-
Categories
-
Pharmaceutical Intermediates
-
Active Pharmaceutical Ingredients
-
Food Additives
- Industrial Coatings
- Agrochemicals
- Dyes and Pigments
- Surfactant
- Flavors and Fragrances
- Chemical Reagents
- Catalyst and Auxiliary
- Natural Products
- Inorganic Chemistry
-
Organic Chemistry
-
Biochemical Engineering
- Analytical Chemistry
-
Cosmetic Ingredient
- Water Treatment Chemical
-
Pharmaceutical Intermediates
Promotion
ECHEMI Mall
Wholesale
Weekly Price
Exhibition
News
-
Trade Service
It usually takes more than 10 years for a new drug to go from development to market, and hundreds of millions of dollars are consumed
.
Despite this investment, less than 10%
of the products were successfully approved for marketing.
Internationally renowned pharmaceutical companies often share the above costs and risks by raising drug prices, resulting in huge economic burdens
for patients.
For some people with rare diseases in smaller numbers, the situation is even worse
.
The problem of expensive R&D and difficult R&D is the core contradiction that restricts the research and development of new drugs, and has also become a fetter
on the road to recovery for countless patients.
But the turning point is coming, as artificial intelligence algorithms are successively applied in the field of new drug research and development, the cost, risk and cycle of research and development may usher in a significant decline
.
.
With the help of artificial intelligence algorithm platform to carry out pharmaceutical research and development, its core principle is to use various clinical databases, chemical molecular libraries, drug (and drug-like compounds) libraries and other data, through artificial intelligence algorithms such as Bayesian models, convolutional neural networks, decision trees, etc.
, to be completed manually, such as drug target discovery, protein receptor matching, active compound screening, etc.
, to be automatically completed
by computers.
Considering that there are often tens of thousands of possibilities such as drug targets and protein receptors, previous methods of human exploration often require a huge amount of time and materials
.
Computing platforms equipped with artificial intelligence only take a short time and the loss is close to zero
.
While reducing R&D costs, the speed of
R&D is greatly improved.
For example, researchers at MIT trained a deep neural network to predict molecules
with antimicrobial activity.
The system takes only a few days to screen 100 million compounds, which is simply not possible with human labor alone
.
In addition to new drug research and development, artificial intelligence also plays an excellent role
in exploring the field of new use of old drugs.
Due to the ability of artificial intelligence platforms to perform massive calculations in a short period of time, computers will independently explore more possibilities about targets and receptors, and discover new functional areas
that have not been explored before.
The new use of old drugs not only greatly shortens the development cycle, but also the development cost is only a quarter of that of
new drug development.
From the perspective of market development, the artificial intelligence pharmaceutical R&D platform track has the characteristics of
large growth potential and long-term fast growth.
According to the Internet Data Information Network (BCC), it is expected that
In 2024, the market size of artificial intelligence in the field of drug discovery will reach $3.
117 billion, with a compound annual growth rate (CAGR) of 40.
7%; According to Grand View
Research), the global AI+ drug discovery market is expected to reach $3.
5 billion by 2027, with a CAGR of 28.
8%.
The market potential for the future is huge
.
large growth potential and long-term fast growth.
The main players in the track mainly include two categories: the first is traditional technology companies (which have expanded their artificial intelligence platforms into pharmaceutical research and development) - Watson for Drug, which represents companies such as IBM
The Discovery platform and Google's Deep
Mind platform, etc
.
The second category is innovative companies specializing in the development of artificial intelligence pharmaceutical R&D platforms - representative companies such as Atomwise's CNN platform and Exscientia's Centaur
Biologist-driven platforms, etc
.
From the perspective of industry maturity, the products of the head platform have been recognized by a large number of well-known pharmaceutical companies, and the depth of cooperation is increasing
.
International leading artificial intelligence pharmaceutical R&D platforms such as Exscientia and Atomwise have been recognized by well-known pharmaceutical companies at home and abroad, including Pfizer, Merck, AstraZeneca, Huadong Pharmaceutical, WuXi AppTec, etc.
, and have continued to carry out in-depth cooperation
.
Domestic artificial intelligence pharmaceutical R&D platforms are also following suit, and have successively obtained cooperation opportunities
from well-known pharmaceutical companies such as Pfizer, Huadong Pharmaceutical, and Viva Pharmaceutical.
Representative companies include XtalPi, Finkun Intelligence, Bingzhoushi Biotechnology, etc
.
.
From the perspective of financing, the number of financing in this field in the past two years is relatively moderate, but the average amount of each financing is large
.
The reason may be related to the low number of companies participating in the track due to
its high technical threshold.
Among them, Insitro is the most representative, and the C round raised $400 million
.
Investors include Singapore's sovereign wealth fund Temasek, Google Investments, and Silicon Valley's famous A16Z (Anderson Horowitz).
Similarly, Wangshi Wisdom, the hope star of the domestic artificial intelligence pharmaceutical R&D track, has also received $100 million investment
from star funds such as the Greater Bay Area Common Home Development Fund, Lightspeed China, and Hillhouse Venture Capital.
The scale of Series D financing, the head company of the track, XtalPi, reached $400 million
.
.
From the perspective of financing regions, the innovation stars in the international market are still occupied by the United States
.
Domestic investment and financing activities are mainly concentrated in the three regions
of the Pearl River Delta, Beijing-Tianjin-Hebei and Yangtze River Delta.
.
In the last two years, the United States topped
the list with 12 companies receiving financing.
Although Canada ranks second, only 3 companies have received financing, and the number is still far from
the first place.
Figure 1 Number of international financing enterprises in 2021-2022 Source: Firestone Creation Industry Data Center
The regions with the largest number of financing for domestic AI pharmaceutical R&D companies are the Pearl River Delta and Beijing-Tianjin-Hebei
.
A total of 7 companies in the PRD received financing, but the distribution of cities was relatively even (4 in Shenzhen, 2 in Guangzhou and 1 in Hong Kong).
Although there are 7 companies in the Beijing-Tianjin-Hebei region, they mainly rely on Beijing's unique talent resources, resulting in all companies located in Beijing
.
The Yangtze River Delta ranked third, with a total of 5 enterprises (including 2 in Suzhou, 1 in Nanjing, 1 in Hangzhou and 1 in Shanghai).
Figure 2 Number of domestic financing enterprises from 2021 to 2022 Source: Firestone Creation Industry Data Center
Table 1 Global AI pharmaceutical R&D financing events from 2021 to 2022
Source: Flint Creation is compiled according to public information (Note: If multiple financings occur during the period, only the most recent one is recorded in the table)
Table 2 Financing events in the field of domestic artificial intelligence pharmaceutical R&D from 2021 to 2022
Source: Flint Creation is compiled according to public information (Note: If multiple financings occur during the period, only the most recent one is recorded in the table)
Details of representative financing events in the field of domestic artificial intelligence pharmaceutical R&D in 2022
Details of representative financing events in the field of domestic artificial intelligence pharmaceutical R&D in 2022Wangshi Wisdom: Completed $100 million Series B+ financing
Wangshi Wisdom: Completed $100 million Series B+ financingOn April 12, 2021, StoneWise, a platform technology company driven by artificial intelligence technology for the research and development of innovative drugs, announced the completion of Series B+ and Series B financing, with a total financing of US$100 million
.
The Series B+ financing was co-led by the Greater Bay Area Common Home Development Fund and Lightspeed China, while the Series B financing was led by Legend Capital
.
New shareholders CDH VGC (Innovation and Growth Fund) and Zhongding Capital, old shareholders such as Hillhouse Venture Capital, SIG Haina Asia, Changling Capital, and Linear Capital all followed suit
.
The financing will be mainly used to further attract top global talents, consolidate the industrialization of the Wangshi AI platform, accelerate the iteration speed of Wangshi AI technology innovation, and improve the efficiency
of empowerment.
This financing marks the dual engine of "molecular design platform + knowledge graph" created by Wangshi Wisdom, and is about to usher in the success
of AI platform to empower the industrialization of small molecule drug research and development.
XtalPi: $400 million Series D financing
XtalPi: $400 million Series D financingOn August 12, AI drug R&D company XtalPi has completed a $400 million Series D financing, led by HOPU Capital and OrbiMed, followed by China Biopharmaceutical Group and a number of internationally renowned institutions, and early shareholders such as Tencent Group, Sequoia Capital, and Wuyuan Capital continue to make additional investments
.
It is reported that the post-investment valuation of this financing exceeds 13 billion yuan
.
XtalPi has built an integrated intelligent drug R&D platform ID4 to provide intelligent drug R&D services
to innovative pharmaceutical companies around the world.
The company is headquartered in Shenzhen and has branches in Beijing and Boston
.
Fermion Technology: Completed 100 million yuan Series B financing
Fermion Technology: Completed 100 million yuan Series B financingGuangzhou Fermion Technology Co.
, Ltd.
(hereinafter referred to as "Fermion"), an AI+ new drug research and development company, recently announced the completion of a series B financing of more than 100 million yuan, with investors including iFLYTEK Venture Capital, Zhengxuan Capital, old shareholders Panda Capital and Challenger Venture Capital continuing to follow
.
This round of financing will be mainly used to promote the clinical phase 1 research of the company's core pipeline and the subsequent effectiveness proof of concept (POC), the preclinical development of other pipelines, and the further upgrade
of the company's AI drug development platform and team.
Deepin Zhiyao: Completed $15 million Series B financing
Deepin Zhiyao: Completed $15 million Series B financingDeepZhiyao, an AI new drug R&D company, received nearly US$15 million in Series B financing, exclusively invested
by Sequoia China.
Founded in September 2017, Beijing Deepin Zhiyao Technology Co.
, Ltd.
is a new drug research and development service provider, integrating the production and sales of innovative drug research and development equipment
.
Li Xing, founder and CEO of Deepin Zhiyao, said that this round of financing will be mainly used for product research and development and business development
in the field of AI+ pharmaceutical research and development.
Insilico: Completed $15 million Series D financing
Insilico: Completed $15 million Series D financingAI pharmaceutical company Insilico announced a D2 round of funding, this time by Prosperity7, a diversified venture capital fund owned by Saudi Aramco
Ventures led the investment
.
After this round of financing, Insilico has completed a cumulative Series D financing of $95 million, with a latest valuation of $3 billion
.
The company is an AI-driven, end-to-end innovative drug discovery company, and its founder, Dr.
AIex Zhavoronkov, has both a computer and bioinformatics background and is a pioneer
in drug discovery and anti-aging research with the help of GAN (Adversarial Generative Networking) and reinforcement learning.
AccutarBio: Completed tens of millions of dollars in strategic financing
AccutarBio: Completed tens of millions of dollars in strategic financingAI pharmaceutical company Accutar Biotechnology (Bingzhoushi Biotechnology) recently announced the completion of a new round of financing of tens of millions of dollars, Yunfeng Fund, Coatue, 3W
The Healthcare Fund participated in the investment
.
Previously
AccutarBio has received multiple financings with the participation of IDG Capital, YITU Technology, ZhenFund, etc.
, IDG Capital led AccutarBio's Series A financing in 2017, and has continued to increase its weight in subsequent financings, and is currently the largest institutional shareholder
of AccutarBio.
The company expects that by the end of 2022, a number of new drug products will enter the clinical research stage
.
Baitu Biologics: Completed a series A financing of 100 million US dollars
Baitu Biologics: Completed a series A financing of 100 million US dollarsBiotronic (Beijing) Intelligent Technology Co.
, Ltd.
completed A
Round of financing, investment institutions include GGV Jiyuan Capital, Baidu, Robin Li, etc.
, with a financing amount of more than 100 million US dollars
.
Baitu Shengke is positioned as an innovative drug research and development platform enterprise driven by the biocomputing engine, and was initiated and founded
by Baidu founder Robin Li.
This round of financing will be mainly used for technology research and development and talent introduction
.