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Recently, AI drug research and development company XtalPi and Signet Therapeutics have made significant progress in the diffuse gastric cancer project.
The molecules designed, synthesized and optimized by XtalPi are about to enter the IND-enabling stage.
In just over half a year, significant progress has been made, and it has helped Siegsenko complete an angel round of financing of approximately RMB 60 million.
This cooperation once again verified the one-stop drug discovery capability of Jingtai Technology of "AI algorithm + drug experiment + expert experience".
Whether it is a First-in-class project or a Fast Follow-on project, for a given target, Jingtai Technology can quickly obtain high-quality preclinical candidate compounds (PCC).
The project started in 2020.
With a deep understanding of the mechanism of the disease, the founding team Siegsenko from the Dana-Farber Cancer Institute found a specific target for diffuse gastric cancer for the first time in the world, and decided to use Jingtai The technological AI platform is rapidly advancing the discovery of new drugs.
Jingtai Technology used the new drug discovery model of "AI algorithm + expert experience + drug experiment" to formulate a full set of artificial intelligence drug discovery solutions for the project, including early-stage target information collection and screening, AI model construction and evaluation, and new The generation and design of molecules, combined with the experience evaluation of medicinal chemists, completes the work of molecular design, synthesis, in vitro activity and PK characterization.
Subsequently, Sigma Biosciences used its proprietary disease model screening and evaluation mechanism to conduct biological and functional experimental verification of candidate molecules recommended by Jingtai Technology, and feedback the experimental results.
In the specific research and development process of this diffuse gastric cancer target project, Jingtai Technology first used the self-developed artificial intelligence drug discovery platform (ID4 platform) to generate millions of compound molecules, and through AI technology and high-precision computational chemistry tools, Calculate and evaluate the various properties of the generated molecules (such as activity, selectivity, drug-like properties, novelty, synthesizable, etc.
), and quickly converge millions of molecules to nearly a hundred molecules.
After that, medicinal chemists screened and evaluated nearly a hundred molecules, selected 10-20 molecules for synthesis and testing, and fed the experimental results back to the ID4 platform to complete the iteration and carry out a new round of molecular generation.
Each round of molecule generation only takes about 2 weeks.
Artificial intelligence and high-precision computational chemistry methods can not only significantly improve the efficiency of drug research and development, but also break through the limitations of the diversity of the existing drug small molecule library, and obtain a new (de novo) drug molecular skeleton, which is a great impact on existing drug research and development.
Has a very important meaning.
In the future, the cooperation between Jingtai Technology and SigmaBio will be more in-depth.
In addition to the existing cooperation pipeline, SigmaBio’s accumulation of data on functional biology platforms, such as organoids, PDO, and PDX, will be greatly improved.
Improve the accuracy of the prediction of the drug function level of the Jingtai Technology AI model "after the molecular level, before the IND", and expand the operation space of the Jingtai Technology AI.
During the progress of this project, Sigma Biosciences fully demonstrated the evaluation advantages of the functional biology platform, established exclusive disease models for the project, and evaluated candidate design compounds more quickly and efficiently.
At the same time, through the experimental data generated in real projects fed back by Sigma Biotech, the accuracy of the AI model prediction of Jingtai Technology has also been rapidly improved, which has facilitated the rapid progress of the project.
About XtalPi Technology XtalPi (XtalPi) is an artificial intelligence (AI) drug research and development technology company driven by digitization and intelligence.
Based on quantum physics, quantum chemistry, artificial intelligence and cloud computing technology, XtalPi provides intelligence for global innovative pharmaceutical companies Chemical drug research and development services.
We hope to help partners bring more high-quality drugs to patients by improving the efficiency and success rate of key links in drug research and development, and reducing research and development costs.
Jingtai Technology was founded on the campus of the Massachusetts Institute of Technology (MIT).
The core team is composed of outstanding talents from academia, IT, Internet, and the pharmaceutical industry.
The company is headquartered in Shenzhen, and has branches in Beijing, Shanghai, and Boston.
Since its establishment, Jingtai Technology has successfully provided drug R&D services to more than 70 pioneer pharmaceutical companies from the United States, Europe, China, and Japan.
About Signet Therapeutics Signet Therapeutics is a cancer-based innovative targeted drug research and development company based on disease models.
Sigma Bioscience was established at the end of 2020.
It was originally founded on the campus of Harvard University.
The core team is composed of outstanding talents from the academic circles of Harvard University, MIT and the Chinese Academy of Sciences, as well as the pharmaceutical industry.
Headquartered in Shenzhen, and has a branch in Boston, USA.
SIG is not only the transliteration of Signet, but also adhering to the vision of "Hopeful, knowledge and knowledge".
Through the professional, cutting-edge and pursuit of the ultimate effort of the company team, the current cancer patients with no medicines are full of hope, and they are committed to precision targeting.
Treatment turns highly lethal malignant cancers into manageable chronic diseases and makes unremitting efforts.
For business inquiries, please contact bd@xtalpi.
com-END-+ recommended reading,
The molecules designed, synthesized and optimized by XtalPi are about to enter the IND-enabling stage.
In just over half a year, significant progress has been made, and it has helped Siegsenko complete an angel round of financing of approximately RMB 60 million.
This cooperation once again verified the one-stop drug discovery capability of Jingtai Technology of "AI algorithm + drug experiment + expert experience".
Whether it is a First-in-class project or a Fast Follow-on project, for a given target, Jingtai Technology can quickly obtain high-quality preclinical candidate compounds (PCC).
The project started in 2020.
With a deep understanding of the mechanism of the disease, the founding team Siegsenko from the Dana-Farber Cancer Institute found a specific target for diffuse gastric cancer for the first time in the world, and decided to use Jingtai The technological AI platform is rapidly advancing the discovery of new drugs.
Jingtai Technology used the new drug discovery model of "AI algorithm + expert experience + drug experiment" to formulate a full set of artificial intelligence drug discovery solutions for the project, including early-stage target information collection and screening, AI model construction and evaluation, and new The generation and design of molecules, combined with the experience evaluation of medicinal chemists, completes the work of molecular design, synthesis, in vitro activity and PK characterization.
Subsequently, Sigma Biosciences used its proprietary disease model screening and evaluation mechanism to conduct biological and functional experimental verification of candidate molecules recommended by Jingtai Technology, and feedback the experimental results.
In the specific research and development process of this diffuse gastric cancer target project, Jingtai Technology first used the self-developed artificial intelligence drug discovery platform (ID4 platform) to generate millions of compound molecules, and through AI technology and high-precision computational chemistry tools, Calculate and evaluate the various properties of the generated molecules (such as activity, selectivity, drug-like properties, novelty, synthesizable, etc.
), and quickly converge millions of molecules to nearly a hundred molecules.
After that, medicinal chemists screened and evaluated nearly a hundred molecules, selected 10-20 molecules for synthesis and testing, and fed the experimental results back to the ID4 platform to complete the iteration and carry out a new round of molecular generation.
Each round of molecule generation only takes about 2 weeks.
Artificial intelligence and high-precision computational chemistry methods can not only significantly improve the efficiency of drug research and development, but also break through the limitations of the diversity of the existing drug small molecule library, and obtain a new (de novo) drug molecular skeleton, which is a great impact on existing drug research and development.
Has a very important meaning.
In the future, the cooperation between Jingtai Technology and SigmaBio will be more in-depth.
In addition to the existing cooperation pipeline, SigmaBio’s accumulation of data on functional biology platforms, such as organoids, PDO, and PDX, will be greatly improved.
Improve the accuracy of the prediction of the drug function level of the Jingtai Technology AI model "after the molecular level, before the IND", and expand the operation space of the Jingtai Technology AI.
During the progress of this project, Sigma Biosciences fully demonstrated the evaluation advantages of the functional biology platform, established exclusive disease models for the project, and evaluated candidate design compounds more quickly and efficiently.
At the same time, through the experimental data generated in real projects fed back by Sigma Biotech, the accuracy of the AI model prediction of Jingtai Technology has also been rapidly improved, which has facilitated the rapid progress of the project.
About XtalPi Technology XtalPi (XtalPi) is an artificial intelligence (AI) drug research and development technology company driven by digitization and intelligence.
Based on quantum physics, quantum chemistry, artificial intelligence and cloud computing technology, XtalPi provides intelligence for global innovative pharmaceutical companies Chemical drug research and development services.
We hope to help partners bring more high-quality drugs to patients by improving the efficiency and success rate of key links in drug research and development, and reducing research and development costs.
Jingtai Technology was founded on the campus of the Massachusetts Institute of Technology (MIT).
The core team is composed of outstanding talents from academia, IT, Internet, and the pharmaceutical industry.
The company is headquartered in Shenzhen, and has branches in Beijing, Shanghai, and Boston.
Since its establishment, Jingtai Technology has successfully provided drug R&D services to more than 70 pioneer pharmaceutical companies from the United States, Europe, China, and Japan.
About Signet Therapeutics Signet Therapeutics is a cancer-based innovative targeted drug research and development company based on disease models.
Sigma Bioscience was established at the end of 2020.
It was originally founded on the campus of Harvard University.
The core team is composed of outstanding talents from the academic circles of Harvard University, MIT and the Chinese Academy of Sciences, as well as the pharmaceutical industry.
Headquartered in Shenzhen, and has a branch in Boston, USA.
SIG is not only the transliteration of Signet, but also adhering to the vision of "Hopeful, knowledge and knowledge".
Through the professional, cutting-edge and pursuit of the ultimate effort of the company team, the current cancer patients with no medicines are full of hope, and they are committed to precision targeting.
Treatment turns highly lethal malignant cancers into manageable chronic diseases and makes unremitting efforts.
For business inquiries, please contact bd@xtalpi.
com-END-+ recommended reading,
