The NR3C1 (nuclear receptor subfamily 3 group C member 1) gene encodes the glucocorticoid receptor (GR), a nuclear receptor vital for maintaining physiological homeostasis, and inhibition of NR3C1 could increase the sensitivity of cancer cells to standard chemotherapy, particularly in ovarian cancer. Notably, the FDA has approved a clinical proof‑of‑concept study of the NR3C1 inhibitor relacorilant plus nab‑paclitaxel in cancer. Beyond oncology, NR3C1 inhibitors shows also therapeutic promise in nervous, cardiovascular, immune and metabolism systems, boasting a wide indication area.
Till date, the evolution of NR3C1 inhibitors has successfully addressed the selectivity and off-target toxicity issues that plagued the first generation, yet the field continues to struggle with the benefit-risk balance in non-cancer indications. There is an urgent need for next-generation inhibitors to overcome the persistent limitations of current benchmarks, particularly the high risk of drug-drug interactions.
Insilico Medicine (03696.HK), a clinical-stage, generative AI-driven drug discovery company, today announced the nomination of ISM6200 as a potent, potentially best-in-class preclinical candidate (PCC) targeting NR3C1, for the treatment of ovarian cancer, Hypercortisolism (Cushing’s Syndrome), and other disorders related to excess cortisol including obesity. The process was empowered by Chemistry42, the generative chemistry engine affiliated to Insilico’s Pharma.AI, as well as the specialized applications across the molecule discovery and optimization cycle.
“In platinum-resistant ovarian cancer, patients face an overall survival of only about one year, so the field is calling for new therapies,” said Dr. Feng Ren, Co-CEO and Chief Scientific Officer of Insilico Medicine. “ISM6200 was specifically engineered with outstanding properties, including lower DDI risks, which allow broader combination options. More importantly, the molecule can deliver strong efficacy at a much lower projected human dose, offering a safer and more effective treatment path for patients in need.”
As shown in preclinical studies, ISM6200 is a small molecule candidate with low DDI risk and higher in vivo efficacy across multiple animal models. In a preclinical CDX (cell line-derived xenograft) model, ISM6200 demonstrated significant and dose-dependent enhancement of anti-tumor efficacy when combined with paclitaxel. Also, a favorable ADME and pharmacokinetic profile support strong systemic exposure and a low predicted efficacious dose in humans, and its solid developability profile marked by good stability lays the foundation as a therapeutically effective agent.
“We originally identified NR3C1 utilizing dual target research related to aging – it scored in multiple age-related diseases. We started working on a portfolio of small molecule drugs targeting NR3C1 to help unlock the full potential of this target while avoiding the known on-target liabilities. The nomination of ISM6200 highlights the transformative power of generative AI in addressing complex medicinal chemistry challenges while reducing traditional risks such as metabolic instability and off-target toxicity,” said Alex Zhavoronkov, PhD, Founder and Co-CEO of Insilico Medicine. “I am especially encouraged by multi-purpose candidates like this one, as it is indicated in systems across the body, even exceeding our expectation of targeting both aging and certain diseases. By using AI, we can identify high-quality molecules with broad potential, in record time, and we are advancing more pipelines with AI-driven efficiency.”
Notably, the nomination of ISM6200 marks another step forward in Insilico’s cardiometabolic portfolio, which was first introduced at BIO-Europe 2025, with the NR3C1 program as a key asset holding potential to reverse cortisol-driven metabolic dysfunction and enhance semaglutide-mediated weight loss.
In the DIO mouse model, ISM6200 demonstrated a good weight loss effect, mainly reducing fat while better retaining muscle mass. After 28 days of administration, compared with the control group, ISM6200 monotherapy achieved significant weight loss, with a relative weight reduction of 8.8% from the baseline. When ISM6200 was combined with Semaglutide, the weight loss effect was further enhanced, reaching 23.8% within the same administration period, while the DIO control group gained 2.4% in weight. The above data provided strong support for subsequent clinical development.
In a rat model of Cushing's syndrome, ISM6200 significantly alleviated insulin resistance and decreased blood pressure. Following 6-day treatment, insulin resistance levels were reduced by 68%, and blood pressure approached the levels observed in healthy control groups. Additionally, in the therapeutic glaucoma model, after 3 days of dexamethasone injection followed by 3 days of ISM6200 treatment, measurements revealed a significant decrease in intraocular pressure (IOP) in mice, providing clues for subsequent clinical development.
ISM6200 is the 29th Preclinical/Developmental Candidate (PCC/DC) Nomination by Insilico. Since 2021, 12 PCCs obtained IND clearance, 3 entered Phase II, among which 1 Phase IIa trial is completed, with 10+ business development deals marking superior quality of Insilico PCC and high standards.
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