According to the Zhitong Finance App, Lai Kai Pharmaceutical-B (02105) announced that the Group has initiated the recruitment of subjects for the LAE118 Phase I clinical study (“Phase I Clinical Study”) for the treatment of advanced solid tumors in China, and has completed the enrollment of the first case of subjects.
In June 2026, the Group entered into an exclusive license agreement (“License Agreement”) with Vasque Bio, Inc. (“Vasque Bio”). According to the terms and conditions of the license agreement, the Group is entitled to a total of up to $527 million in non-refundable and non-deductible down payments and milestone payments, as well as a single-digit to double-digit percentage of LAE118's future net sales within the license area. The Group also has the right to obtain up to a double digit percentage of Vasque Bio's issued common shares, or to replace cash payments for such common shares without additional consideration. If Vasque Bio enters into an eligible strategic cooperation or acquisition transaction that meets specific conditions (relating to the use of LAE118), the Group will be entitled to additional payments up to 50% of the value of the strategic transaction.
Vasque Bio mainly focuses on the development of drugs to treat rare diseases, while the group focuses on developing LAE118 oncology therapies outside of licensed regions. The Group can use this opportunity to accelerate the global development and commercialization of LAE118 for a wider range of indications within licensing regions, and accelerate its downstream value creation (such as exit from licensing, partnerships, or mergers and acquisitions).
The company will continue to focus on specific treatment areas where the company has accumulated deep expertise and rich practical experience. To further improve the efficiency of the company's discovery research and shorten pre-clinical development time, the company is accelerating the application of artificial intelligence (AI) in the company's discovery platform — from target identification and lead compound optimization to predictive toxicology and clinical candidate drug screening.