AI into a pharmaceutical master: the market will usher in a big outbreak
In the field of drug care, artificial intelligence (AI) is in turmoil. First, AI pharmaceutical company Jingtai Technology completed a round of financing of about 15 million US dollars, followed by pharmaceutical giant Roche to acquire the entire shares of tumor big data company FlatironHealth for 1.9 billion US dollars, actively deploying digital and AI. In these industry giants, AI's function in pharmaceuticals will usher in a huge market outbreak.
Reduce R&D costs, pharmaceuticals are more transparent
The long-term development cycle of new drugs, large investment, long-lasting, and low efficiency have always been a "big worry" in the medical field. According to data from the Taft Center for Drug Development Research, it takes an average of 96.8 months for a new drug to be available from drug discovery to FDA approval. In terms of cost, Deloitte's data shows that since 2010, the cost of approved drug development for 12 major pharmaceutical companies has increased by 33%, about $1.6 billion per year.
With the addition of AI, people have seen a welcome change. According to TechEmergence's research report, AI can increase the success rate of new drug development from 12% to 14%. This only 2% growth can not be underestimated, can save billions of dollars for the entire biopharmaceutical industry, and at the same time, Save a lot of research and development time.
Children's medication is no longer half the adult dose
For a long time, due to the shortage of children's special medicines, many children will take adult medicines. The so-called “children's discretion†in adult medicine has a huge risk of medication safety. Secondly, there are too few suppliers. In China, there are more than 8,000 pharmaceutical manufacturers in the country, of which only 0.1% are specialized in the production of children's drugs, that is, only 8 are produced for children.
From this current situation, it is necessary for AI to help the development of children's medication. First of all, AI is definitely a master in the data. The underlying core of AI drug development is the knowledge map, which essentially integrates the physics and chemistry data from the laboratory, the research results in various journal articles, and the clinical data, which are not related to each other, and integrates the discrete data. Provide valuable decision support. Through the data mastered by AI, we can experiment with the effects of different doses, and finally find the most accurate dosage, and also manage the data of drug taste. And all this, the cycle won't be too long, and consumers don't have to bear too much cost for it.
Chinese medicine is no longer "traditional, ignorant"
Although there are still many good Chinese medicines on the market, the fact that safety is not purely safe, there are still many potentially unknown risk factors. This is one of the reasons why people don't trust Chinese medicine.
If the technology of AI drug discovery can be used in Chinese medicine research, it will be a milestone in the development of Chinese medicine. For example, AI builds neural networks through deep learning, absorbs all known single-step organic chemical reactions, deconstructs molecules in drugs, attempts chemical reactions that can be used in any single step, and repeatedly applies these neural networks to plan multi-step organic chemistry. Synthesis of the reaction until the pharmacological and toxicological mechanisms of the Chinese medicine are obtained. Simply put, all the chemicals in the soup are separated, and through the chemical reaction and clinical data, the truly effective chemical is found, and other chemicals are analyzed one by one.
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