The concept of ‘digital twins’ has a strong association with engineering and with design innovation. Connecting the digital twin concept to medicine represents a new area of consideration.
Researchers from Linköping University have used the digital twins concept to develop a computerised digital aid designed to help to provide individual patients the right treatment at the right time.
This is through constructing a ‘digital twin’ of diseases. The focus is with strengthening diagnosis and treatment. As an example, the scientists have constructed a model to identify the most important disease protein in hay fever.
The research question was ‘Why is a drug effective against a certain illness in some individuals, but not in others?’ As thig s stand, with most over-the-counter-medicines these are ineffective in 40-70 percent of the patients.
This occurs because the root cause of a diseases may relate to a different root for different patients, or a disease is not caused by a single “fault” that can be easily treated. Often a disease is the result of altered interactions between thousands of genes in many different cell types.
To target hay fever, the researchers used a technique called single-cell RNA sequencing to determine all gene activity in each of thousands of individual immune cells. This enabled the researchers to measured gene activity at different time points before and after stimulating white blood cells with pollen.
This led to building computer models of all the data using network analyses. Networks describe and analyse complex systems, in this case to identify the most important disease protein.
It was found that multiple proteins and signalling cascades were important in seasonal allergies, and that these varied greatly across cell types and at different stages of the disease. In terms of a crucial breakthrough, inhibiting a protein called PDGF-BB, appears to be more effective than using a known allergy drug directed against a commonly targeted protein – IL-4.
It is hoped that the technology can be developed to give the right treatment at the right time to patients in relation to other immunological diseases, like rheumatism or inflammatory bowel diseases.
The research appears in the journal Genome Medicine, titled “A dynamic single cell-based framework for digital twins to prioritize disease genes and drug targets.”
