Insilico Medicine lists on Hong Kong Stock Exchange, showing AI drug discovery momentum with 2025’s largest Hong Kong biotech IPO

InSilico Medicine

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This initial public offering (IPO) raised a total of HKD 2.277 billion, achieving the largest biotech IPO in Hong Kong this year, as in the size of fundraising.

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Credit: Insilico Medicine

Hong Kong, China, December 30, 2025 --- Insilico Medicine (3696.HK), a clinical-stage drug discovery and development company driven by generative artificial intelligence (AI), is successfully listed on the Hong Kong Stock Exchange today, becoming the first AI-driven biotech company to go public in Main Board under Chapter 8.05 listing rules of the HKEX. This initial public offering (IPO) raised a total of HKD 2.277 billion, achieving the largest biotech IPO in Hong Kong this year, as in the size of fundraising.

“With this massively oversubscribed listing we set several world’s firsts further confirming Insilico’s validated leadership position in AI-powered drug discovery and development and the strength of our platform and pipeline. Insilico is dedicated to extending human productive longevity and this listing provides us with more resources to advance our mission”, says Alex Zhavoronkov, PhD, Founder and CEO, Chief Business Officer of Insilico Medicine. "Over the past few years, we set very clear industry benchmarks demonstrating that AI can help make drug discovery faster, cheaper, and deliver higher success rates in preclinical and early clinical development. We have validated the end-to-end capabilities of AI-empowered programs from novel target discovery to molecular generation, and then to preclinical and clinical stages. Going forward, we will continue to increase investment in our AI platform and innovative pipeline, accelerate the advancement of differentiated innovative programs into clinic, and bring truly accessible, affordable, and breakthrough treatment solutions to patients worldwide."

“Today marks not only an important step forward for Insilico Medicine, but also a new starting point for our deep integration of AI with life sciences and reshaping of the drug development paradigm”, says Feng Ren, PhD, Co-CEO and Chief Scientific Officer of Insilico Medicine. "With our self-developed AI platform, we have identified innovative targets and novel molecules with first-in-class or best-in-class potential across multiple disease areas, and several programs have already entered clinical development. We believe that the value of AI extends far beyond cost reduction and efficiency gains; it lies in continuously pushing the boundaries of foundational innovation.  Support from the capital markets will help us further enhance our AI platform, expand our pipeline, improve R&D efficiency, and collaborate with global partners to accelerate the translation of innovative medicines. Guided by a long‑term vision and driven by technology, we are committed to transform AI into real productivity that improves human health.”

 

Global Capital Endorsement: AI‑driven Biotech Lands on HKEX

As a global pioneer AI‑driven biotechnology company, Insilico’s Hong Kong listing, jointly sponsored by Morgan Stanley, CICC and GF Securities, attracted strong interest and active participation from both local and international investors. A total of 94,690,500 shares were offered globally, with 10% Hong Kong public offering, which was oversubscribed by approximately 1427.37 times, locking in subscription funds of over HKD 328.349 billion and setting a record for Hong Kong public offering subscription amount among non‑18A healthcare IPOs in Hong Kong during the year. The international offering accounted for 90% of the total, and was oversubscribed by 26.27 times, marking the most oversubscribed case in international placement among non‑18A healthcare IPOs in Hong Kong during the year.

In terms of cornerstone, Insilico introduced 15 cornerstone investors globally, including Lilly, Tencent, Temasek, Schroders, UBS AM, Oaktree, E Fund and Taikang Life Insurance, among others, forming an all-star line‑up covering global pharmaceutical leaders, internet giants, international sovereign funds and large asset managers, as well as leading Chinese mutual funds and insurances funds.

Notably, Lilly and Tencent for the first time subscribed as cornerstone investors in a biotechnology company, highlighting cross‑industry leaders’ recognition of and confidence in the AI‑driven R&D business. Additionally, Oaktree Capital, a long‑term U.S. investment institution, returned to the Hong Kong biotech market as a cornerstone investor for the first time this year, reflecting its continued optimism about the long‑term value of the capital market and innovative pharmaceuticals. Furthermore, several international institutional investors also made their first entry into the Hong Kong capital market through this offering, further enhancing Hong Kong’s position on the global capital map for healthcare and technology.

 

Racing Towards AI-first Innovation: From GANs Pioneer to Pharmaceutical Superintelligence

Insilico is at the forefront of generative AI application in life science research, aiming to tackle key scientific and technological challenges in life sciences from first principles using cutting‑edge generative AI. Since its inception, Insilico Medicine is committed to transparency and reproducibility, publishing hundreds of academic papers and presenting at frontier academic and industry conferences. 

In 2016, Insilico published a Nature Communications paper, proposing a novel computational method, iPANDA, to address core challenges in biomarker discovery and target-disease associations in omics data analysis. This pathway-based method has since evolved into multiple deep-learning generative algorithms behind Insilico’s AI‑powered biological research powering the PandaOmics platform. 

In 2019, Insilico’s publication in Nature Biotechnology described how its proprietary deep generative model, GENTRL, was used to discover a potent inhibitor of the kinase target DDR1. It took only 21 days from target identification to the generation of a molecule with drug‑like properties. This study is regarded as one of the landmark events in the rise of AI‑driven drug discovery and laid an important academic foundation for the widespread adoption of generative AI in drug discovery and development.

These two early academic papers, along with a series of other published fundamental research, laid a solid foundation for Insilico to build Pharma.AI, its integrated end‑to‑end platform spanning biology, generative chemistry, clinical development and scientific research. 

In 2025 alone, Insilico Medicine scientists published 9 papers in Nature-family journals and 10 papers in the American Chemical Society’s Journal of Medicinal Chemistry. 

Since 2020, the Pharma.AI platform has been launched and commercialized as a modular software suite, and its collaboration network has expanded globally. As of the latest practicable date, Insilico has entered into software licensing collaborations with 13 of the world’s top 20 largest pharmaceutical companies. 

By continuously iterating its algorithms, building proprietary multimodal data warehouses, and improving infrastructure and tooling, Insilico has consistently optimized the performance of the Pharma.AI platform and extended its capabilities into emerging areas such as sustainable chemistry and agriculture, driving deep integration of AI‑driven innovation across the entire life science value chain.

In December 2022, Life Star 1, the industry’s first fully automated biology laboratory independently constructed by Insilico, was officially put into operation. Highly integrated with Insilico’s AI platform, the lab closes the loop from in silico design to experimental validation, enabling a highly efficient “lights‑out factory” capable of unmanned operation. While supporting wet‑lab validation for both internal and partnered projects, it continuously accumulates high‑quality proprietary datasets to further power the evolution of the AI platform. In September 2025, the upgraded Life Star 2 was officially launched with significantly enhanced cross‑island equipment coordination and multi‑workflow parallel processing capabilities, establishing a more convenient, stable and highly scalable intelligent lab system through refined allocation algorithms and response mechanisms.

In 2025, Insilico first proposed the concept of Pharmaceutical Superintelligence, defining it as the next stage of AI‑driven drug R&D, which aims at a fully AI‑driven, autonomous, and intelligent system for drug discovery and development. Insilico’s experimentally-validated purpose-built models can now be used to make other frontier multimodal models including third-party models more intelligent and capable in multiple scientific discovery tasks. 

 

Global Leading AI R&D Capabilities: From First AIDD Milestone to Global Benchmarks

By integrating its proprietary AI‑enabled drug discovery platform with advanced automated laboratory capabilities, Insilico has significantly improved the efficiency of drug R&D in practice. It has not only delivered pioneering innovation milestones, but also established a benchmark for AI‑driven drug discovery. Compared with the average of 4.5 years typically required for traditional early‑stage drug R&D, Insilico reduced the average time from program initiation to preclinical candidate (PCC) nomination to 12–18 months across more than 20 in‑house programs between 2021 and 2024, with only 60–200 molecules synthesized and tested per program.

The most representative example is Rentosertib (ISM001‑055), a novel mechanism‑of‑action candidate for idiopathic pulmonary fibrosis (IPF) empowered by AI. This program is considered the most advanced first‑in‑class AI‑discovered drug currently in development. Insilico completed the early discovery phase in just 18 months and identified the PCC after screening and testing only 78 molecules. The AI‑driven R&D journey of this program, from target discovery and molecule design through to Phase I clinical studies, was published in Nature Biotechnology in March 2024, providing the first systematic demonstration of an AI‑enabled, end‑to‑end drug discovery process from scratch.

Also in 2024, Insilico completed the China Phase IIa clinical trial for Rentosertib, with favorable safety and tolerability demonstrated, as well as an emerging dose‑dependent efficacy trend in IPF patients, indicating the potential to reverse the disease progression. The results were published in Nature Medicine in May 2025 and are regarded as the first clinical proof‑of‑concept milestone in the AI drug discovery field, providing valid practical evidence for AI‑driven drug discovery.

In addition, Insilico continues to extend its specialized AI‑driven capabilities into more areas of high unmet medical needs, building a structured portfolio of more than 30 programs centered around key therapeutic areas including fibrosis, oncology, immunology, inflammation, cardiometabolics and central nervous system (CNS) disease. Among all the innovative pipelines, 10 have received IND clearance, 7 of them are currently in active clinical development.

Meanwhile, AI‑driven R&D collaborations and pipeline out‑licensing are expanding. As of the latest practicable date, Insilico has achieved 3 out‑licensing deals with global pharmaceutical companies including Exelixis and Menarini, with the maximum total deal value up to$2.1 billion. Furthermore, co‑development partnerships with global pharma leaders including Fosun Pharma, Sanofi and Lilly provide solid validation and powerful boost for the value of AI applications in the global drug discovery industry.

 

AI&DD Dual‑engine Drive: Global Appearance Attract Long‑term Support for Industry Paradigm Shift

Since its founding in the United States in 2014, Insilico Medicine has expanded its business to four continents with the pioneering AI&DD dual‑engine management model, driving an in-depth combination of AI algorithm innovation and drug development expertise to achieve efficient and balanced growth. As of the latest practicable date, under the leadership of its two Co‑CEOs, Insilico boasts an R&D team of 249 experienced scientists, with master and doctorate degree holders accounting for 87% of this highly international team.

Under this dual‑engine management framework, the two core leaders bring their unique strengths to work in close synergy. Alex Zhavoronkov, PhD, Founder, Chief Executive Officer and Chief Business Officer of Insilico, focuses on the application of cutting‑edge AI technologies and is responsible for overall corporate strategy and AI innovation. Dr. Zhavoronkov is widely recognized for his academic influence and research productivity, being listed 3 times among the Clarivate Highly Cited Researchers, with an H‑index of 72 assessed by Google Scholar. The drug discovery and development team is led by Feng Ren, PhD, Co-CEO and Chief Scientific Officer of Insilico Medicine, an experienced drug hunter, who is responsible for guiding R&D exploration directions and overseeing the execution of pipeline asset development. Dr. Ren has devoted nearly 20 years to innovative drug R&D and has authored more than 80 publications in peer-reviewed journals, and holds approximately 120 patents in total. 

Committed to open-source academic research and knowledge sharing, Insilico maintains active communication with the industry with continuous publication about technological breakthroughs and industrial milestones. The company authors more than 300 peer‑reviewed papers and holds over 700 patents or applications. Supported by its outstanding contribution, Insilico was recognized in the Nature Index 2024 list of the world’s top 100 global corporate institutions for biological sciences and natural sciences publications. In 2025, one of Insilico’s studies was selected among the top 10 advances by Nature Biotechnology, and featured on the journal's December cover.

Following the IPO, Insilico plans to allocate approximately 48% of the net proceeds to fund further clinical research and development of our key clinical stage pipeline drug candidates, 20% to fund the research and development, for early-stage drug discovery and development, 15% for development of new generative AI models and the associated validation research work, 12% for the further development and expansion of our automated lab, and 5% for working capital and other general corporate purposes. While consolidating the strengths of its “AIDD dual‑engine” model, the company will continue to integrate global resources and seek collaboration opportunities to accelerate the fundamental paradigm shift across the biopharmaceutical industry.

 

About Insilico Medicine

Insilico Medicine is a pioneering global biotechnology company dedicated to integrating artificial intelligence and automation technologies to accelerate drug discovery, drive innovation in the life sciences, and extend healthy longevity to people on the planet. The company was listed on the Main Board of the Hong Kong Stock Exchange on December 30, 2025, under the stock code 03696.HK.

By integrating AI and automation technologies and deep in-house drug discovery capabilities, Insilico is delivering innovative drug solutions for unmet needs including fibrosis, oncology, immunology, pain, and obesity and metabolic disorders. Additionally, Insilico extends the reach of Pharma.AI across diverse industries, such as advanced materials, agriculture, nutritional products and veterinary medicine. For more information, please visit www.insilico.com

 

Climate policies can backfire by eroding “green” values, study finds

Santa Fe Institute

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Green values can be crowded out or cultivated depending on whether policies feel imposed or embraced, but well-designed policies can cultivate green values if they appear effective and non-intrusive. (image: Irene Pérez)

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Credit: Irene Pérez

A popular vision of life after climate action looks like vegetarians riding bikes, city centers without cars, and people foregoing air travel. But a paper published in Nature Sustainability finds that climate policies targeting lifestyle changes (say, urban car bans) actually may weaken people’s green values, thereby undermining support for other needed environmental policies.

“Policies don’t just spur a target behavior. We find that they can change people’s underlying values: leading to unintended negative effects, but also possibly cultivating green values,” says SFI Complexity Postdoctoral Fellow Katrin Schmelz, lead author on the study. 

Schmelz, a behavioral economist and psychologist who also holds an Associate Professorship at the Technical University of Denmark, began gathering data while at the University of Konstanz in Germany. Along with SFI Professor and economist Sam Bowles, she surveyed more than 3,000 Germans representative of the country’s demographics, asking about climate policies and, for comparison, COVID-19 policies.

The survey yielded evidence that well-intended, but poorly designed, mandates can make even “green” citizens less green. Restrictions that promote carbon-neutral behavior, like urban car bans, may trigger strong negative reactions — even among people who would voluntarily choose sustainable lifestyles.

This erosion of existing values is a clear example of what’s known in psychology and economics as the “crowding-out effect." A person’s aversion to control “crowds out” their pre-existing motivation to follow a green lifestyle — for example, riding their bike, walking, and taking public transportation, or being more mindful when heating or cooling their home. “These crowding-out effects are big enough that policymakers should worry,” says Bowles.

Another key finding, which surprised the authors, was a 52% greater negative response to climate mandates than to COVID-19 mandates. “We saw incredible hostility in the U.S. and other countries towards controls during the COVID-19 pandemic, hindering the implementation of much-needed public policies. It looks like the climate case could be much worse,” says Bowles. “The science and technology to provide a low-carbon way of life is nearly solved. What’s lagging behind is a social–behavioral science of effective and politically viable climate policies.”

The research Schmelz and Bowles have begun is already seeing applications. Last April, policy experts and researchers from various disciplines met at SFI to discuss preliminary findings from the study and brainstorm how to design policy that can encourage green values.

There is reason for optimism, the study shows. Mandate resistance was less for people who felt that policies were effective, didn’t restrict their freedom of choice, and were not intrusive on their privacy or their body. 

“We found three conditions that minimize opposition to mandates, and may even cultivate, rather than crowd out, green values,” says Schmelz. “People are more open to policies that they think are effective (in reducing CO2 emissions), and that they don’t perceive as privacy-intrusive. People also respond much more positively if they don’t feel that a policy restricts their freedom — so in Germany, there is less opposition to limitations on short-haul flights compared to other policies, and this may be because the European train network provides an adequate alternative (which may not be the case in the U.S., for example).”

Read the full paper "An empirically based dynamic approach to sustainable climate policy design" in Nature Sustainability (December 30) DOI: 10.1038/s41893-025-01715-5

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Journal

Nature Sustainability

DOI

10.1038/s41893-025-01715-5 

Article Title

An empirically based dynamic approach to sustainable climate policy design

Article Publication Date

30-Dec-2025

 

Too much hydrogen? Scientists reveal how metabolic shifts and viral defense in syngas microbiomes

Chinese Society for Environmental Sciences

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Workflow of syngas biomethanation under increasing hydrogen ratios. This schematic illustrates the experimental workflow used to evaluate how hydrogen enrichment affects syngas-converting microbiomes. Cultures were initially supplied with baseline syngas (69% H₂, 16% CO₂, 15% CO), followed by stepwise hydrogen increases to 77% and 84%. Samples collected across stages were analyzed using metagenomics, metatranscriptomics, and virome profiling to track changes in microbial composition, viral populations, and metabolic pathways. The approach enabled quantitative comparison of community abundance and activity, revealing metabolic reprogramming and defense activation under hydrogen-rich conditions.

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Credit: Environmental Science and Ecotechnology

Syngas biomethanation—converting CO/CO₂/H₂ into renewable methane—relies on coordinated microbial interactions. This study reveals that excess hydrogen disrupts this balance, reducing methanogenesis efficiency and triggering major shifts in microbial metabolism and viral dynamics. Under hydrogen-rich conditions, the key methanogen Methanothermobacter thermautotrophicus downregulates methane-producing pathways while activating defense systems such as CRISPR-Cas and restriction-modification mechanisms. Meanwhile, acetogenic bacteria intensify carbon fixation through the Wood–Ljungdahl pathway, acting as alternative electron sinks. The findings uncover a previously unclear mechanism of thermodynamic stress and microbiome-virus interplay, offering guidance for optimizing microbial consortia in syngas-to-methane conversion. 

Biomethanation provides an energy-efficient, low-carbon alternative to thermochemical gas conversion, turning biomass-derived syngas into biomethane for circular energy systems. The performance of this process depends on balanced microbial metabolism, where hydrogenotrophic methanogens reduce CO₂ using H₂, supported by acetogens and syntrophic partners. However, syngas composition fluctuates during industrial operation, and the metabolic response to hydrogen excess is poorly understood. Traditional studies observed performance drops at high H₂ supply, but lacked molecular-level mechanistic explanation regarding microbial regulation and viral interactions. Due to these uncertainties, deeper investigation into microbial and viral responses under hydrogen-rich conditions is needed.

Researchers from the University of Padua reported on a 2025 early-access study (DOI: 10.1016/j.ese.2025.100637) in Environmental Science and Ecotechnology demonstrating how hydrogen surplus alters microbiome metabolism and triggers viral defense responses in syngas-converting systems. Using genome-resolved metagenomics, metatranscriptomics and virome profiling, the team monitored microbiomes as syngas composition shifted from optimal ratios to hydrogen-rich conditions. Their findings uncover a stress-driven metabolic reorganization and highlight phage dynamics as a significant ecological dimension in biomethanation efficiency.

The study cultivated thermophilic anaerobic microbiomes under three syngas compositions and applied multi-omics analysis to track responses before and after hydrogen increase. Under near-optimal gas ratios, methane yield improved and the dominant methanogen Methanothermobacter thermautotrophicus maintained stable gene expression. However, when hydrogen supply exceeded stoichiometric demand, methane production declined and transcriptome analysis revealed strong metabolic repression. Key methanogenesis genes—including mcr, hdr, mvh, and enzymes in CO₂-to-CH₄ reduction—were significantly downregulated.

Simultaneously, M. thermautotrophicus activated antiviral defense systems, upregulating CRISPR-Cas, restriction-modification genes, and stress markers such as ftsZ. Virome mapping identified 190 viral species, including phages linked to major methanogens and acetogens. Some viruses showed reduced activity, suggesting defense-driven suppression, while others exhibited active replication patterns. In contrast, several acetogenic taxa—including Tepidanaerobacteraceae—enhanced expression of Wood–Ljungdahl pathway genes (cdh, acs, cooF, cooS) to boost CO/CO₂ fixation and act as electron sinks. This reprogramming indicates a shift from methanogenesis to carbon-fixation-dominant metabolism when hydrogen is excessive.

The authors emphasize that hydrogen excess creates a regulatory bottleneck, pushing methanogens into stress mode while enabling acetogens to take over carbon metabolism. They note that viral interactions—previously overlooked in biomethanation—play a major role in shaping community stability. The team points out that CRISPR-Cas activation and phage suppression indicate a defensive state, suggesting that virome dynamics must be considered in bioreactor design.

This research provides molecular-level evidence that hydrogen oversupply can destabilize methane production, highlighting the need for gas-ratio control in industrial reactors. Understanding how microbial populations reprogram under stress can guide engineering of more resilient biomethanation systems, enabling consistent biomethane yields even with variable feedstocks. The insights into phage-microbe interactions further suggest potential for virome-aware reactor management strategies, including microbial community design, phage monitoring, or antiviral interventions. These findings support future development of carbon-neutral gas-to-energy technologies and scalable waste-to-resource platforms.

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References

DOI

10.1016/j.ese.2025.100637

Original Source URL

https://doi.org/10.1016/j.ese.2025.100637

Funding information

This work was supported by the LIFE20 CCM/GR/001642 – LIFE CO2toCH4 of the European Union LIFE + program and the European Union’s Horizon 2020 research and innovation program under grant agreement No 101084405 (CRONUS).

About Environmental Science and Ecotechnology

Environmental Science and Ecotechnology (ISSN 2666-4984) is an international, peer-reviewed, and open-access journal published by Elsevier. The journal publishes significant views and research across the full spectrum of ecology and environmental sciences, such as climate change, sustainability, biodiversity conservation, environment & health, green catalysis/processing for pollution control, and AI-driven environmental engineering. The latest impact factor of ESE is 14.3, according to the Journal Citation ReportsTM 2024.

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Journal

Environmental Science and Ecotechnology

DOI

10.1016/j.ese.2025.100637 

Subject of Research

Not applicable

Article Title

Hydrogen excess drives metabolic reprogramming and viral dynamics in syngas-converting microbiomes