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The Next-Gen Technologies Driving Bioscience Business Innovation

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The electronics and software technology sector is currently in all the headlines, for the right and wrong reasons. However, it isn’t the only cutting-edge sector in town. The biosciences industry is also making gigantic leaps forward that promise to change the fabric of human life forever. 

But which technologies are driving this revolution in these brands? Let’s take a look at some of the cutting-edge technology and what it is making possible. 

Gene Editing

Top of the list of revolutionary technologies is gene editing, perhaps the most exciting invention of the 21st century so far (minus AI). The technology enables companies to develop products that adjust the genome of their customers, enabling new forms of medicine and biological enhancements

Gene editing is already a proven technology used daily in laboratories. Researchers use viruses to transplant gene sequences into cells, giving them new properties, like the ability to glow in the dark or fight cancer more effectively. 

The gene revolution has been upon us for 10 years, but now the research is proceeding to the point where real therapies are becoming available. And that’s a massive business opportunity. 

Single-Cell Analysis

Another lesser-known emerging technology is single-cell analysis. Companies are using RNA sequencing to characterize specific cells and learn more about them. This process is building a corpus of knowledge of how the cell works that future AI systems could parse and use to develop new theories, insights, and disease-fighting strategies. 

One approach uses a flow cytometer. This device uses a laser to determine the characteristics of cells as they pass by it in a medium. The ability to quick-scan cells enables more analysis of samples and could potentially enable the creation of products that scan patients in real-time, telling them if they have any health conditions. 

Machine Learning in Drug Discovery

Another frontier is the use of machine learning in drug discovery. Historically, pharma companies would have to manually go through drug combinations in a database and select the ones they thought would be most beneficial. However, this approach depended on human reasoning, which could be limited or flawed. 

That changes considerably with the advent of machine learning. AI is far more able to test new combinations and find candidates based on existing studies and data. 

Current AI systems are information-dependent. That means they rely on the data researchers feed into them from existing bodies of knowledge. However, state-of-the-art systems are gaining the ability to experiment with ideas, form hypotheses, and test them in the lab. It means that new drugs are more likely to be found in the future by pharma businesses. 


Another next-gen technology transforming the biosciences sector is immunotherapy. The concept of this approach is to trigger the body’s immune system to fight cancer by reprogramming specific cells. 

Early testing and implementation prove the technique is highly effective. The medicine could potentially eliminate the need for radiation and chemo by undoing the defects that lead to tumors in the first place. 

CAR-T cell therapy, for instance, is making a tremendous difference in cancer treatment. Personalized approaches are more effective with fewer side effects.

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