Resistance to chemotherapy and molecularly targeted therapies presents significant challenges in cancer treatment. The mechanisms of resistance to classical chemotherapies and to early-line precision therapies share many features.
Common mechanisms of resistance include alterations in drug targets, pro-survival pathway activation, and ineffective cell death induction. However, the increasing arsenal of anticancer agents, improved preclinical models of resistant cancers, Artificial Intelligence and Machine Learning technologies provide unprecedented opportunities to overcome treatment resistance. At SPARC, we leverage these enabling approaches while using predictive biomarkers to better stratify patients in clinical studies. Our modality-agnostic approach to oncology includes small- and large-molecules and targeted therapies. Our lead oncology programs include vodobatinib (SCO-088), a BCR-ABL targeting tyrosine kinase inhibitor for refractory chronic myelogenous leukaemia, and a first-in-class anti-MUC-1 antibody-drug conjugate (ADC) with potential to treat multiple cancers.