BMS has two transactions exceeding one billion US dollars in two days, introducing new drugs and expanding AI-assisted new drug R&D cooperation

Recently, BMS can be described as the best
.

Many layouts, no TIGIT drug has been approved yet

TIGIT, T cell immunoglobulin and ITIM domain protein, is specifically expressed on NK cells and T cells, and interacts with PVRL2 and PVRL3 in PVR (CD155) and PVR-like proteins (which binds to PVR and PVRL3) CD96 and CD226 will compete with TIGIT for binding to PVR
.

These research findings need to be further in-depth and detailed research
.

At present, TIGIT has become another immune checkpoint that has attracted much attention after PD-1/PDL1 and CTLA4, but no relevant targeted drugs have been approved
.

These TIGIT inhibitors in the clinical stage are not only used in combination with PD-1/L1 to treat tumors, but also combined with darlimumab (targeting CD38)/rituximab (targeting CD20) to treat multiple cases Myeloma/B-cell non-Hodgkin’s lymphoma, combined with Pomalidimide (cereblon ligand) and chemotherapy for multiple myeloma, combined with pembrolizumab (PD-1 antibody) and CTLA-4 inhibitor / Lovatinib (tyrosine kinase inhibitor) three-drug combination for the treatment of melanoma, combined with zimberelimab (PD-1 monoclonal antibody) and AB928 (biadenosine receptor antagonist) for the treatment of NSCLC
.

In addition, in recent years, pharmaceutical companies have reached several deals around TIGIT inhibitors
.

AI helps new drug research and development, and many companies reach cooperation

A new drug needs to go through the four stages of drug discovery, preclinical research, clinical research, and approval and marketing from the idea to commercial sales.
Artificial intelligence (AI) technology can be applied to drug discovery, preclinical research, and drug discovery in drug development.
The five stages of clinical trials, drug production and sales promotion are mainly used for target discovery, compound synthesis, new indication discovery, compound screening, crystal form prediction, patient recruitment, optimization of clinical trial design, drug inspection, and academic promotion.
The scenario is conducive to improving the efficiency of new drug research and development and saving costs
.

At present, AI is mainly used in drug discovery and preclinical research, among which target discovery is the most popular field in AI+ drug research and development
.

It is reported that from 2013 to 2018, there were 170 AI-related business operations (such as mergers and acquisitions, cooperation, self-development, etc.
) of international pharmaceutical companies, and almost every international pharmaceutical company had cooperation with at least one AI company
.

This time, the cooperation between BMS and Exscientia is actually based on the existing cooperation.
In March 2019, Xinji (later acquired by BMS) reached a three-year cooperation with Exscientia to jointly explore the use of AI discovery and Research and development of tumor and immune drugs
.

In addition, this year, many companies have reached cooperation on AI to help the research and development of new drugs
.

       • On January 28, Tempus, a leader in the field of artificial intelligence and precision medicine, expanded the cooperation agreement with BMS to analyze and discover RNA-based targets;

       • On January 28, OSE and MAbSilico expanded their cooperation to use AI to promote the development of new antibody therapeutics;

       • On February 26, Roivant acquired SiKang Pharmaceutical for US$450 million in equity to improve computational drug discovery capabilities;

       • On March 2, Iktos and Pfizer reached an AI new drug development cooperation;

       • On March 25th, Jingtai Technology, an AI drug research and development company driven by digitization and intelligence, and Qingyu Pharmaceutical, a company focused on pioneering drug research and development, reached a strategic cooperation to carry out drug research and development cooperation on multiple anti-tumor drug targets;

       • On April 12th, NVIDIA and Schrödinger reached a strategic cooperation.
Schrödinger will use the NVIDIA DGX A100™ system to further expand the speed and accuracy of its computational drug discovery platform;

       • On April 16, Relay, a precision drug company that combines leading computing and experimental technologies to change the drug discovery process, announced the acquisition of ZebiAI.
ZebiAI is a machine learning (ML-DEL) that applies a large number of experimental DNA coding library data sets to drug discovery.
) Pioneer;

       • On April 27th, InveniAI® LLC, which applied advanced AI and machine learning in the field of drug discovery and development to achieve an innovative transformation, announced a multi-target drug discovery collaboration with Shiono Yoshi Pharmaceutical;

       • On May 12, Hebo Medicine and Baitu Biopharmaceutical reached a strategic cooperation agreement.
The cooperation will be based on Hebo Biopharma’s fully human genetically modified mouse platform, combined with Baitu Biopharma’s advantages in the field of artificial intelligence, according to The structure and biological characteristics of potential therapeutic targets, and the specific design of antibody drugs with advantageous physical and chemical properties and druggability
.