Technology

Innovative AI Technologies

COLOXIS AI system. A first-of-the-class AI clinical decision system for predicting oxaliplatin benefits in GI cancers.
Revealing genomic causes of each individual tumor using tumor-specific causal inference (TCI) (Patent pending)

Discovering tumor-specific intercellular communication network using single-cell sequencing, spatial sequencing, and instance-specific Bayesian causal network learning.

Understanding individual tumor's disease mechanisms, such as oncogenic processes and immune evasion mechanisms.

Interpretable deep learning technology for inferring the state of cellular signaling systems and immune systems in a tumor

Reliable decision support systems to match cancer cells with effective drugs

Publications

Chen, L, Wang, Y, Cai, C, Ding, Y, Kim, RS., Lipchik, C, Gavin, PG., Yothers, G, Allegra, CJ, Petrelli, NJ, Suga, JM., Hopkins, JO., Saito, NG., Evans, T., Jujjavarapu, S., Wolmark, N., Lucas, PC., Paik, S., Sun, M., Pogue-Geile, KL., Lu, X. (2023) Machine Learning Predicts Oxaliplatin Benefit in Early Colon Cancer. Journal of Clinical Oncology Epub:JCO2301080. doi: 10.1200/JCO.23.01080
Ren, S., Tao, Y., Xue., Y., Yu., K., Schwartz, R., and Lu, X. (2022) De novo prediction of cell-drug sensitivities using deep learning-based graph-regularized matrix factorization. Proceedings of Pacific Symposium of Biocomputing 27:278-289
Chen, X., Chen, L., Kürten, C. H., Jabbari, F., Vujanovic, L., Ding, Y., ... & Lu, X. (2022). An individualized causal framework for learning intercellular communication networks that define microenvironments of individual tumors. PLOS Computational Biology, 18(12), e1010761.
Tao, Y., Cai, C., Cohen, W., and Lu, X (2020) From genome to phenome: Predicting multiple cancer phenotypes based on somatic genomic alterations via the genomic impact transformer. Proceedings of Pacific Symposium on Biocomputing.
Tao, Y., Ren, S., Ding, MQ., Schwartz, R., Lu, X (2020) Predicting drug sensitivity of cancer cell lines via collaborative filtering with contextual attention. Proceedings of the Machine Learning for Healthcare Conference 2020. 126:660-684.
Ding, MQ., Chen, L., Cooper, GF., Young, JD., and Lu, X. (2017) Precision oncology beyond targeted therapy: Combining omics data with machine learning matches the majority of cancer cells to effective therapeutics. Molecular Cancer Research 16(2):269-278