Sequences tumor DNA to identify actionable mutations and biomarkers for targeted cancer therapies.
Aggregates data from electronic health records, labs, and imaging to provide a holistic patient view.
Uses machine learning algorithms to analyze large datasets and uncover insights for cancer care.
Recommends targeted therapies and clinical trials based on genomic and clinical data.
Enables data sharing and collaboration for clinical trials and academic research.
Collects and analyzes data from patient outcomes to inform future research and treatment guidelines.
Matching patients with targeted therapies based on genomic data to improve treatment efficacy.
Identifying eligible patients for specific clinical trials using genomic and clinical criteria.
Analyzing large datasets to discover new biomarkers and therapeutic targets for cancer.
Tracking patient response over time by integrating sequential genomic and clinical data.
Aiding in the diagnosis of rare or complex cancers through comprehensive genomic profiling.
Assisting oncologists in making informed decisions by providing data-driven insights and reports.
Helping patients understand their cancer and treatment options through accessible reports and resources.
Providing genomic and clinical data to pharmaceutical companies for developing new cancer drugs.
Studying cancer trends and outcomes at a population level to inform public health strategies.
Enabling universities and research institutions to access and analyze genomic data for studies.
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