Regend Therapeutics To Present Hainan Real-World Study Data At The 2026 ERS International Congress
By Ron Chen, Bureau Chief, Asia
On August 26, 2026, Regend Therapeutics announced that it will present, in the form of an oral report, global data from its Hainan real-world study on autologous airway basal stem cell transplantation for lung injury repair, along with the launch of the WuKong AI Efficacy Prediction System, at the 2026 European Respiratory Society (ERS) International Congress on September 8, 2026.
The 36th European Respiratory Society (ERS) International Congress 2026 will be held grandly from September 5 to 9 in Barcelona, Spain. As the largest and most influential academic event in the global respiratory medicine field, this year’s ERS Congress adopts the official theme “United for better breathing: partnership between patients, clinicians and researchers.” Tens of thousands of experts and scholars from over 100 countries will gather to share the latest clinical trial breakthroughs, guideline updates, and achievements indigital health and AI applications, covering hot topics such as COPD, asthma, sleep-disordered breathing, interstitial lung diseases, and respiratory infections.
I. World-first real-world study data on airway basal stem cells to be unveiled
Presentation details:
Date: September 8, 2026
Time: 9:40
Session: 3I
Title: Real-world study of autologous airway basal stem cell transplantation for COPD therapy
This study, conducted by Regend Therapeutics in collaboration with the Ruijin Hospital Hainan (Hainan Boao Research Hospital), Shanghai Jiao Tong University School of Medicine, is a real-world clinical research initiative supported by the biomedical technology access policies of the Hainan Boao Pilot Zone. It covers multiple indications including chronic obstructive pulmonary disease (COPD), bronchiectasis (BE), and interstitial lung disease (ILD). These diseases are all characterized by irreversible lung structural damage, for which conventional treatments offer little fundamental repair—representing a significant unmet clinical need.
The REGEND001 product is a first-in-class airway basal stem cell therapy independently developed by Regend Therapeutics. Its core technology utilizes the company’s proprietary R-Clone patent to harvest adult stem cells from healthy airway sites of the patient, expand them extensively in vitro over approximately one month, and then deliver them back to the patient’s damaged lung areas via bronchoscopy. This therapy is safe and easy to administer, can be performed in an outpatient bronchoscopy suite, and requires only a single dose to achieve long-term benefits. This innovative approach not only reduces healthcare resource utilization but also fully considers patient accessibility and affordability in the commercialization of cell therapy products. As of July 2026, this real-world study has completed infusions in nearly 200 patients. The relevant study data will be presented by Professor Zuo Wei at this ERS Congress to a global audience of respiratory clinicians, investors, and multinational pharmaceutical companies.
II. WuKong AI Efficacy Prediction System to be launched, empowering precision decision-making and outcome optimization in stem cell therapy
Presentation details:
Date: September 7, 2026
Time: 8:00
Session: PS-10
Title: A multimodal AI-based model to predict the efficacy of airway basal stem cell therapy for respiratory diseases
This system is a multimodal efficacy prediction model designed for autologous airway basal stem cell therapy. It aims to integrate patient-specific status and autologous cell product characteristics to enable individualized prediction of therapeutic outcomes. The system comprehensively incorporates baseline clinical and pulmonary function information, lung CT features, as well as morphological and transcriptomic profiles of the autologous cell product—capturing key factors that may influence treatment response from both the “patient side” and the “cell side.”
The WuKong AI Efficacy Prediction System, by integrating clinical, imaging, and cell-product multidimensional information, offers a novel research approach for exploring patient stratification and individualized efficacy prediction in cell therapy. Currently, the model still requires prospective validation in larger and more diverse patient populations to further assess its clinical utility.
