What are AI and 3D printing doing for medicine?

Jon Lawson

Manufacturing has been revolutionised by technology. However, pharmaceutical manufacturers are only just beginning to see the potential of innovative product creation. The potential benefits of technology in healthcare are vast, and revolutionary techniques are clearing the way for a cost-effective, efficient and tailored approach to medicinal production.

One study from the LSE suggests that the cost of bringing a new drug to market is upwards of US$985 million. This is then reflected in the cost paid by insurance companies and end-users. The need to accelerate technology to drive these costs down is essential, and innovation is key. Here we look at the technology which is allowing pharmaceutical manufacturing to be revolutionised.

While medicine is no stranger to the marvel of 3D printing, pharmaceutical manufacturing is yet to hop on the trend. 3D-printed teeth and prosthetics are already commonly used in the health industry to assist patients. However, there is a distinct lack of approved 3D-printed pharma products in the US marketplace.

Medicines can be produced through 3D printing. This has interesting benefits, including unique tailoring to a specific patient’s needs.

In 2015, the US FDA approved the first medicine that had been produced by 3D printing. The precision of the machine allowed manufacturers to create a pill with a high drug load. In one dose, patients were now able to receive 1,000 milligrams of levetiracetam. This was a revolutionary treatment for sufferers of epileptic seizures. However, since then, there has been limited progress which may be due to the high cost of this method.

While having a 3D printer in your local pharmacy is a futuristic concept, the idea of additive pharmaceutical manufacturing is driving the industry towards a future where everyone’s ailments can be individually tackled.

The pharmaceutical industry looks beyond itself for inspiration when innovating. Of course, automation has played a large part in manufacturing for near to a century. For example, in vehicle manufacturing, automation is used to reduce costs and better perform intricate tasks. Now, pharma businesses are looking to do just the same.

Previously, scientists have become curbed by the manual task of individual genome testing. However, automation is allowing manufacturers to access a huge amount of data, enabling them to create unique molecular profiles of their customers and provide them with the best care.

Of course, technology in the workplace must be safe, especially when working with medicine. The use of electrical enclosure boxes (like these) ensures that operators are safe when dealing with electrical machinery and that the stringent sanitation practices are maintained.

Artificial intelligence is common across many sectors. In general manufacturing, it can collate data and calculate the most efficient processes. This then allows it to create products and optimise the entire process. In pharmaceutical manufacturing, the process of medicinal engineering can be improved through digital reform.

Machine learning, with access to patient data, can compare individual profiles and medicine effectiveness. By doing this, manufacturers can adapt their medicines to create improved predictions on the demand of medicines and their effectiveness. This can allow pharmacists to prioritise medicines and amend their ingredients for maximum effect. This has a general benefit to everyone.

The technology can even be used to simulate real experiments. By predicting the outcomes of experiments, technology will be able to predict which medicines are the most effective. It can also note which projects pharmaceutical manufacturers should pursue, and they may even calculate cost and source ingredients for completing these tasks.

Medicines are constantly improving, producing new drugs for a variety of illnesses. The innovation of technology in pharmaceutical engineering is allowing for individually tailored drugs to be produced for customers who require special attention while driving down the costs of production. Equally, the attention and precision of technology including machine learning and automation are allowing for more accurate medicines to be created for the benefit of everyone.

 

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