The Elucidatas MLOps platform boosts drug discovery data quality

The Elucidatas MLOps platform boosts drug discovery data quality ...

Nearly every life sciences business is using AI to drive research and develop novel medications and therapies, from junior startups to large corporations. The effort revolves around developing predictive models on massive datasets pertaining to the issue at hand. However, for many organizations, gathering high-quality data remains a major challenge.

Multi-omics, bioassays, clinical, EHR, and other kinds of biomedical data are required by most scientists. This kind of data is often stored in many different systems within their organizations or sourced externally. It is so vast that it becomes difficult to build an accurate predictive model.

“Deciphering biomedical data insights is at the core of addressing the world's most significant breakthroughs in biopharmaceuticals,” says Ashish Venkataramani, a partner at Eight Roads Ventures. “These multifaceted, heterogeneous datasets are being created as a result of advances in sequencing technologies and connected devices.”

Elucidata solves the challenge of data quality.

Polly, a Massachusetts-based MLOps platform, allows life sciences businesses to make the most of this opportunity without worrying about the heterogeneous or siloed nature of data. The solution allows R&D teams to access clean, curated biomolecular data that can be viewed and analyzed using a graphical user interface (GUI) or programmatically.

Polly, a software company, gathers, transforms, and harmonizes data into machine-readable formats, enabling companies to leverage it for machine learning tasks. The solution has access to more than 70TB of biomedical data, including more than 1.5 million datasets and 4.1 million samples, from more than 30 public and proprietary sources.

The platform draws data from sources such as TCGA and Gene Expression Omnibus (GEO). Next, it converts the information into flat files and adds ontology-backed metadata and labels to enhance it into machine learning-ready biomedical data.

"Organizations often underestimate the importance of data quality, and as a result, a lot of AI/ML initiatives are harmed," according to Abhishek Jha, the CEO and co-founder of Elucidata.

Adoption is a popular topic in the United States.

Polly has already been adopted by more than 30 life science industry players, including Genentech, Pfizer, and Janssen, as well as research institutions like Stanford and the Bill and Melinda Gates Foundation, according to the company.

Elucidata will focus on expanding its product capabilities in translational drug research and related markets, scaling go-to-market initiatives, and speeding up its global expansion.

Nihal Sinha, MD and partner at F-Prime Capital, which participated in the round, said in a statement.

„Elucidata is enabling life science companies to obtain high-quality data sets, thus accelerating their R&D efforts toward developing novel solutions that improve human health,” Singha said.

According to RBC Capital Markets, the compound annual growth rate of data for healthcare will reach 36% by 2025 — 6% faster than manufacturing, 10% faster than financial services, and 11% faster than media and entertainment.

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