QureGenAI Shows Its 15-Qubit Quantum AI Drug-Design Center in Xi'an to 15 Shaanxi Drug Makers on 28 October 2026: What the Company Claims and What Has Been Published
How QureGenAI presented quantum AI drug design to 15 Shaanxi drug makers in Xi'an
Quentir Medicine Monitor
Evidence-based insights for quantum medicine.
On the afternoon of 28 October 2026, representatives of fifteen pharmaceutical companies from Shaanxi province toured a quantum computing center in Xi'an that is built for drug research. The host, QureGenAI (医图生科 in Chinese), used the visit to present its case for quantum AI drug design to companies that make peptides, traditional Chinese medicines and generic drugs.
The Xi'an Advanced Manufacturing Association organized the visit, and the Chang'an Xiandao Life Sciences Industry Innovation Center co-hosted it. According to the event report published on ifeng.com on 5 November 2026, the companies attending included the Shaanxi Pharmaceutical Research Institute, Huikang Biotech, Jinhua Pharmaceutical and Lijun Pharmaceutical. Officials from the Xi'an industry and information technology bureau also attended.
The center itself is a joint project of the Chang'an Xiandao innovation center and Xi'an Xiandao Yitu Quantum Technology, a company linked to QureGenAI. The report describes it as housing the first 15-qubit superconducting quantum computer in northwest China, coupled to classical computers in a hybrid cluster for biomedical work. The company also calls its offering the world's first end-to-end quantum computing solution aimed at industrial drug design and discovery. That claim comes from the company and the report repeats it without any comparison to other platforms.
Li Xiaoran, chief executive of QureGenAI and chief scientist of the center, listed four areas where the company applies its methods: design of new drugs, protein structure prediction, optimization of fermentation processes, and activity screening of natural products. He cited two examples from cancer research, a prodrug design for pancreatic cancer and drug development against the KRAS target, a protein that is mutated in many pancreatic, colorectal and lung tumors.
Li argued that quantum computing has an advantage that classical methods cannot match in two specific steps of chemistry: calculations on strongly correlated electronic systems, and searches for the transition states of chemical reactions. Both steps are hard for standard computational chemistry, so the choice of target is sensible. The report gives no data for either example, however. It names no molecule, no accuracy figure and no comparison with a classical calculation on the same problem.
The same applies to the largest number in the report. Li said the team had applied combined quantum and AI methods to traditional medicine design, enzyme engineering and aqueous two-phase extraction, and that peptide batch production had reached an efficiency of several dozen times that of traditional processes. No study, patent or customer is cited for that figure, so a reader cannot yet check how it was measured or how much of it came from the quantum part of the workflow.