XtalPi announced that they are embarking on a strategic collaboration with CK Life Sciences, a member of the CK Hutchison Group. XtalPi and CK Life Sciences will leverage their respective expertise to jointly develop a novel AI tumour vaccine R&D platform to improve the discovery and design capabilities of tumour vaccines and accelerate the development of more vaccine types. The goal of this collaboration is to realize precision treatment for patients worldwide.

According to public information, there were nearly 20 million newly diagnosed cancer patients worldwide in 2021, of which about 4.5 million cases came from China. Many cancer types lead to detrimental outcomes, with high morbidity and mortality, and there remains a large unmet clinical need. Tumour vaccines targeting different tumour neoantigens, tumour-associated antigens (TAA) and tumour-specific antigens (TSA) in patients can be designed for use as immunotherapy, to activate the patient's own specific immune responses.

Currently, there are only two therapeutic tumour vaccines— sipuleucel-T for melanoma and Bacillus Calmette-Guérin (BCG) for bladder cancer, as well as preventive tumour vaccines against human papillomavirus infection and hepatitis B infection approved by the U.S. Food and Drug Administration (FDA). Recently, several other tumour vaccines have entered clinical development and evidence of efficacy has begun to emerge. Currently, the design and preclinical development process for tumour vaccines is complex and lengthy, hindering the efficiency and success rate of tumour vaccine research and development.

Incorporating XtalPi's industry expertise in AI computation and robotic automation, this collaboration aims to build an AI tumour vaccine R&D platform that applies advanced AI algorithms and high-precision molecular modeling to predict and design a variety of tumour vaccines that can activate specific immune responses to kill tumours. The tumour vaccines will be screened and verified through automated experiments, and through integrating algorithmic feedback to optimise activity and efficacy, the platform is expected to generate preclinical tumour vaccine candidate compounds with robust immune activity.