MolecularHealth is working with SAP to help it speed up a software solution it is developing to help oncologists make better treatment decisions for their patients.
The partners are working on integrating MolecularHealth's oncology treatment decision support solution, targeted for launch next year, with the SAP Hana platform — an in-memory database technology system for analyzing large volumes of data.
Specifically, MolecularHealth will use "retrospective and predictive modeling components" within Hana to shorten the analysis time, John Papandrea, SAP's healthcare business unit lead, told BioInform.
In addition, "we will learn from [SAP's] experience and improve if necessary the platform for genomic computation," he said.
MolecularHealth said the software will help clinicians quickly process large quantities of sequence data and perform complex analytics.
The molecular oncology solution is MolecularHealth's second product. Earlier this year, the company launched Molecular Analysis of Side Effects, or MASE, a software-as-a-service offering for use in drug safety assessment and prediction. At the time, it hinted at plans to develop a product specifically for the oncology market (BI 1/20/2012).
Jeffrey Marrazzo, MolecularHealth's chief business officer, told BioInform that some applications that will be part of the treatment decision-support solution are currently being used in oncology projects at MD Anderson Cancer Center and elsewhere.
With SAP, "we saw an opportunity to use a new type of database technology" that could speed up ”our interpretation engine” by enabling "real-time look ups and faster information pulls from our proprietary knowledgebase," he said. This will eventually enable the system to provide answers "in a near real-time fashion rather than the more slow cohort-based analysis that you get from a relational database," he said.
Furthermore, SAP's technology can help customers deal with some of the more compute-intensive parts of processing whole-genome data such as sequence alignment and variant calling, Marrazzo said.
He said the company conducted an internal proof-of-concept test with its MASE software in which SAP's platform made the software "about 5000 times" faster.
The companies have signed an original equipment manufacturing agreement — the details of which aren't being disclosed — that allows MolecularHealth to sell the Hana technology as part of its molecular oncology application.
SAP has further life science partnerships planned for its Hana platform and will focus on other diseases besides cancer.
The company has an existing arrangement with Qiagen to develop a bioinformatics pipeline for next-generation sequence data that will include tools to align genomic sequences and identify mutations based on reference data (BI 7/6/2012).
SAP has also worked with German medical school Charité Berlin to develop a tool called Hana Oncolyzer, a mobile healthcare application based on the Hana platform that uses information such as tumor type, gender, age, risk factors, therapy, and diagnoses to select patient cohorts for oncology clinical trials.
However, the partnership with MolecularHealth is SAP's first dealing with the clinical genomics market and the company is eyeing additional opportunities in the omics space in general, Papandrea said, although he could not divulge specific details.
Toward More Effective Treatments
MolecularHealth's solution will let oncologists use a combination of clinical information, molecular data from tumor and normal cells, and drug data to select the most effective treatments for their patients.
It will provide a set of treatment options that are specific to each patient along with supporting evidence from research studies what will let users create patient-specific therapeutic system models that include perturbation and past therapy information.
It will also provide oncologists with details about off-target safety or resistance effects through MolecularHealth's MASE software.
MolecularHealth expects its software to be used in cancer centers as well as by drug and diagnostic developers and payers seeking to apply clinico-molecular insights to treatment decision-making.