Digital Twins.
The creation of vaccines is becoming a software intensive endeavour. Researchers use computers to model viruses and computers to simulate countermeasures (the identification of proteins that can stop the virus in attacking a cell, in multiplying, in having side effects, the design and simulation of vectors…). Tests are run in vitro, then on animals and eventually on human volunteers.
A new wave of simulators is now arriving, based on labs on chips simulating organs (organ on a chip) and physiology. Additionally, researchers are now creating Digital Twins of people, based on their genome. metabolome and proteinome to simulate the effect of a drug on that specific person.
There are now over a hundred Covid-19 vaccines under development and many of these are in the testing phase with human volunteers. The expectation is that a few will succeed and it is likely that they will show different levels of effectiveness depending on broad classes of people (some might be better suited for elderly, other for people with certain pathologies…). Moving to a virtualised, digital, person could allow the tailoring of a vaccine (or at least the selection of one among those available) to a specific person.
Hence the idea of a near future where vaccines will first be “digitally injected” on my digital twin and based on the resulting simulation one will be chosen to inject physical self.