Insilico Medicine has expanded its MMAI Gym platform, launching three benchmark leaderboard portals to evaluate AI systems in scientific research and drug discovery. The platforms assess broader scientific reasoning and end-to-end drug discovery tasks, enabling scalable evaluation of AI models.
The event showcases the Pharma.AI ecosystem's new capabilities, including the MMAI Gym for Science, updates to PandaOmics, Generative Biologics, and Chemistry42. Researchers can learn how to access these tools and best practices for tackling challenging problems in human health.
Researchers at Insilico Medicine have developed novel small molecular inhibitors and extremely selective PROTACs targeting the serine/threonine kinase PKMYT1. The discovery utilizes noncovalent interactions to achieve selectivity, masking hydrogen-bond donors that negatively affect permeability and solubility.
ISM6200 is a potent, potentially best-in-class preclinical candidate targeting NR3C1 for the treatment of ovarian cancer, Hypercortisolism (Cushing’s Syndrome), and other disorders related to excess cortisol. The molecule demonstrates low DDI risks and higher in vivo efficacy across multiple animal models.
Researchers developed a compact AI model that reasons through chemistry logic, outperforming larger models on critical tasks. The Liquid Foundation Model achieves state-of-the-art success rates in molecular optimization and ADMET superiority.
Insilico Medicine will present four novel cancer inhibitors discovered via its Pharma.AI platform, targeting KRAS and Cbl-b pathways. ISM6166 and ISM3830 demonstrate robust anti-tumor activity against solid tumors with KRAS alterations and restored innate and adaptive immunity, respectively.
Insilico Medicine and Eli Lilly partner to accelerate discovery of novel therapeutics using AI engine, focusing on preclinical development for certain indications. The collaboration aims to deliver transformative therapies for diseases with high unmet need.
The companies are leveraging generative AI to develop innovative candidates for challenging neurological diseases, aiming to provide a broader range of therapeutic options. Insilico's Pharma.AI platform and Tenacia's expertise will continue to generate innovative solutions with strong translational potential.
Insilico Medicine recognized for demonstrating real-world clinical impact from its generative AI platform and achieving significant commercial milestones. The company's momentum is underscored by its successful public listing on the Hong Kong Stock Exchange.
The collaboration aims to identify therapeutic targets for challenging gynecological conditions using Insilico's AI-driven target identification engine, PandaOmics. ASKA will validate the AI-predicted targets with high translational potential, accelerating the development of innovative solutions for millions of patients worldwide.
PandaClaw automates complex real-time analyses, enabling researchers to discover novel targets and identify new indications through an intuitive natural language interface. The tool accelerates translational medical research by lowering the barrier for biologists to apply AI.
Insilico Medicine's inclusion in the Hang Seng Index and Stock Connect program is expected to enhance stock liquidity and market attention, strengthening the company's capital market influence. The company has achieved multiple drug development milestones, including 12 IND-enabling programs and preclinical candidates ISM0676 and ISM5059.
Insilico Medicine's Alex Zhavoronkov chairs precision aging discussion and presents Luminary Award to OpenAI president Greg Brockman. The company's AI-driven approaches accelerate drug discovery and advance precision medicine for aging and age-related diseases.
ISM4808, a PHD inhibitor for chronic kidney disease-related anemia, has achieved its first milestone with successful completion of the Phase I clinical trial. The treatment stimulates endogenous erythropoietin production and improves iron utilization, offering improved efficiency and safety compared to existing treatments.
The partnership produced a single checkpoint model, LFM2-2.6B-MMAI, that achieves state-of-the-art performance across multiple drug discovery subdomains and covers the complete discovery loop, including property prediction, molecular optimization, affinity prediction, chemical reasoning, and retrosynthesis planning.
Insilico's new platform automates business development workflows, increasing efficiency and quality of communication. The system integrates proprietary data with AI-powered interactions to streamline partner engagement and due diligence.
Researchers from Insilico Medicine and Lilly outline a comprehensive framework for fully autonomous, AI-orchestrated drug discovery. The vision integrates AI-driven target discovery, generative chemistry, automated synthesis, biological validation, and clinical planning into a single workflow.
The collaboration aims to uncover actionable targets and biological pathways that may lead to personalized therapeutic options and improved outcomes for patients. Insilico's PandaOmics platform integrates clinical datasets with AI models to systematically prioritize druggable targets.
The Harvard Business School case study explores the development of Insilico's lead asset, Rentosertib, which completed a Phase IIa clinical evaluation for idiopathic pulmonary fibrosis. Insilico Medicine has significantly improved preclinical drug development efficiency with its AI-driven approach.
Insilico Medicine and CMS announce multiple collaborations on AI-empowered drug discovery in central nervous system and autoimmune diseases. The partnerships aim to accelerate research, development, and translation of high-potential innovative therapies, leveraging complementary strengths across the entire value chain.
Halle Zhang joins Insilico Medicine to lead global clinical development strategy for the company's oncology portfolio. She brings over 20 years of experience in oncology clinical development and a track record of advancing therapies through registrational trials.
Insilico Medicine will present its latest AI-driven breakthroughs at WHX 2026, highlighting its role in accelerating translational research. The company's Abu Dhabi R&D center has established close collaborations with regional universities, driving innovation and generating global impact.
Insilico Medicine nominates ISM5059, a peripheral-restricted NLRP3 inhibitor, as a preclinical candidate for treating various inflammatory diseases. The compound has demonstrated high potency, selectivity, and excellent in vivo efficacy across animal disease models.
Insilico Medicine received a USD 5 million milestone payment from Menarini Group after completing first-in-human dosing in a Phase 1 study of MEN2501, a small molecule inhibitor targeting cancers with chromosome instability. This achievement follows the completion of a successful Phase 1 clinical trial.
ISM0676 demonstrates excellent metabolic stability, superior efficacy at low doses, and a favorable safety profile, leading to significant body weight reduction and improved body composition. The compound's synergistic efficacy with Semaglutide supports its further clinical development as an obesity treatment.
The collaboration aims to accelerate the development of small molecule inhibitors for treating metabolic diseases. Insilico will utilize its Pharma.AI platform to design and optimize novel molecules, while Qilu will handle subsequent development and commercialization.
Insilico Medicine has received investigational new drug (IND) clearance from the US FDA for ISM8969, an orally available NLRP3 inhibitor targeting inflammation and neurodegenerative disorders. The Phase I clinical trial plans to evaluate the safety, tolerability, and pharmacokinetics of ISM8969 in healthy volunteers.
Science MMAI Gym trains LLMs in medicinal chemistry, biology, and clinical development with precision required in pharma R&D. Partner models emerge with up to 10x improvements in performance, matching state-of-the-art specialist models.
Insilico Medicine presents three abstracts at the 2026 Crohn's & Colitis Congress highlighting clinical, preclinical safety, and efficacy data for ISM5411. The first-in-human Phase 1 results show no serious adverse events or deaths reported, with a favorable pharmacokinetic profile supporting gut restriction.
The article highlights Insilico Medicine's exclusive contributions to two chapters in the latest AI for Drug Discovery Volume, showcasing its expertise in real-life application of AI in early drug target-related tasks. The company's roadmap to 2030 using Quantum Machine Learning (QML) algorithms is also presented, with successful case ...
The companies will jointly develop ISM8969, a brain penetrant NLRP3 inhibitor for treating neuroinflammation-related diseases. Preclinical data shows the molecule's efficacy and favorable safety profile.
Insilico Medicine's multimodal foundation model, Nach01, accelerates drug discovery by integrating molecule generation, property prediction, and downstream analysis within a secure Azure environment. This integration enables unified, AI-native workflows for computational drug discovery.
Researchers use AI-driven target discovery platform to identify PRPF19 and MAPK9 as promising targets that suppress tumor cell proliferation while reducing senescence-associated signaling. The study suggests these dual-purpose targets may address both hepatocellular carcinoma progression and cellular senescence.
Insilico Medicine's Phase IIa clinical trial assesses Garutadustat's safety and efficacy in ulcerative colitis. The novel PHD inhibitor has shown favorable safety and tolerability profiles in completed Phase I studies.
Leadership from Insilico Medicine will discuss its groundbreaking collaboration with Capgemini, showcasing Pharmaceutical Superintelligence in action. The company's diversified pipeline includes 40+ programs discovered using Pharma.AI, with positive topline results from a Phase IIa trial for idiopathic pulmonary fibrosis.
DORA Community Edition aims to democratize access to state-of-the-art research tools, foster global collaboration, and accelerate innovation in biotechnology. The open-source version is designed to streamline the drafting of academic papers and other research-related documents with a team of agile AI agents.
Insilico Medicine collaborates with Servier to develop novel therapeutics in oncology through AI-driven platform Pharma.AI. The partnership is focused on identifying promising targets and generating molecular structures with desired properties.
Insilico Medicine and Hisun Pharma successfully nominated a preclinical candidate using AI-powered R&D in just 8 months after forming a strategic collaboration. The collaboration showcased the acceleration and efficiency gains that AI can bring to drug development, enabling the companies to enhance innovation in early-stage drug discov...
Insilico Medicine raised a total of HKD 2.277 billion in its largest Hong Kong biotech IPO, with 94,690,500 shares offered globally and oversubscribed by approximately 1427 times. The company aims to advance its mission of extending human productive longevity using AI-powered drug discovery and development.
Insilico Medicine showcases its Pharma.AI platform's capabilities in generating biologics and analyzing data to accelerate drug discovery. The company's latest updates include improved Generative Biologics, Chemistry42/Nach01, and PandaOmics features.
Insilico Medicine and Taigen Biotechnology collaborate to develop and commercialize ISM4808, an AI-driven PHD inhibitor for treating anemia of Chronic Kidney Disease (CKD). The partnership grants TaiGen exclusive rights for further development, commercialization, and sub-licensing in the Greater China area.
Insilico Medicine's AI platforms enable discovery of a novel, potent, selective, and orally administered DGKα inhibitor that restores T cell function and overcomes checkpoint resistance. The compound exhibits strong combination activity with anti–PD-1 and anti–CTLA-4 therapies in preclinical studies.
Insilico Medicine's Chemistry42 platform enables the efficient discovery of a potent, oral CBLB inhibitor with low toxicity risks and favorable ADME/PK profiles. The compound demonstrates strong in vitro activity and improved metabolic stability in mouse, rat, and dog models.
The latest Pharma.AI updates focus on generating precision in binder design and analyzing patent information. Insilico's AI-powered platform now boosts biological intelligence by up to 10 times, accelerating drug discovery processes.
Researchers used Insilico's AI-powered PandaOmics platform to identify (Z)-endoxifen as a promising therapeutic candidate for glioblastoma, with strong reversal of biological programs driving tumor growth and treatment resistance. Laboratory validation confirmed the compound's cytotoxic activity and showed enhanced effects in combination.
Researchers at Insilico Medicine developed an AI-empowered dual-action PROTAC targeting PKMYT1, which induces degradation and inhibits kinase activity. The lead compound, D16-M1P2, exhibits high selectivity, potent anti-tumor activity, and favorable oral bioavailability.
Insilico Medicine will demonstrate how generative AI is accelerating therapeutic discovery, improving drug efficacy, and advancing personalized medicine. The company's pharma superintelligence platform aims to tackle challenging problems in modern science and medicine.
Insilico Medicine has nominated ISM3830, a highly selective CBLB inhibitor, as a preclinical candidate for advanced tumor immunotherapy. ISM3830 showed robust anti-tumor activity in multiple murine models and induction of long-term tumor immunity.
Dr. Zhavoronkov's exceptional research influence has been validated by Clarivate, with over 310 peer-reviewed papers since 2012. His work has garnered over 16,500 citations per Google Scholar, primarily on generative adversarial networks and reinforcement learning for drug discovery.
Insilico Medicine is set to showcase its latest AI-driven Pulmonary Fibrosis clinical research at the PFF Summit 2025 in Chicago, IL. The company's Rentosertib (INS018_055/ISM001-055), a novel AI-designed TNIK inhibitor, has demonstrated promising therapeutic outcomes and potential markers of patient response.