06 Feb Why Digitized Data will be a Game Changer for Life Sciences!
Insight by: Jon Warner
In the 2002 movie “Minority Report” the story is about how cleverly integrated data, data analysis and machine learning or artificial intelligence tools (and even futurist robots) can be used to predict future problems – in the film’s case predicting for criminal acts being in the mind individuals of well before they commit the crime (and then pre-arresting the individual concerned). While this ‘technology’ was complete science fiction over 20 years ago, today we have many of the data tools to make determinations of what the future may look like or can be modelled. While we are not yet able to look at ‘thoughts’ in quite this extreme and scary way, (as it relates to possible criminal behavior in the mind and not the deed), my interest in applying this plotline for the purposes of this article is to health and healthcare.
The whole world of genetics (the study of heredity), genomics (the study of genes and their functions), gene expression (the process by which the information encoded in a gene is turned into a function) and epigenetics (the study of changes in organisms when a gene has been modified) has exploded in the last few years, and we can now get more readily into the human mind and body in way not even possible before the beginning of this millennia. What this all means is that we now have the building blocks of life in digital form (given that the whole human genome has been mapped, which involved the recording of 3 billion nucleotides-a process that took from 1990 to 2022 when it was completed). This now allows for not only deep data analysis of which DNA and RNA pathways lead to good and poor health but allows data extrapolation models to be built that show what future living or behavior paths people can and should take in order to maintain good physical and mental health (and increase not only their life-span (living longer) but their health-span or the % of their life they are healthy.
One way in which we already have working models using the rich genetic data set (and these are getting more sophisticated every year) is the development of the health ‘digital twin’. Health digital twins, (or HDT’s) are defined as virtual representations of patients (the “physical twin”) that are generated from multimodal patient data, population data, and real-time updates on patient and environmental variables. With appropriate use, HDTs can model random perturbations on the digital twin to gain insight into the expected behavior of the physical twin—offering groundbreaking applications in precision medicine, clinical trials, and general public health. The main considerations for translating HDT research into clinical practice include computational requirements, clinical implementation, as well as data governance, and product oversight (drug or delivery systems technology).
One specific example of direct application to life sciences is that manufacturers of medical devices or pharmaceuticals can apply digital twins to develop new products and therapies or improve existing ones, as well as modify or redesign equipment that produces those goods. This could all ultimately mean that a host of diseases—including chronic conditions such as heart disease, diabetes, liver disease and even neurodegenerative disorders like Dementia —could be treated in large part by making a range of interventions much earlier than before. This could mean a huge possible market in vitamins, minerals and other supplements, in nutraceuticals and even in a drug regimen applied more precisely, according to people’s individual needs and genetic profile. It may well be that the data and research begin to even slow or possibly reverse the aging process -a huge implication for life sciences companies of all kinds.
This remarkable research and technology and the huge potential that arises from the assembly, curation, analysis, and reporting on very big data sets might be as “scary” to life sciences organizations as the Minority Report movie plot line. However, one thing is sure -this will be a game-changer in health and healthcare and in a very short period of time. This is why every pharmaceutical, bio-technology, medical devices and related organization needs to ensure it has data scientists on staff as well as experts in digital health, in order to deploy solutions efficiently and effectively. Naturally, these changes may shrink some existing revenue streams but replace them with others, although, of course, there will be many risks to be managed in this transition. Tackling this head on and with a clear strategy is the best way to be part of the inevitable changes that we will see happen very quickly.