Science

More than 30 years have passed since the advent of omics technologies revolutionized biological and medical research. Research now highlights the unique opportunity to integrate and decode complex biological mechanisms for health and diseases with machine learning.

It’s now possible to make sense of terabytes of complex data to help guide treatment decisions.  Something as simple as ensuring the right patients are enrolled for a clinical trial can be the difference between a blockbuster drug and failure to get approval. 

Personally I’m partial to proteomics as that’s what I do and it tells you what’s going on in your body but when you integrate omics you get a better understanding of the complete biological system.  

There are a few big things holding us back, I expect these to get sorted out in the next 5-10 years.

1.) Omics are still expensive and data analysis isn’t fully mature
2.) When designing clinical trials, omics data isn’t considered for trial enrollment
3.) Most clinicians don’t understand the value of omics data and have no clue how to interpret it.

Scientist 🧬, dog lover 🐶, amateur photographer 📸, crypto enthusiast, Cat Town Farcaster Community Leader

Wow, the future of medicine looks super exciting with omics and machine learning teaming up to crack complex health puzzles