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Thanks to significant advances in genetics, we are not only getting better at diagnosing disease, but also at predicting disease. Predictive medicine is an exciting new approach to healthcare that harnesses the latest biological and analytical techniques to make predictions about the future health of a patient or population. With breakthroughs in our ability to detect and analyse small differences in genes, proteins and other cellular components, scientists are able to make predictions about a patient’s likelihood of developing a disease, or how they will respond to treatment.

Genomics plays an important role in this medical revolution. While we’ve known about DNA since the 1960s, it wasn’t until the completion of the Human Genome Project in 2003 that scientists were able to map the entire human genome. This led to a lot of hype around the potential impact of genomics with hopes that this new knowledge would enable us to immediately unlock cures for every disease. Despite the project revealing how complicated biology is, breakthroughs have been made in terms of how quickly genomic data can be obtained, the detail that can be resolved from that data, and the information that can be understood from that data.

Revolutionising healthcare

Patients often have a better chance of recovery the earlier their disease is diagnosed and predictive medicine technologies take this to a new level. Patients could be treated even before they have developed symptoms, or adopt lifestyle changes to prevent those symptoms emerging. Understandably, in the face of aging populations, and ever tighter healthcare budgets, governments are supportive of these kinds of technologies. We can expect them to have a fast-track to adoption, particularly as compared to traditional medical technologies such as new drugs.

Promising applications

Significant research is looking into the prediction of cancers, particularly where there’s a family history of a specific cancer. For example, some women are now undergoing a precautionary surgical intervention where there’s a family history of breast cancer, and where they’ve been identified as carrying a cancer-associated mutation in a BRCA gene. 

There are also efforts to more accurately predict the onset and development of cancers in people with other risk factors, such as socioeconomic or lifestyle factors. Prevention or early diagnosis of cancers will have a massive impact on people’s lives, and also economic impacts for healthcare providers, so there are expected to be some significant developments in this area.

Foetal predictive medicine will also see continued growth, particularly with non-invasive neonatal testing. Advances in relapsing-remitting disorders such as relapsing-remitting multiple sclerosis, or irritable bowel syndrome, are expected, helping to improve our ability to predict (and therefore to prevent or reduce) the severity of relapses.

Precision medicine and data

Adopting similar diagnostic and prognostic technologies, personalised medicine has seen significant advances alongside predictive medicine, such as improvements in our ability to sequence nucleic acids, both in terms of scale and detail.

More recent advances have come from (and will continue to come from) improvements in the way we handle and process big data. There’s doubtlessly a lot more to be understood from the data we already have, attempting to filter out background noise in order to identify changes that might appear small and inconsequential at first glance. This data not only allows us to understand why patients respond differently to the same treatment, but also how different factors contribute to disease progression.

What next?

In terms of evolution, we will see an expansion in the types of diseases we’re predicting. This will go hand in hand with an increase in the types of data that are contributing to that prediction. A combination of data will be pulled together to make the prediction - genomics, proteomics, and other information about a person’s biology, but also information about their lifestyle and choices, such as diet and exercise history. We’re only beginning to untangle how all these factors combine to contribute to disease progression. With all of these developments combined, this is an exciting time, not only for predictive medicine, but for the whole of precision medicine.

Fran works in all patent cycle stages within the life sciences sector – from invention capture, drafting and patent strategy to prosecution and global portfolio management. She is a member of our plant variety rights team, having completed the official WIPO course on plant variety protection under the UPOV convention. As such, Fran has extensive experience dealing with plant-related inventions, including obtaining plant variety rights and entry onto the national list and common catalogue.
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