GPT-5 and biopharmaceuticals can be applied, empowered, and empowered in these three areas!

GPT-5 has just been released, and after watching the press conference, I feel that its capabilities are indeed powerful. Not to mention its strong information processing ability, it can also analyze various data together, which has changed the gameplay of biopharmaceuticals.

Firstly, let's talk about research and development efficiency. By combining it with various data analysis methods, the speed of finding drug targets can be three times faster.

Hard bones like GLP1 and WRN, which used to be difficult to chew, now have much easier to design suitable drug molecules. Originally, it took 4 to 6 years of research and development time, but now it can be completed in two to three years.

Clinical trials have also saved a lot of trouble. With virtual patient simulation and flexible trial design, the sample size of phase III trials can be reduced by 20%, and recruiting a patient does not have to wait for three days, it can be done in four hours.

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Speaking of processing different types of data, the biggest improvement of GPT-5 this time is multimodality, where biological information such as text, images, and gene sequences can be analyzed together.

For example, when looking at skin diseases and comparing them with gene sequences, the diagnostic accuracy is much higher; Combined with the protein structure predicted by AlphaFold 3, the simulation of molecular docking is also more accurate.

When integrating real medical data, the ability to dynamically analyze information from over 20 million patients has increased the success rate of breakthrough therapies approved by the FDA and NMPA from the industry average of 42% to 68%.

OpenAI and Sanofi teamed up to create an intelligent tool that can manage the entire process of drug development, changing the old way of research and development.

XtalPi and DoveTree have teamed up for $6 billion to specialize in targets such as RAS and Myc that no one has been able to tackle before.

CRO companies that conduct contract research are also upgrading with intelligent technology.

However, on the other hand, using GPT-5 can also be troublesome.

In terms of data privacy, countries have strict regulations and rely on special information sharing technologies to ensure security; Moreover, the decision-making process of this intelligent system seems to be a black box, and the reasoning is not clear. The regulatory authorities are always worried and need to rely on specialized tools to solve this problem.

Looking ahead, combining with quantum computing is probably a major direction, greatly improving computing speed.

The intelligent closed-loop system in the laboratory can also complete the cycle of "hypothesis making experiment model modification" on its own. All of these are pushing the biopharmaceutical industry to shift from relying on experience to relying on data intelligence to speak.

It is estimated that by 2027, the size of China's intelligent pharmaceutical market will exceed 200 billion yuan.