The 2024 European Society for Medical Oncology (ESMO) Congress will be held in Barcelona, Spain, from September 13th to 17th. As one of the largest and authoritative clinical oncology conferences globally, many significant research findings will be released during the meeting.

As a leading precision medicine company in China, OrigiMed has been deeply rooted in academic research since its establishment, participating in international exchanges and cooperation actively, showcasing its research achievements on the global stage continuously, and presenting innovative and comprehensive precision diagnosis and treatment solutions for tumors to peers in the industry.

At this conference, OrigiMed, in collaboration with clinical experts, will showcase a number of exciting research findings, covering various types of cancer such as lung, kidney, and colorectal, and encompassing new technologies like artificial intelligence and minimal residual disease (MRD). These advancements not only provide new strategies for cancer treatment but also lay a solid foundation for achieving the goals of precision medicine. We have selected some of the research results for you to preview.

① AI-Based Smart Oncology Follow-Up System: Prospective Application Testing and Enhancement of Clinical Efficacy

Research Highlight: SmartMTB, developed by OrigiMed, is an AI-based precision medicine assistant focused on the field of oncology. It integrates multiple international cancer treatment guidelines and a vast amount of precision oncology case data. By analyzing patient data, it provides personalized care and clinical trial options. SmartMTB excels in improving the efficiency of report interpretation, predicting patient recurrence and progression, and assisting in matching patients with suitable clinical trials. This model significantly enhances the work efficiency of doctors and demonstrates great potential in improving follow-up efficiency, optimizing treatment plans, and even correcting misdiagnoses.

② Predicting the efficacy of immunotherapy in non-small cell lung cancer using machine learning based on simple clinical characteristics and biochemical indexes

Research Highlight: This study developed a machine learning-assisted clinical decision-making tool for predicting the therapeutic response of non-small cell lung cancer patients to first-line immune checkpoint inhibitors (ICIs). The study included a total of 445 patients and comprehensively analyzed 55 clinical and pathological characteristics, including systemic factors, lifestyle, metastasis, routine blood tests, blood biochemistry, PD-L1 expression, and treatment plans. Univariate logistic regression analysis identified liver and bone metastasis, histology, PD-L1, and platelet distribution width as being correlated with the efficacy of ICIs (p < 0.05). The study tested five models, including decision trees, logistic regression, random forests, support vector machines, and XGBoost. The random forest model demonstrated superior predictive performance compared to other models in both the training set (AUC 0.87) and the test set (AUC 0.7).

③ The clinical value of tumor-informed minimal residual disease detection in renal cell carcinoma

Research Highlight: This study, through OrigiMed's whole-exome sequencing (WES) and minimal residual disease (MRD) testing, found that tumor-informed MRD detection methods are superior to fixed-panel MRD detection in patients with clear cell renal cell carcinoma (ccRCC). The study also found that the negative and positive predictive values of MRD detection are 100% and 42.9% respectively, emphasizing the importance of continuous MRD monitoring for long-term prognosis assessment. Despite limited follow-up time, MRD has shown great potential in predicting recurrence and metastasis.

④ Circulating Tumor DNA Guided Therapeutic Strategies for Colorectal Cancer Patients with Multiple Small Pulmonary-limited Nodules

Research Highlight: The study explored the clinical value of tumor-informed MRD testing in identifying pulmonary metastases in patients with metastatic colorectal cancer (CRC), aiming to indicate high-risk patients for escalated treatment. The findings suggest that MRD testing can detect intra-pulmonary and extra-pulmonary metastases earlier than imaging, and adjusting treatment strategies based on MRD results can lead to clinical benefits.

The 2024 ESMO Congress will open soon, and we sincerely look forward to sharing the latest achievements of OrigiMed in the fields of artificial intelligence, data science, and precision diagnosis and treatment with experts from around the world. We believe that with the joint efforts of scientists worldwide, as technology and science continue to mature, the various challenges in cancer treatment will eventually be overcome one by one!