Insilico Medicine has secured a $110 million Series E financing to accelerate the advancement of its AI-driven drug discovery pipeline and platform developments. The funds will focus on refining AI models and algorithms, as well as advancing clinical validation of its flagship candidate for idiopathic pulmonary fibrosis treatment.
Rentosertib, a breakthrough drug candidate for idiopathic pulmonary fibrosis (IPF), has been granted an official generic name by the USAN Council. The drug's development was accelerated using generative AI, identifying TNIK as a promising target and designing small-molecule compounds in just 18 months.
Insilico Medicine has deployed the first bipedal humanoid AI scientist, Supervisor, to aid in data acquisition and generation for training embodied AI systems. The humanoid will assist with lab tours, telepresence, tracking, and supervision, bridging the gap between human-free fully-autonomous robotics facilities.
The collaboration combines Insilico's Pharma.AI platform with Tenacia's expertise in CNS biology and clinical development. By leveraging generative AI, the partnership seeks to expand therapeutic options and enhance outcomes for patients worldwide. Recent successes by Insilico include the nomination of ISM8969, a BBB penetrable NLRP3 i...
Insilico Medicine has discovered a potent and selective CDK12/13 dual inhibitor, compound 12b, using AI-powered platforms. The compound shows significant efficacy in breast cancer and AML models without inducing side effects, paving the way for further therapeutic development.
InSilico Medicine achieved a preclinical milestone in its collaboration with Therasid Bioscience, optimizing AI-driven compounds targeting MASH. The team synthesized and tested approximately 40 molecules in just 4 months, identifying candidate compounds with highly satisfactory properties.
A groundbreaking study using AI-driven robotics laboratory identifies Rentosertib, a potent TNIK inhibitor, as a highly effective senomorphic agent capable of reducing aging-related markers. The study reveals TNIK inhibition alleviates key signaling pathways implicated in senescence and fibrosis.
The collaboration aims to accelerate antibody discovery and development using Harbour BioMed's technology platform and Insilico's AI expertise. The companies will develop next-generation AI-powered antibodies for immunology, oncology, and neuroscience, aiming to deliver innovative therapies with enhanced specificity, efficacy, and safety.
Insilico Medicine has nominated 22 developmental candidates, with 10 progressing to human clinical stage, demonstrating efficient drug discovery using generative AI. The company's platform reduces developmental times, cost, and resource allocation, setting a new standard for the industry.
Insilico Medicine has developed a highly selective FGFR2/3 dual inhibitor, which maintains efficacy against resistance mutations and demonstrates a more favorable safety profile compared to existing FGFR inhibitors. The compound showed robust antitumor efficacy in gastric cancer mouse models.
Insilico Medicine has successfully dosed the first patient in its global Phase I clinical trial of ISM6331, a potent pan-TEAD inhibitor. The treatment demonstrates superior efficacy and safety in preclinical studies, with potential synergistic anti-tumor effects and overcoming drug resistance.
Insilico Medicine's AI-driven platform, PandaOmics, identifies two new therapeutic targets and a repurposed FDA-approved drug for treating endometriosis. The study reveals guanylate-binding protein 2 (GBP2) and hematopoietic cell kinase (HCK) as key proteins involved in the disease mechanism.
The Menarini Group and Insilico Medicine have entered into an exclusive licensing agreement for a preclinical small molecule targeting solid tumor cancers. The asset has demonstrated broad anti-tumor activity in selected cancers, offering new treatment options for cancer patients with high unmet needs.
Positive Phase 1 trial results suggest ISM5411's gut-restrictive property and favorable pharmacokinetic profile, validating its potential for treating inflammatory bowel disease. Insilico Medicine expects to initiate a Phase 2 proof-of-concept study in active ulcerative colitis patients.
ISM1745, a potentially best-in-class small molecule inhibitor, has been nominated as a preclinical candidate for the treatment of MTAP-deleted cancers. It targets Protein arginine methyltransferase 5 (PRMT5), which is elevated in various cancers and correlates with poor prognostic outcomes.
The study uses generative AI to identify and optimize potent and selective HPK1 inhibitors for immunotherapy. The results show a relatively balanced candidate compound with adequate in vitro ADME, in vivo PK properties, good oral bioavailability, and robust in vivo efficacy in various cancer models.
Insilico Medicine has received its first clinical milestone payment of $10 million from Exelixis for XL309, a selective USP1 inhibitor discovered with the company's AI platform. The drug is being developed for advanced solid tumors and has shown efficacy in preclinical studies.
Scientists at Insilico Medicine developed a novel gut-restricted PHD inhibitor using generative chemistry engine Chemistry42, promising to repair intestinal mucosal barriers and regulate immune responses in IBD. The compound, ISM5411, demonstrated significant anti-colitis activity without systemic side effects.
Insilico Medicine has nominated ISM8969, an orally available NLRP3 inhibitor, as a potential treatment for various inflammatory diseases. The compound has shown promising results in preclinical evaluation studies, including balanced druggability and efficacy against inflammation.
Insilico Medicine has successfully integrated cutting-edge generative AI models into its platform, achieving significant increases in accuracy and speed. The company's AI-powered solutions have shown promising results in preclinical candidates and Phase II clinical trials.
Insilico Medicine has developed an innovative platform using generative AI to discover novel molecules. The company has nominated over 20 preclinical candidates and received IND clearance for 10 molecules.
Alex Zhavoronkov, Insilico Medicine's founder and CEO, was named Highly Cited Researchers of 2024. He has published over 40 peer-reviewed research papers, with a total H-index of 64, and led the development of Insilico's lead drug pipeline, ISM001-055.
Insilico Medicine has been selected by Fortune as one of the top AI innovators, leveraging its generative AI platform to develop novel drugs and treatments. The company's lead drug pipeline, ISM001-055, has shown promising results in Phase IIa trials, offering new hope for patients with idiopathic pulmonary fibrosis.
Insilico Medicine has received FDA clearance for ISM5939, a potential best-in-class oral small molecule inhibitor targeting ENPP1 for the treatment of solid tumors. ISM5939 demonstrated robust anti-tumor efficacy in preclinical studies and showed favorable safety profiles.
Pharma.AI Week will showcase the latest advancements in Insilico's generative AI platform, including PandaOmics and Science42, with expert speakers and hands-on demos. The event aims to empower researchers and scientists with tools for faster and more accurate discoveries.
The Phase IIa trial of ISM001-055 showed dose-dependent improvement in forced vital capacity (FVC) and percent predicted FVC, suggesting potential to slow or reverse disease progression. The treatment also demonstrated a favorable pharmacokinetics profile with minimal adverse events.
Insilico Medicine CEO Alex Zhavoronkov to discuss AI business potential and economic growth at Fortune Global Forum 2024. The company has developed a generative AI-powered platform that utilizes deep learning techniques for novel target discovery and molecular structure generation.
Insilico Medicine has entered into a revolving loan facility of up to US$100 million with HSBC, enabling the company's global expansion and AI-driven innovation in biotechnology. The credit line will support Insilico's proprietary novel drug discovery pipeline and its end-to-end diversified AI platform, Pharma.AI.
The collaboration utilized Insilico's generative biology AI platform, Pharma.AI, to identify a novel lead for treating oncology diseases. The joint R&D team addressed the druggability challenge of highly novel targets using novel scaffolds generated by Chemistry42.
A new study reveals TNIK's role in various diseases, including fibrosis, cancer, obesity, and Alzheimer's. The protein has been found to drive cancer cell proliferation and treatment resistance, while also regulating metabolic processes.
Nach0 was trained on diverse tasks, including natural language understanding, synthetic route prediction, and molecular generation. The model performed well on molecular tasks using molecular data and outperformed ChatGPT, making it a significant step toward unlocking the full potential of LLMs for drug discovery.
Insilico Medicine's lead compound demonstrates strong enzymatic activity, selectivity, and favorable ADME properties, as well as antitumor activity in various animal models. The company's generative AI-powered platform generated over 3,600 candidate molecules before identifying the promising lead compound.
Researchers at Insilico Medicine developed COSMIC, a new framework for molecular conformation space modeling that provides accurate insights into molecule positioning and activity. This enables faster and more efficient drug design decisions.
Researchers at Insilico Medicine have identified a new class of Polθ inhibitors featuring central scaffolding rings, designed using Chemistry42, with significant enzymatic and cellular potency. The discovery showcases the potential of AI in medicinal chemistry for precise molecular modifications.
Researchers at Insilico Medicine have developed a novel PTPN2/N1 inhibitor with improved oral absorption and robust antitumor efficacy using the company's generative AI engine. The new compound demonstrates enhanced biological activities compared to existing inhibitors, offering new treatment possibilities for cancer patients.
Researchers at Insilico Medicine developed QFASG, a quantum-assisted algorithm generating novel small-molecule structures from fragments. The tool successfully designed inhibitors for cancer-related proteins, showcasing its potential in accelerating drug discovery and development.
Researchers used generative AI to design a lead molecule for treating fibrosis, a biological process associated with aging. The compound, INS018_055, demonstrated significant efficacy in preclinical studies and showed promising results in clinical trials, accelerating drug discovery and providing new therapeutic options.
PandaOmics uses advanced AI algorithms to process vast quantities of diverse data, performing gene and pathway analysis and target predictions. The platform has been extensively validated in multiple therapeutic areas, including oncology, inflammation, and immunology.
Researchers developed a framework for standardizing biomarker development and validation to improve the prediction of age-related health outcomes. The study highlights the need for expanded focus on functional decline, frailty, chronic disease, and disability, and calls for harmonization of omic data to enhance reliability.
Insilico Medicine has discovered a novel PHD inhibitor for treating anemia using its AI-powered generative chemistry platform Chemistry42. The compound demonstrated favorable ADMET and PK profiles in animal models, showing promise for further investigations.
Researchers at Insilico Medicine have identified MYT1 as a promising therapeutic target for breast and gynecological cancers. A series of novel, potent, and highly selective inhibitors specifically targeting MYT1 were discovered using AI-driven generative biology and chemistry engine.
Researchers identified a promising dual-purpose target, KDM1A, using AI analysis of transcriptomic data from 16,740 healthy samples and 11,303 tumors. KDM1A was found to significantly extend lifespan in Caenorhabditis elegans and has anti-cancer activities established in preclinical and clinical studies.
Insilico Medicine has identified 9 potential dual-purpose targets against aging and 14 major age-related diseases using Microsoft BioGPT. The proposed genes include CCR5 and PTH, which have not been previously correlated to the aging process.
Researchers identified potential therapeutic targets for Alzheimer's disease and other conditions using a new approach combining AI-driven target identification with protein phase separation analysis. The study provides insights into the role of protein phase separation in human disease and its potential as a therapeutic target.
Insilico Medicine's inClinico platform uses generative AI to predict Phase II to Phase III clinical trial success with an accuracy of 79%. The tool has been validated in various studies and can provide valuable insights for investors and biotech/pharma companies.
Researchers at Insilico Medicine discovered novel inhibitors for salt-inducible kinase 2 (SIK2), a potential target for anti-inflammation and anti-cancer therapy. The findings were published in the July 13 edition of Bioorganic & Medicinal Chemistry, demonstrating the power of Insilico's Pharma.AI platform.
The study evaluates recent research on artificial intelligence-generated molecular structures from the perspective of medicinal chemists, recommending guidelines for assessing novelty and validity. Insilico Medicine's recommendations aim to improve the process of generating and evaluating novel AI-generated drugs.
Scientists used Insilico Medicine's generative AI platform to identify actionable drug targets for cystinosis and validate them in preclinical models. The study found that hyperactive mTOR signaling drives kidney tubular cell dysfunction, making it a targetable pathway.
Three high school students co-authored a paper using AI engine PandaOmics to discover new therapeutic targets for glioblastoma multiforme, a common and aggressive malignant brain tumor. The study identified three genes strongly correlated with both aging and glioblastoma as potential therapeutic targets.
Researchers utilized the Chemistry42 platform to generate novel molecular structures and identified a hit molecule for CDK20, a promising target for hepatocellular carcinoma. The platform's customizable reward function and generative models enabled efficient design and optimization of molecules.