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Recently, Xinhua Bio, an AI-driven macromolecular drug research and development company, announced that the company has completed a financing of RMB 100 million led by Matrix Partners China and co-invested by Sequoia China and the company's existing investor Danlu Capital
.
After the completion of this round of financing, the company will accelerate the research and development of AI-driven macromolecular drugs
.
Not long ago, Westlake Omi, an artificial intelligence proteome diagnostic service provider, also announced the completion of hundreds of millions of yuan in Pre-A round of financing.
This round of financing will continue to be used to promote the development of protein profiling-driven in vitro diagnostic (IVD) products and AI pharmaceutical products.
R&D
.
It can be seen that since 2022, domestic AI pharmaceuticals are still making great progress, continuing the hot capital market in 2020, and financing has shown explosive growth
.
Data from the past three years shows that in 2021, there will be 34 financing events in the domestic AI pharmaceutical industry, involving a total financing amount of 8.
345 billion yuan, and an average single financing amount of 245 million yuan.
In 12 cases, the financing amount exceeded 2.
723 billion yuan; in 2019, the financing amount was only 242 million yuan
.
From the data changes in the past three years, it is enough to see that AI pharmaceuticals are getting more and more popular
.
Among them, Jingtai Technology has won the attention of everyone, and has completed a single huge financing of more than 2 billion yuan in 2021
.
Behind the popularity of AI pharmaceuticals, pharmaceutical companies are facing increasing challenges, including the rising cost of new drug research and development year by year, and the increasingly fierce market competition
.
According to research data, in 2020, the average cost of a new drug to market is 2.
508 billion US dollars; in 2010, this figure was 1.
188 billion US dollars
.
In just ten years, the average cost of a new drug to market has doubled
.
From the point of view of returns, after continuous high investment, the return rate of pharmaceutical companies is difficult to be proportional
.
Relevant reports show that in 2019, the return on investment of 12 biopharmaceutical giants in the world was only 1.
8%; in 2010, it was 10.
1%
.
In addition, in recent years, it can be seen that the financial reports of some multinational pharmaceutical companies are not as bright as in previous years.
Although the R&D investment of many pharmaceutical companies still maintains a high growth trend, the growth of net profit is very slow, and some even show a continuous downward trend.
.
In the current context, how to "reduce costs and increase efficiency" in the development of new drugs has become a challenge for major pharmaceutical companies.
The emergence of AI pharmaceuticals just brings hope to pharmaceutical companies
.
With the help of AI technology, the R&D process of new drugs, including target discovery, compound synthesis, compound screening, crystal form prediction, patient recruitment, optimization of clinical trial design and drug redirection, can be applied, which can greatly shorten the development time of new drugs and reduce R&D.
risk, thereby reducing the cost of the enterprise
.
Domestic AI pharmaceutical companies are also optimistic about the prospects and development space of the AI pharmaceutical market, and continue to increase their investment
.
In addition to traditional pharmaceutical companies, Internet giants such as Ali, Tencent, ByteDance, Baidu, and Huawei have also joined the track
.
For example, Alibaba's medical cloud AI is used for gene sequencing, thyroid nodule identification, lung nodule identification, digital simulation clinical experiments, etc.
; Tencent's Yunshen Zhiyao is used for protein structure screening and other drug research and development processes; byte's AILab, based on AI algorithms, is used to support the discovery and manufacture of research drugs
.
In general, domestic AI pharmaceuticals are hot, and will continue to make great progress under the pursuit of capital
.
It is worth mentioning that the domestic AI pharmaceutical field is still in the initial stage of development, and there is still a long way to go before the industry matures
.
For emerging AI pharmaceutical companies, opportunities and challenges will coexist
.
.
After the completion of this round of financing, the company will accelerate the research and development of AI-driven macromolecular drugs
.
Not long ago, Westlake Omi, an artificial intelligence proteome diagnostic service provider, also announced the completion of hundreds of millions of yuan in Pre-A round of financing.
This round of financing will continue to be used to promote the development of protein profiling-driven in vitro diagnostic (IVD) products and AI pharmaceutical products.
R&D
.
It can be seen that since 2022, domestic AI pharmaceuticals are still making great progress, continuing the hot capital market in 2020, and financing has shown explosive growth
.
Data from the past three years shows that in 2021, there will be 34 financing events in the domestic AI pharmaceutical industry, involving a total financing amount of 8.
345 billion yuan, and an average single financing amount of 245 million yuan.
In 12 cases, the financing amount exceeded 2.
723 billion yuan; in 2019, the financing amount was only 242 million yuan
.
From the data changes in the past three years, it is enough to see that AI pharmaceuticals are getting more and more popular
.
Among them, Jingtai Technology has won the attention of everyone, and has completed a single huge financing of more than 2 billion yuan in 2021
.
Behind the popularity of AI pharmaceuticals, pharmaceutical companies are facing increasing challenges, including the rising cost of new drug research and development year by year, and the increasingly fierce market competition
.
According to research data, in 2020, the average cost of a new drug to market is 2.
508 billion US dollars; in 2010, this figure was 1.
188 billion US dollars
.
In just ten years, the average cost of a new drug to market has doubled
.
From the point of view of returns, after continuous high investment, the return rate of pharmaceutical companies is difficult to be proportional
.
Relevant reports show that in 2019, the return on investment of 12 biopharmaceutical giants in the world was only 1.
8%; in 2010, it was 10.
1%
.
In addition, in recent years, it can be seen that the financial reports of some multinational pharmaceutical companies are not as bright as in previous years.
Although the R&D investment of many pharmaceutical companies still maintains a high growth trend, the growth of net profit is very slow, and some even show a continuous downward trend.
.
In the current context, how to "reduce costs and increase efficiency" in the development of new drugs has become a challenge for major pharmaceutical companies.
The emergence of AI pharmaceuticals just brings hope to pharmaceutical companies
.
With the help of AI technology, the R&D process of new drugs, including target discovery, compound synthesis, compound screening, crystal form prediction, patient recruitment, optimization of clinical trial design and drug redirection, can be applied, which can greatly shorten the development time of new drugs and reduce R&D.
risk, thereby reducing the cost of the enterprise
.
Domestic AI pharmaceutical companies are also optimistic about the prospects and development space of the AI pharmaceutical market, and continue to increase their investment
.
In addition to traditional pharmaceutical companies, Internet giants such as Ali, Tencent, ByteDance, Baidu, and Huawei have also joined the track
.
For example, Alibaba's medical cloud AI is used for gene sequencing, thyroid nodule identification, lung nodule identification, digital simulation clinical experiments, etc.
; Tencent's Yunshen Zhiyao is used for protein structure screening and other drug research and development processes; byte's AILab, based on AI algorithms, is used to support the discovery and manufacture of research drugs
.
In general, domestic AI pharmaceuticals are hot, and will continue to make great progress under the pursuit of capital
.
It is worth mentioning that the domestic AI pharmaceutical field is still in the initial stage of development, and there is still a long way to go before the industry matures
.
For emerging AI pharmaceutical companies, opportunities and challenges will coexist
.
