YuLu QianXing and Anshi Biologics: Two Years of Collaboration Demonstrating the Value of AIDD for Medicinal Chemistry Teams

As a client of Yulu Qianxing, Anshi Biopharma has established a two-year collaborative partnership. The AIDD team at Yulu Qianxing and the medicinal chemistry team at Anshi Biopharma have joined forces to achieve phased milestones across multiple targets, including EGFR exon 20 insertion mutations, c-Met, and NTRK resistance mutations. Notably, the EGFR program has completed Phase I clinical trials, while the c-MET program represents the world’s only second-generation c-MET inhibitor currently in development. The collaboration between the two teams has delivered synergistic outcomes, exceeding the sum of their individual contributions. In today’s interview, Dr. Li Gong, Director of Medicinal Chemistry at Anshi Biopharma, will review the partnership with Yulu Qianxing from the following three perspectives:

• Why did Anshi Biologics choose Yulu Qianxing’s services at that time?

• What specific roles does AIDD play across different project pipelines?

• What value can the AIDD team provide to the medicinal chemistry team?

Dr. Zheng Zheng, Founder of YuluganxingAlso respond to the following two aspects in the dialogue:

• Optimal Collaboration Framework Between the AIDD Team and the Medicinal Chemistry Team

• What Role Does AI Play in Molecular Dynamics Methods? How Accurate Can Its Calculations Be?

Dr. Li Gong of Anshi and Dr. Zheng Zheng of Yulu Qiankunxing in Dialogue at the 2022 World Summit on Medical Technology

Dr. Zheng Zheng, Founder of Yulu Qianxing

Ph.D. in Chemistry from the University of Florida, USA; B.S. in Pharmacy from Peking University; Studied under Professor Kenneth Merz, a world-leading expert in computational chemistry; Expert in computer-aided drug design and machine learning, and inventor of core project algorithms; Senior Scientist at QuantumBio, Inc., a US-based drug design software company; Professor and Doctoral Supervisor at Wuhan University of Technology; Selected for Hubei Province’s “Hundred Talents Program”; Recipient of the China Industry-University-Research Cooperation Innovation Award and recognized as a Science and Technology Leading Talent in Suzhou Industrial Park; Has published over 40 academic papers in top-tier international journals and authored one academic monograph; Principal Investigator or Co-Investigator on two NIH projects in the US and one project funded by the National Natural Science Foundation of China; Led the commercial translation of multiple international patents; Serves as an Editorial Board Member for the Journal of Chemical Information and Modeling (J. Chem. Inf. Model.), a premier international journal in cheminformatics.

Dr. Li Gong, Director of Medicinal Chemistry at Anshi Bio

Ph.D. in Chemical Biology from Peking University; led the discovery of candidate compounds for two innovative drug projects (ANS01, ANS03) at Anshi Biologics, developing a novel MET inhibitor to address resistance issues associated with existing products. The ANS03 project breakthroughly resolves multiple resistance mutations—including solvent front, gatekeeper, DFG motif, and compound mutations—overcoming the limitation of current clinical competitors that only address partial mutational resistance, with no international competitors.

Li Gong, Anshi:Beijing Anshi Biopharma, located in the Wangjing Technology Park in Chaoyang District, Beijing, is a biotechnology company dedicated to the research and development of innovative small-molecule drugs. In 2020, we were introduced to Mr. Zheng from Yulu Qianxing through a mutual friend, and our collaboration gradually commenced.

At that time, Anshi Biotech was stillCompared to the traditional drug chemistry-driven approachbiotechnology companies, which are struggling with the widespread lack of support for structural biology, molecular biology, and translational medicine in China, regardingSome highly original R&D efforts leave one feeling helpless and unsure of where to begin.Therefore, Anshi is also in urgent need of finding a CRO that can support innovative work, especially in the field of exploring structures and molecular mechanisms, including but not limited to computational chemistry or artificial intelligence. This can make up for the company's shortcomings, promote our unique projects based on clinical translation, and accelerate verification and development.

By a stroke of serendipity, we came to know Mr. Zheng, General Manager of Yulu Qianxing. Through background research, we learned that Yulu Qianxing is a companyNot only develops its own algorithms, but also has a background in pharmacy., which strongly motivates us to further pursue collaboration. If Anshi were to choose a company that provides only software services, although confidentiality would be high, limitations in professional expertise regarding software utilization and in-depth understanding of data might lead us astray. Another concern is the communication gap between pharmaceutical development teams and algorithm engineers.Yulu Qianxing combines pharmaceutical expertise with computational capabilities, which we believe can better support Anshi in pursuing more focused and targeted innovation, aligning closely with Anshi’s needs.

After someIn initial trials, Yu Luqianxing delivered some impressive results for Anshi., which has further strengthened Anshi’s desire to engage in deep collaboration with Yulu Qianxing and transform into an AI-powered biotechnology company.

For the EGFR exon 20 insertion product from Anshi, Yulu Qianxing has passedAnalysis of Protein Dynamic Mechanisms, providing a clear and in-depth understanding of the molecular mechanisms underlying the disease caused by this mutation. Meanwhile, Yulu Qianxing conducted dynamic binding simulation and kinetic analyses of molecules and proteins,Elucidated the mechanistic differentiation and potential advantages of our product compared to existing clinical competitors.

From a mechanistic perspective, the analysis provided by Yulu Qianxing also offers usConfidence in Continuing Clinical Development Exploration, includingBy increasing the dose, to evaluate various clinical mutations in terms of both efficacy and safety.. In fact, we already achieved very promising efficacy in the Phase I clinical trial and identified a safe recommended Phase II dose.

Dynamic Conformational Differences in EGFR Insertion Mutations Revealed by Molecular Dynamics Simulations

In addition, Yulu Qianxing and Anshi have also collaborated on another flagship project of the company: a next-generation inhibitor targeting c-MET resistance mutations, which is the world’s only second-generation c-MET inhibitor. Leveraging dynamic molecular simulations of protein structures and ADMET property prediction services provided by Yulu Qianxing, we have conducted targetedStructural Modification,Currently, the project is in the phase of organizing IND-enabling data, preparing for simultaneous Investigational New Drug (IND) applications in both China and the United States.

Meanwhile, leveraging Yulu QianxingPrecise Virtual ScreeningSelect, we have identified a highly promising structural fragment. Through structural integration and further optimization, we have developed a candidate capable of overcoming nearly all clinically common NTRK resistance mutations, including those in the solvent front, gatekeeper region, and DFG motif, as well as certain compound mutations. This represents a globally uncontested pipeline, with no similar projects reported that meet such high standards and barriers to entry.

In summary, our collaboration is primarily divided into three aspects.

First, from the perspective of protein simulation, we have gained a clearer understanding of the dynamic trajectories and even the spatiotemporal existence states of proteins than what co-crystal structures provide, enabling us to predict and deduce the pathogenic molecular mechanisms induced by mutations;

Secondly, dynamic simulations of molecules and proteins enable a better understanding of their modes of action, advantages, and limitations, and also allow for the prediction of the accessibility of interactions with specific target amino acids;

Finally, through virtual screening, Yulu Qianxing has provided us with an option for generating hit compounds or novel scaffolds. In just two short years, Yulu Qianxing’s support for our company and projects has been immense.

Mechanism of Virtual Screening for Luqian Action Dynamics

Let me provide a brief introduction to Beijing Anshi Biopharma. Established in 2018, Beijing Anshi Biopharma merged with Beijing Purun Ao in 2021. Beijing Purun Ao is a company specializing in clinical development, with years of accumulated experience and expertise. Following the integration, Anshi Biopharma has become a comprehensive biopharmaceutical R&D company covering all stages from preclinical discovery to clinical development. In December 2021, the company completed its first round of financing, raising over USD 200 million, led by three major US-dollar funds: Vivo Capital, Bain Capital, and Primavera Capital.

Currently, our primary pipeline is focused on two targets: EGFR and c-MET. Bozitinib, the c-MET-targeted product acquired through the merger with Purunao, completed its New Drug Application (NDA) submission this September. We anticipate generating commercial revenue next year, thereby facilitating our transformation into a Biopharma company.

Another key asset is our EGFR exon 20 insertion inhibitor program. Phase I clinical trials have been largely completed, and a highly favorable recommended Phase II dose has been identified. Further clinical efficacy data are expected to be disclosed next year. Since 2020, Anshi has maintained an in-depth strategic partnership with Mr. Zheng from Yulu Qianxing. Notably, our next-generation kinase inhibitor addresses resistance mutations associated with existing clinical products and holds the potential to explore more challenging indications. Furthermore, our pipeline candidates can be used in combination regimens to overcome resistance mechanisms not addressed by current therapies, thereby further meeting unmet clinical needs.

We are confident that the partnership between Future and Yulu Qianxing will continue, with both companies supporting each other to go further together, thereby laying a solid foundation for Anshi Biopharma to truly transform into an innovative biopharmaceutical company.

To Lu Qianxing and Zheng Zheng:Yulu Qianxing has been providing services to Anshi for two years. Throughout our collaboration, we have felt Anshi’s recognition of our work.

From my perspective, every new drug company should have an AIDD team. Based on our collaboration with Anshi and combined with our experience working with numerous pharmaceutical companies in the United States, we feelA genuine AIDD team should be an integral part of the medicinal chemistry team.. As a provider of computational tools, AIDD can deliver insights that experiments are unable to provide from many perspectives. In such relatively high-dimensional and highly complex scenarios, certain aspects remain beyond the reach of human intuition or even the expertise of medicinal chemists.

By leveraging computational methods to provide more accurate predictions and integrating the expertise of medicinal chemists for final decision-making, we believe this is the most effective approach to advancing early-stage drug molecule discovery.

Currently, there is a relative scarcity of AI-driven drug discovery (AIDD) experts in China, and not all companies have dedicated AIDD teams. Our company’s positioning is to serve as AIDD and computer-aided drug design (CADD) experts within the medicinal chemistry teams of our pharmaceutical partners. Through our collaboration with Dr. Li Gong’s team, we have gradually established this well-defined role in our partnerships with innovative drug companies.

To Lu Qianxing and Zheng Zheng:In many drug development efforts, particularly at the molecular level, there are physics-based models that serve as highly interpretable, precise explanatory models.

However, current computational power is insufficient to fully rely on analytical models for calculations in relatively complex macromolecular scenarios. Therefore, we integrate AI to achieve a balance between accuracy and speed.

Yulu Qianxing's Underlying Force Field and Algorithm Technologies

In pure AI-driven drug discovery (AIDD), or through statistical approaches, we utilize static or sequence-based information to derive values that we consider relevant to certain drug indications. However, if such statistical models are used exclusively, it becomes difficult to assess the interpretability of these values and the accuracy of the predictions.

When using physical models, the theoretical accuracy is reliable. The current upper limit for physical models is generally considered to be 1–2 kcal/mol. By combining with experimental data, we can achieve an accuracy of approximately 0.6–0.8 kcal/mol, which closely approximates the true values.

In our collaboration with Anshi, we believe that the primary value of physical models, or molecular dynamics simulations, lies in their ability to provide conformational probability distributions. For specific interactions, such as hydrogen bonds between drug molecules and target groups, we can not only determine whether such interactions exist but also quantify the probability of their stable formation throughout the dynamic process.

Some hydrogen bonds can be identified using traditional methods, while others are less stable, exhibiting only a 20% or 30% probability of formation under stable dynamic conditions. Consequently, they offer relatively fewer advantages compared to other structural features. This is where physical models play a more significant role.

Yulu Qianxing leverages AI models to enhance the efficiency of physical models, which forms our underlying logic. I am also very pleased to see that the collaboration between Yulu Qianxing and Anshi Biopharma has indeed provided a boost to certain projects.

Anshi Biotech is a Chinese innovative pharmaceutical company with two wholly-owned subsidiaries: Beijing Purunao Biotechnology Co., Ltd., established in 2012; and Beijing Anshi Biotechnology Co., Ltd., established in 2018.

Anshi Biotech is dedicated to the health services industry, with a mission to provide patients with high-quality pharmaceutical products. The company focuses on the research and development of innovative anti-tumor drugs, maintaining multiple drug development pipelines. Its primary R&D direction is centered on “First-in-Class” and “Best-in-Class” innovative therapeutics in the field of oncology, covering various cancer treatment areas including lung cancer and glioma.

Anshi Biotech is committed to enhancing patients’ quality of life by providing high-quality innovative medicines and serving human health through continuous innovation. Leveraging its comprehensive platform for innovative drug research and development, the company drives the industrialization of pharmaceuticals and contributes to the growth of China’s domestic pharmaceutical industry.

Yu Lu Qian Xing is an interdisciplinary, technology-driven biopharmaceutical company that leverages artificial intelligence, quantum mechanics, and molecular simulation algorithms as its core technologies to empower new drug development through computational simulations.

In 2021, the company integrated its proprietary AI technology with core algorithms for high-precision molecular dynamics simulations to establish an internationally leading, next-generation artificial intelligence platform for drug discovery and development. This AI-driven R&D platform primarily focuses on high-precision structural elucidation and simulation of physiological dynamic processes for uncharacterized targets and highly flexible targets, thereby enabling the development of novel therapeutics against historically “undruggable” targets. Since its inception, the company has been recognized as a Technology Leader Enterprise in the Suzhou Industrial Park. Currently, the company collaborates with multiple domestic and international biopharmaceutical partners to advance several new drug development pipelines, achieving breakthrough results in multiple therapeutic areas targeting undruggable targets.

UtilizeMolecular Dynamics + AI AlgorithmsPlatform

ExpansionUndruggableTrack, ShortenNew Drug DevelopmentCycle

Committed toFirst In ClassInnovation