Shiyao Group has once again achieved a heavyweight business development.

Recently, Shiyao announced that it has reached a BD agreement with BeiGene regarding the group's new methionine adenosyltransferase 2A (MAT2A) inhibitor, SYH2039, granting BeiGene the global development and commercialization rights for the pipeline.

And the amount of BD this time is also very astonishing: Shiyao Group will receive a total advance payment of $150 million, and has the right to receive up to $135 million in potential development milestone payments and up to $1.55 billion in potential sales milestone payments, as well as tiered sales commissions calculated based on the annual net sales of the product.

It is worth mentioning that the compound was selected by Shiyao through AI technology. Previously, Shiyao also provided AstraZeneca with a high priced BD through a preclinical pipeline screened by AI technology.

The stone medicine AI has exploded.

01 Why is it stone medicine?

The molecule involved in this BD transaction is a MAT2A inhibitor, which is also a relatively new targeted drug. Methionine adenosyltransferase (MAT) is involved in the key transformation of S-adenosylmethionine (SAM), which plays an important role in protein and DNA methylation. The imbalance of methionine cycle metabolism has been found to be a potential direction for cancer, manifested by elevated levels of related indicators detected in most cancers, with MAT2A being a typical example.

MAT2A is the catalytic subunit of MATII (an isomer of MAT) and plays an exceptionally critical role in the aforementioned biochemical reactions. More importantly, high expression of MAT2A has been observed in various cancers, such as liver cancer, colon cancer, gastric cancer, and non-small cell lung cancer. Inhibition of this target can lead to precise death of cancer cells. In addition, the combination of MAT2A inhibitor and PRMT5 inhibitor has a synergistic effect.

Therefore, the inhibition of MAT2A has become a new development direction for small molecule targeted drugs. Currently, a typical pipeline under research is IDEAYA's IDE397, which just released positive clinical phase II data in non-small cell lung cancer and urothelial carcinoma this year.

The same target inhibitor SYH2039 of Shiyao was approved for clinical use in China and the United States in March and April this year, respectively. Pre clinical trials have shown that this molecule can effectively inhibit the growth of a variety of MTAP deficient tumor cells, such as non-small cell lung cancer, glioma, gastroesophageal cancer, pancreatic cancer and bladder cancer.

Why did BeiGene acquire this drug? As mentioned earlier, the combination of MAT2A inhibitor and PPMT5 inhibitor theoretically has a very good synergistic effect. Currently, BeiGene has a pipeline for PPMT5 inhibitors. In September of this year, its related pipeline BGB-58097 clinical trial application was accepted by CDE. Currently, the fastest progress of related pipelines is in the United States, and the fastest progress in China is only in Shiyao. Therefore, this BD will occur between Shiyao and BeiGene.

In addition, the amount of BD this time is also very interesting: the advance payment amount has reached 150 million US dollars, but the milestone payment for research and development is only 135 million US dollars, and the large potential milestone payments are all in commercialization. That is to say, this transaction has exceeded most of the expected R&D progress in advance, which can be understood as spending most of the milestone expenses that should have been incurred during R&D in the advance payment.

Speculatively, on the one hand, it may be due to the remarkable therapeutic effect of the molecule, and on the other hand, it may be due to the current scarcity of the molecule, which is the only one in China that has entered clinical trials and is jointly promoted by China and the United States. This is very consistent with BeiGene's own strategy. Handing over the commercialization of this drug in the United States to Baekje in the future is also a win-win cooperation.

02 High quality AI platform

As is well known, in the field of AIDD (AI drug design), the development speed of small molecules is much faster than that of large molecules, and there are now many companies that discover small molecule drugs.

There are mainly two categories here: one is mainly engaged in R&D outsourcing through its platform, mainly represented by Jingtai Technology. Of course, Jingtai Technology has not limited its business to the pharmaceutical field. The other type is AIDD enterprises with their own pipelines, which can be understood as biotech, and the most typical one is Yingsi Intelligence. Of course, Yingsi Intelligence currently has a portion of its revenue coming from licensing cooperation on its technology platform.

And Shiyao has already signed cooperation agreements with Yingsi Intelligent and Jingtai Technology. In August last year, Shiyao Group announced a strategic cooperation with Jingtai Technology and Yingsi Intelligent. Based on the cooperation agreement, Shiyao Group will combine its own drug research and development experience with Yingsi Intelligent and Jingtai Technology on the leading AI technology platform, focusing on strategic products with high clinical demand, using AI to assist drug design, improve the efficiency and success rate of new drug screening, and jointly promote the research and development of innovative drugs.

The author predicts that Yingsi Intelligent's Pharma The AI platform has greatly empowered stone medicine.

PharmaAI consists of three parts: Biology42, Chemistry42, and Medicine42.

Biology42 is used for target discovery and prioritization, consisting of three parts: PandaOmics, Generative Biologics, and LifeStar 1.

PandaOmics: Systems biology research across data types, aimed at facilitating the discovery of new targets or prioritizing established targets for diseases of interest, providing target identification and biomarker recognition based on molecular features and clinical data correlations.

Generative Biologics: Using generative models to design and evaluate proteins, predict protein interactions, and generate protein sequences to perform protein generation for selected targets.

Star of Life 1: Analyze the input cell line samples, and then use PandaOmics' algorithm to analyze the generated data to identify potential candidate targets, compounds, and biomarkers. In addition, LifeStar 1 can further promote the maintenance and testing of these cell line samples to determine whether the desired effects can be achieved through the use of selected targets, compounds, and biomarkers.

Chemistry42- Generate novel small molecules and determine their properties. Composed of four parts: Generative Chemistry, Golden Cubes, ADMET Predictors, and Alchemist.

Medicine42- Prediction of Clinical Trial Results. Composed of inLinico application data. Using AI algorithms to analyze publicly available data, including the chemical structure of drugs, past clinical data, past clinical protocols, public publications, subsidies, and patents. The goal is to build a knowledge graph and then use it to train machine learning models. Use this model to predict the probability of successful experiments and evaluate the impact of specific experimental design features on the overall success rate.

Not only stone medicine, but also Pharma from Yingsi Intelligent AI platforms have also gained favor from other large pharmaceuticals.

03 The stone medicine AI has exploded

For AIDD small molecules, the future trend is inevitably to significantly shorten the drug discovery process, thereby greatly accelerating their entry into the clinical stage. According to the prospectus of Insilicon Intelligence, its PandaOmics platform can quickly discover new targets by comparing multiple omics data. In the preclinical stage, its AI technology shortens the research and development cycle to 11-18 months, with an overall investment of less than 2.7 million US dollars, while traditional methods often require 5 years and hundreds of millions of dollars.

The shortened preclinical time and cost have greatly accelerated the development speed of small molecule drugs, turning them into factories for mass production of innovative drug molecules. The increase in molecules also means an increase in opportunities for drug development. The future trend is likely to be AIDD enterprises' bulk production of pipeline BD.

This trend was first realized in the pharmaceutical industry of Shiyao.

Firstly, a few months ago, we collaborated with AstraZeneca to advance the development of a preclinical innovative small molecule lipoprotein (a) (Lp (a)) inhibitor - YS2302018. According to the terms of the agreement, Shiyao Group will receive a $100 million advance payment and is entitled to receive up to $370 million in potential development milestone payments and up to $1.55 billion in sales milestone payments, totaling $2.02 billion.

Afterwards, it was the BD of this stone medicine and Baekje.

Shiyao has become the first pharmaceutical company to implement the AIDD batch BD model, which is a successful example of a traditional Chinese pharmaceutical company transitioning from imitation to innovation.