Researchers evaluated biological age using six internationally recognized proteomic aging clocks, finding a reduction in predicted biological age among patients treated with rentosertib. The drug also showed promising dose-dependent reversal of Forced Vital Capacity (FVC), a measure of lung function declining with age.
Insilico Medicine's inclusion in the HKEX Tech 100 Index underscores its advancements in AI-driven drug discovery and healthcare. The company has reported significant revenue growth and achieved its first profitable half-year, with its AI technology capabilities driving expansion and liquidity.
Insilico Medicine has released state-of-the-art (SOTA) MMAI specialist models for chemistry and biology, achieving superior performance on over 70 benchmark tasks. These models demonstrate the potential of language models to compete with dedicated scientific methods in drug discovery.
Insilico Medicine leaders will share AI-driven insights at key tech events, including LEAP 2026 and the UBS China A-Share Conference. The company will discuss how AI drug discovery is reshaping R&D paradigms, enhancing efficiency and innovation value.
Insilico Medicine convenes O3DC, an open initiative addressing critical limitations in benchmarks for AI-driven drug discovery. The consortium catalogues hundreds of benchmarks across 10 categories, including molecular property prediction and binding affinity.
Dr. Alex Aliper will share insights on how cutting-edge technological innovation can drive industrial growth at the Global Unicorn Summit, and discuss AI applications in precision medicine at MedTech World Asia. He will also present real-world case studies and explore industry challenges in applying AI to personalized healthcare.
ARDD 2026 will convene leaders from pharma, biotechnology, academia, clinical medicine, investment, AI and policy to present research and exchange perspectives on longevity biotechnology. The meeting will address therapeutic development and commercialization, with sessions on clinical trials, regulatory pathways, and AI in healthspan.
Insilico Medicine has been nominated for the 2026 Prix Galien USA 'Best Start-Up' Award for its generative AI-driven approach in biotechnology. The nomination follows significant advancements in its lead AI-discovered drug, rentosertib, and its expansion of collaborations with pharmaceutical companies.
Insilico Medicine's inclusion in the MSCI Global Small Cap Indexes reflects growing recognition of its core strengths in AI-powered drug discovery. The Company is expected to benefit from increased international visibility, passive capital inflows, and improved trading liquidity.
Insilico Medicine introduces the Virtual Aging Cell (VAC) platform, which leverages multi-agent AI to simulate cellular processes, including differentiation, reprogramming, and aging. The VAC platform aims to support target identification, cellular fate intervention, novel drug discovery, and geroscience research.
Insilico Medicine has nominated ISM0900, a potent and selective oral Lp(a) inhibitor, as a preclinical candidate for managing cardiovascular risks. The compound demonstrates rapid onset, excellent oral pharmacokinetics, and superior efficacy in reducing Lp(a) levels.
Researchers identified NDRG1 as a key regulator of DNA damage repair, which can be targeted by the antimalarial drug quinacrine to trigger synthetic lethality in specific cancer subtypes. The study also reveals potential strategies for targeting DNA damage response based on NDRG1 expression.
ISM9077 boasts potent inhibition across species, excellent exposure and permeability traits, and a favorable safety profile in preclinical studies. It modulates pathological inflammation, supporting broad indication expansion into therapeutic areas like aging and neurodegenerative diseases.
A collaborative study between Insilico Medicine and top research institutions uses AI to identify therapeutic targets for IP-SNSCC, a rare and aggressive subset of head and neck cancers. The study provides the first comprehensive molecular atlas of this disease, enabling future translational research.
ISM8969/HT-001 is an orally available, brain-penetrant NLRP3 inhibitor with promising in vitro and in vivo profiles. The clinical trial aims to evaluate its safety, tolerability, and efficacy in patients with Parkinson's disease.
Insilico Medicine's Dr. Alex Zhavoronkov will deliver two keynotes on AI-driven drug discovery and anti-aging at Ai4 2026. The panel discussion explores the evolution of AI in medicine, while the solo keynote delves into the company's strategy for breakthrough innovation using frontier AI models.
The DDD Benchmark provides an independent, real-world measure of how a model performs in drug discovery. It comprises two evaluation suites: Drug Discovery Foundations and Drug Candidate Essentials.
ISM6331, a novel pan-TEAD inhibitor, has received Fast Track Designation from the FDA for treating adult patients with unresectable malignant pleural mesothelioma. The treatment boasts synergistic anti-tumor effects and potential to overcome drug resistance as combination therapy.
Insilico Medicine presents first-in-human Phase 1 study data for its novel AI-designed pan-TEAD inhibitor ISM6331, targeting complex oncogenic drivers like the Hippo pathway. The study assesses safety, pharmacokinetics, and preliminary antitumor activity in patients with advanced mesothelioma and other solid tumors.
The US and China have distinct advantages in different domains, with the US lacking efficient translational infrastructure and China building a more efficient biomedical development engine. The conversation will address areas of collaboration and competition in biopharmaceutical innovation.
Insilico Medicine has nominated an AI-driven novel compound ISM9528 for pain management, addressing the $100 billion market challenge. The compound targets Target Z and offers a non-opioid treatment approach with superior efficacy and safety profile.
At CPIC 2026, Insilico Medicine's Dr. Alex Zhavoronkov and Dr. Feng Ren presented on their approach to AI-driven life sciences, leveraging the Pharma.AI platform for agile translation and closed-loop validation. The duo emphasized the importance of technological breakthroughs and clinical validation in shaping the future of R&D.
The strategic alliance combines Insilico's Pharma.AI platform with Bora's global capabilities to explore a next-generation drug innovation model. The partnership aims to accelerate Bora's transition towards AI-driven drug discovery and development, leveraging Insilico's comprehensive research and development strategies.
The collaboration aims to advance co-development of R&D programs by combining Insilico's validated AI platform with CMS's therapeutic expertise. The partnership enables the development of innovative drugs for central nervous system conditions, streamlining the process and accelerating delivery of clinically meaningful innovations.
The 13th Aging Research & Drug Discovery (ARDD) Meeting will take place from October 1-3, 2026, at the David Rubenstein Treehouse at Harvard University. The conference features a comprehensive program with daily tracks focused on clinical translation and industry growth.
Insilico Medicine will deliver a keynote speech and participate in a panel discussion on the future of drug discovery with generative AI. The company showcases its innovative approach to accelerating drug development, compressing timelines and enabling sustainable growth.
Insilico Medicine achieved a significant revenue increase of 272.7% to 287.3% for the First Half of 2026, with net profit expected in the range of USD33.5 million to USD39.5 million. Global collaborations and strategic partnerships drove business growth, with major deals secured with top pharmaceutical companies.
Rentosertib is a potentially first-in-class oral small-molecule inhibitor targeting TNIK for the treatment of idiopathic pulmonary fibrosis. The Phase III clinical trial will evaluate the efficacy and safety of once-daily Rentosertib administered over 52 weeks.
Insilico Medicine has expanded its generative AI capabilities through a strategic collaboration with Liquid AI, yielding models optimized for retrosynthesis and multi-omics target discovery. The company's platform upgrades enable enterprise-grade automation, parallel simulation, and precision sifting in biologics design.
Insilico Medicine is leveraging its end-to-end Pharma.AI platform to drive clinical validation in AI drug discovery, with a diversified pipeline featuring over 40 projects. The company has nominated 31 development candidates and achieved positive results in a Phase IIa clinical trial for Rentosertib, an AI-discovered TNIK inhibitor for...
The collaboration aims to identify clinically differentiated drug candidates using Insilico's generative AI and Takeda's global development capabilities. The partnership seeks to deliver meaningful treatment options for patients and support Takeda's transition to an AI-native discovery model.
Generative AI is transforming pharmaceutical RÝ into a highly efficient, end-to-end new era. Insilico Medicine has accumulated extensive experience in AI-driven drug discovery, sharing breakthroughs and latest advancements in molecular design, multi-target synergy, and clinical translation success rates.
Insilico Medicine announces a $2.5 billion global R&D collaboration with SK Biopharmaceuticals to discover AI-enabled drug candidates for neuroimmune disorders. The company's Pharma.AI platform will drive target-to-candidate discovery, while SK Biopharmaceuticals will handle late-stage clinical development and commercialization.
Insilico Medicine announced a record-breaking $2.5 billion global R&D collaboration with SK Biopharmaceuticals, focusing on neuroimmune disorders. The company showcased its proprietary Pharma.AI platform and demonstrated its expertise in accelerating drug discovery.
Insilico and SK Biopharmaceuticals collaborate on AI-powered drug discovery for neuroimmune disorders, aiming to accelerate discovery timelines and advance next-generation therapies. The partnership could be worth up to $2.5 billion, with Insilico receiving upfront and milestone payments.
Insilico Medicine will showcase its core capabilities and latest R&D pipeline at the BIO 2026 International Convention. The company's CEO, Dr. Alex Zhavoronkov, will present four featured speeches on AI-driven drug discovery and quantum technology-enabled research.
Insilico Medicine has completed the first-in-human dosing of its AI-driven NLRP3 inhibitor ISM8969 in a Phase I clinical study. The trial aims to evaluate the safety, tolerability, and efficacy of ISM8969 in healthy participants and those at risk of cardiovascular disease.
Insilico Medicine has completed the first-in-human dosing of its AI-driven NLRP3 inhibitor ISM8969 in a phase I clinical study. The trial achieved its first clinical milestone with partner Hygtia Therapeutics, evaluating the safety and efficacy of the treatment for chronic neuroinflammation.
Insilico Medicine is revolutionizing preclinical drug development through its AI and automation platform, reaching PCC nomination in just 12-18 months. The company has nominated 31 PCCs since 2021, with 13 receiving IND approval or clearance.
Alex Zhavoronkov, founder of Insilico Medicine, has been named to the inaugural SCW75 list for his work in AI-driven drug discovery and longevity research. The company's Pharma.AI platform has drastically compressed traditional drug discovery timelines, advancing 30 developmental candidates to clinical trials.
Jue Wang joins Insilico Medicine as Global Head of Business Development to drive high-value alliances and empower commercial growth. She brings expertise in small-molecule novel drug discovery and has led landmark collaborations worth USD 4 billion.
Insilico Medicine will present its end-to-end Pharma.AI platform and latest pipeline, highlighting the synergy between AI-driven drug design, quantum algorithms, and automation labs. The company has built an extensive therapeutic portfolio across various areas and rapidly advancing its internal R&D pipeline.
The collaboration aims to jointly develop a super-intelligence AI foundation model to predict disease risk, diagnose conditions, and discover novel therapeutics. By integrating advanced algorithms with deep biological insights, the models are expected to drive breakthroughs in early detection and personalized interventions for age-rela...
Insilico Medicine's Pharma.AI platform combines with Ribo's expertise in oligonucleotide therapeutics, aiming to boost efficiency and certainty of clinical research. The partnership enables end-to-end empowerment of RNA interference and oligonucleotide therapeutics development.
LabClaw integrates PandaOmics, automated laboratory hardware matrix, LIMS, and multi-dimensional data analysis pipelines to create an end-to-end intelligent closed loop. The system features five types of agents and a Human-in-the-Loop confirmation mechanism for maximizing efficiency without compromising scientific safety standards.
The INS001-055 inhalation solution is the world's first AI-driven candidate to receive IND clearance. It targets Idiopathic Pulmonary Fibrosis (IPF) with a novel molecule structure and demonstrates good tolerability, PK profiles, and dose-dependent efficacy trend.
Insilico Medicine nominates UAE's first developmental preclinical candidate using generative AI, marking a significant step forward for pharmaceutical innovation. The milestone showcases the country's growing biotechnological capabilities and its rise as a global hub.
The review highlights key considerations for selecting an optimal drug target, including therapeutic hypothesis, druggability and safety, commercial tractability, and combination value. AI's capacity to process complex multimodal data enables researchers to navigate biological complexity and uncover disease-associated targets.
The Insilico Medicine Longevity Board aims to accelerate the development of therapeutics targeting the biological processes of aging. The board, led by Andrew Adams, will oversee AI-enabled aging research and drug discovery.
Insilico's unified AI framework combines disease-specific predictive modeling with rigorous benchmarking to improve target identification accuracy and reliability. The validated system generates actionable intelligence, prioritizing targets with strong potential for successful development.