Lifespin GmbH Secures EUR2.5M Bridge Financing to Further Build its AI-Enabled Metabolomics-Based Differential Diagnosis Panel for Neurological Diseases

REGENSBURG, Germany–(BUSINESS WIRE)–Lifespin GmbH, a deep data company currently developing a proprietary AI-based health testing platform to measure quantitative metabolic data in patient samples, has secured EUR2.5M bridge financing to fuel the company’s continued product development.

The Lifespin platform is based on mapping metabolomics for human health and translating that data into health information that can be deployed in a wide range of pharmaceutical, research, and clinical settings. Lifespin’s health diagnostics software will be applicable in the broader healthcare space ranging from diagnostics to patient stratification and personalized medicine, as well as supporting the drug discovery process.

“We are very excited about Lifespin’s growth trajectory with a platform solution which can be accessed by collaborating clinical laboratories and drug discovery partners and scale globally via our cloud solutions,” said Lifespin’s CEO, Dr. Ali Tinazli.

The bridge financing will be used to continue the development of the first diagnostics panel for neurological diseases such as multiple sclerosis and Parkinson’s disease, some of which cannot be addressed with legacy laboratory-based methods. The first commercial test of the differential diagnostics panel will be covering early stages of multiple sclerosis. The panel will be further expanded with other neurological indications over time.

“Lifespin’s new software-based approach to digitally capture, compare and analyze human metabolomes will open up a new and exciting field, complementary to existing health diagnostics,” said Robert Wieland, Managing Director of Wieland Capital and Lifespin’s lead investor.

Lifespin expects to begin fundraising for a Series A in 2022 to fund its first product introductions and to support expanding its business operations to the United States.

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Lifespin (www.lifespin.ai) is a deep data company that maps human health based on metabolomics. Lifespin’s advisory board consists of key opinion leaders such as James Rothman (Nobel Laureate in Physiology/Medicine, Sterling Professor of Cell Biology, Yale University, New Haven, CT USA) and numerous industry veterans. We have standardized the baseline for human health and can detect distinct deviations caused by diseases. A pathogenesis impacts metabolism, causing specific changes in the presence and quantity of metabolites. Our proprietary technology platform quantitatively captures individual metabolomes, i.e., up to hundreds of metabolite concentrations with a single Nuclear Magnet Resonance (NMR) measurement. Lifespin is building a proprietary in-house biobank with currently 200,000 human blood samples and performing quantitative in-house measurements of metabolomes for systematic mapping across health conditions. Our constantly growing proprietary database of digitized metabolic profiles enables the analysis of billions of metabolic relationships. Digital metabolic profiles enable differential diagnosis for the early detection of health conditions, staging of diseases, monitoring of treatment success and personalized medicine. Our first regulatory approved Software-as-IVD will be for the early differential diagnosis of multiple sclerosis and is expected in 2022. This will be followed by other tests for the detection of neurological, cancer, and inflammatory diseases. Our cloud-based business model is built on our proprietary Software-as-a-Service (SaaS) platform for diagnostics and health information and is globally scalable.

REGENSBURG, Germany–(BUSINESS WIRE)– #ai–Lifespin GmbH, a deep data company currently developing a proprietary AI-based health testing platform to measure quantitative metabolic data in patient samples, has secured EUR2.5M bridge financing to fuel the company’s continued product development. The Lifespin platform is based on mapping metabolomics for human health and translating that data into health information that can be deployed in a wide range of pharmaceutical, research, and clinical settings.