Leukemia & Lymphoma Society to adopt Saama LSAC in Beat AML trial

19th February 2019 (Last Updated February 19th, 2019 12:20)

US-based non-profit Leukemia & Lymphoma Society (LLS) has partnered with data analytics company Saama Technologies to implement Life Science Analytics Cloud (LSAC) in its Beat AML Master Clinical Trial.

Saama’s LSAC is designed to optimise clinical development processes. It provides a range of clinical data analytics solutions integrated with structured and unstructured data sources.

The technology features data ingestion, integration and analysis capabilities. In the Beat trial, LSAC is expected to boost operational and clinical conduct.

Saama Technologies Ecosystem Innovations senior vice-president Murali Krishnam said: “Combining Saama’s LSAC solution with the amazing work currently in progress at Beat AML trial sites across the US will enhance and expedite data collection and analysis, generating insights that will inform critical decisions to accelerate the discovery of promising new AML therapies.”

The Beat AML Master Trial is being conducted to assess precision medicine approach in patients suffering from acute myeloid leukaemia (AML), a type of blood cancer.

Comprehensive genomic profiling (CGP) is used to screen trial participants for AML genetic changes mutations, and the patients are assigned to a therapy based on their genetic profile.

The trial involves newly diagnosed patients aged 60 years and older.

Leukemia & Lymphoma Society Clinical Operations head Len Rosenberg said: “We look forward to the insights Saama and LSAC will add to our novel Beat AML umbrella trial, which is changing the paradigm for AML treatment and which has already yielded invaluable information in the two years since it got underway.”

Saama Technologies has also announced the addition of new Virtual Assistant/AI, Operational and Financial Risk Mitigation, and Drug Efficacy and Patient Safety Analytics programmes to LSAC.

Virtual Assistant is intended to improve conversational user engagement and supports LSAC’s context and a domain-aware conversational user interface called Deep Learning Intelligent Assistant (DaLIA).

The Operational and Financial Risk Mitigation programme enables tracking of clinical trial key performance indicators (KPIs) as well as management and reducing of operational and financial risks.

Meanwhile, the new Drug Efficacy and Patient Safety Analytics feature is said to optimise the time and effort needed to correlate patient profiles with data variables.