Tern : Vaccine development and the role of IoT / AI

Vaccine development is, for obvious reasons, currently at the forefront of many people's minds. The race to find a safe and effective vaccine for COVID-19 is one on which thousands or even millions of lives may depend, as well as the health of the global economy.

It is a race in which the Internet of Things (IoT) and artificial intelligence (AI) technologies will have a vital role to play.

This is because vaccine development requires the collection and analysis of vast amounts of data, and IoT and AI can help with both sides of the equation. The IoT can facilitate the quick and cost-effective collection of data, and AI can enable the analysis of that data far faster and more comprehensively than humans could.

Data collection

Data collection takes place throughout the drug discovery cycle. Right at the beginning of the process, it might involve collecting data on multiple different existing drugs and molecules - tens or even hundreds of thousands of them. The IoT might play a role here in facilitating the gathering of data from multiple different labs and research centres.

Then, whilst new molecules and drugs are being developed, clearly there are myriad different layers of data collection throughout the testing processes. In lab settings, IoT technology can again enable the automatic collection of pertinent data, through smart sensors and connected lab equipment. Critical information can be fed directly to computers for analysis, rather than requiring manual (and therefore slower, and more error-prone) collection.

Then, when a vaccine is ready for human testing, those human subjects need to be incredibly carefully monitored. Myriad different vital signs must be stringently watched and measured in order to understand how the drug is affecting each subject. Once again, IoT technology can enable this data collection to take place automatically. Even relatively straightforward devices such as connected thermometers can grant researchers a whole new kind of visibility into the test process.

Data analysis

At every stage in this process, those vast quantities of data need to be analysed in order to spot trends, unlock insights and guide the next stage of the process - whether that is pinpointing a particular molecule at the outset which could form the basis of a vaccine, or confirming whether a vaccine is likely to have a particular effect in a particular group of people.

Carrying out this analysis manually is hugely time-consuming. AI and machine learning algorithms can make an extraordinary difference, not only spotting trends and patterns that would take human researchers far longer to uncover, but also learning from their own insights and getting smarter over time.

Furthermore, as researchers all over the world contribute new insights and new data to the global knowledge base - whether on COVID-19 or a different disease altogether - AI and machine learning can ensure that this new information is aggregated with existing conclusions. In other words, the more data is generated - from multiple different sources - the smarter, faster and more efficient the vaccine development process can become.

Traditionally, drug discovery and vaccine development processes take years. IoT and AI technology could accelerate them to mere months.