Breaking the Safety Barrier: Insilico Medicine Nominates ISM1354, the Next-Generation Small Molecule GIPR Antagonist

CAMBRIDGE, Mass., Sept. 30, 2026 /PRNewswire/ -- As population aging accelerates with demand for weight management continuing to expand, the market for GLP-1 receptor agonist (GLP-1RA) drugs is experiencing explosive growth. Tirzepatide, with annual sales of $36.507 billion in 2025, has become the latest Top Drug, underscoring the industry's momentum and commercial potential. To further advance long-acting and precise weight management, the industry has proposed a combination strategy using GIPR (glucose-dependent insulinotropic polypeptide receptor) antagonists alongside GLP-1 therapies. This approach is expected to reduce fat while preserving muscle mass, demonstrating significant synergistic weight-loss potential. This strategy carries heightened clinical relevance given the rising risk of sarcopenia among aging populations. However, several GIPR candidates have recently stumbled in clinical trials due to toxicity and tolerability issues. This highlights the R&D challenges while pointing the way for further optimization.

Insilico Medicine ("Insilico", HKEX: 3696), a clinical-stage drug discovery company powered by generative artificial intelligence (AI), today announced the nomination of ISM1354, an AI-driven novel small molecule preclinical candidate (PCC) targeting GIPR, for the potential intervention of obesity, as well as obesity-related disorders including type 2 diabetes, with the potential to expand into cardiovascular diseases in regulating obesity-associated heart failure and more. Notably, in January of this year, Insilico announced the nomination of another GIPR antagonist, ISM0676, which demonstrated up to a 31.3% weight loss when used in combination with Semaglutide in humanized mouse models. In comparison, the newly nominated PCC maintains robust weight-loss efficacy while delivering further improvements in pharmacokinetic and safety profiles, while retaining its favorable drug-like properties.

"Generative AI is demonstrating immense potential in cracking complex drug discovery challenges," said Feng Ren, PhD, Co-CEO and CSO of Insilico Medicine. "Given the structural complexity and intricate functional mechanisms of GIPR, the identification of viable small-molecule GIPR antagonists and the optimization of their drug-like properties remain major challenges in drug development. However, by leveraging the highly efficient molecular generation and optimization capabilities of our Pharma.AI platform, we successfully overcame these bottlenecks in a very short time and nominated the next-generation GIPR antagonist, ISM1354. This breakthrough, balancing both speed and quality, is truly encouraging. With the empowerment of generative AI, we look forward to exploring viable models for R&D breakthroughs in the cardiometabolic field, providing patients with safer and longer-lasting intervention options."

Leveraging Chemistry42, the proprietary generative chemistry platform, the Insilico R&D team integrated multiple prediction modules into the molecular generation and optimization workflow, balancing potency, selectivity and safety. Built upon in-house protein-ligand complex structures and key interaction information, Chemistry42 performed multi-objective molecular optimization by reinforcing critical on-target interactions and penalizing off-target interactions. Meanwhile, the DILI (Drug Induced Liver Injury) prediction model was deployed for upfront filtering of candidate molecules with improved safety profiles. FEP (Free Energy Perturbation) was subsequently applied for affinity prediction and ranking. After multiple rounds of DMTA (Design-Make-Test-Analyze) iterations with experimental data feedback, ISM1354 was selected as the preclinical candidate.

Preclinical evaluation showed that ISM1354 possesses outstanding and highly consistent pharmacokinetic characteristics across multiple species, including mice, rats, dogs, and monkeys, achieving oral bioavailability of 75-104%. At the same dose level, ISM1354 delivered at least 18-fold greater plasma exposure than a clinical-stage benchmark compound, demonstrating a marked advantage in systemic exposure and supporting its strong development potential.

Beyond its favorable PK properties, ISM1354 also displayed differentiated safety attributes. In vitro studies revealed substantially weaker inhibition of OATP1B1 compared to the clinical-stage benchmark compound, suggesting a more favorable transporter-related safety profile and an improved overall developability profile. ISM1354 demonstrated a markedly wider hepatocyte safety margin, showing minimal effects on cell viability at concentrations up to 200 μM, whereas a clinical-stage benchmark compound exhibited cytotoxicity with IC₅₀ values of ~25 μM in human hepatocytes and ~20 μM in monkey hepatocytes, indicating a lower potential hepatotoxicity risk for ISM1354.

In a non-GLP monkey toxicology assessment, ISM1354 was generally well tolerated and exhibited a favorable safety profile, with no significant toxicity findings observed. The current exposure-based analysis indicated an estimated ~45-fold margin of safety (MOS), providing strong support for advancing into GLP toxicology studies.

"Obesity is not an isolated health issue; it is a trigger for many diseases, and lipid metabolism disorder itself is a core hallmark of biological aging. I believe that GLP-1 therapies are poised to become the first 'longevity drugs' that can be popularized on a large scale, which is a massive opportunity that cannot be measured by money alone. " said Alex Zhavoronkov, PhD, Founder and Co-CEO of Insilico Medicine. "However, we absolutely cannot trade the decline in body weight at the expense of physical vitality and muscle mass, and this has been a long-standing pain point in the industry. At Insilico Medicine, we are leveraging the breakthrough power of generative AI to conquer this challenge, committing to discovering innovative mechanisms that can break through the existing efficacy ceiling, and providing next-generation disruptive solutions for true healthy aging."

To date, Insilico announced the nomination of 10 preclinical candidate compounds (PCCs) in the first 9 months of 2026, breaking the company's historical record for annual pipeline output pushing the total number of PCCs nominated since 2021 to 34, validating the R&D efficiency of generative AI through reproducible, real-world examples. According to the 2026 interim report, as of the middle of August, Insilico has achieved 8 clinical milestones across its internal and partnered pipelines. Leading these R&D advances is Rentosertib (ISM001-055), the world's first potential first-in-class drug candidate enabled by generative AI. Rentosertib has officially entered Phase III clinical trials for the treatment of idiopathic pulmonary fibrosis (IPF), taking a crucial step toward clinical validation and commercialization.

Since launching the MMAI Gym model training and evaluation ecosystem in 2026, Insilico Medicine has established AI co-development collaborations with Liquid AI (focused on liquid foundation models), Human Longevity (focused on precision health and longevity research), and others. Leveraging the MMAI Gym evaluation ecosystem, Insilico established and published benchmark leaderboard portals evaluating general-purpose model capabilities across specialized domains such as scientific reasoning, longevity research, and drug discovery, making evaluation results publicly accessible online. Notably, the Longevity benchmark focusing on the biology of aging was recently featured on the cover of a Cell special issue.

Additionally, in July, Insilico released the industry's first "Drug Discovery Benchmark Evaluation" dataset, aiming to systematically assess the comprehensive performance of foundation models in the field of drug discovery. Recently, the company further announced the launch of a series of cutting-edge chemistry and biology expert models trained and driven by MMAI Gym for Science. These models have demonstrated State-of-the-Art (SOTA) performance across over 50 benchmark tasks. Backed by this novel capability, Insilico is poised to drive scaled innovation, explore new modalities, and expand into diversified indications, further accelerating the discovery and development of "longevity drugs".

Driven by broad global recognition of its AI platform and pipeline assets, Insilico recently announced total revenue of approximately $106 million for the first half of 2026, representing a year-over-year increase of 287%, alongside an adjusted net profit exceeding $51 million—marking its first profitable half-year since listing. This financial milestone was primarily propelled by a series of out-licensing, co-development, and R&D collaborations with leading global partners, including Eli Lilly, Servier, Takeda, SK Biopharmaceuticals, Qilu Pharmaceutical, Hygtia Therapeutics, China Medical System (CMS), and Tenacia Biotechnology. According to the 2026 interim report, as of the middle of August, Insilico's disclosed deal value for signed collaborations in 2026 alone has reached approximately $7.3 billion, bringing the company's cumulative total signed deal value since 2021 to nearly $11 billion.

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

SOURCE Insilico Medicine