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From Months to Minutes: Insights on How to Accelerate R&D with Microbiome Network Science in Beauty and Personal Care
Interview with Dr Sven Sewitz, Director of Biodata Innovation
Eagle Genomics
Can you very briefly explain your company’s core business?
Eagle Genomics is a Deep Tech software business pioneering the digitization of R&D across the Personal Care and Beauty, Consumer Goods, Food and Nutrition, AgBio and Healthcare sectors. Our award-winning AI-augmented knowledge discovery platform, the e[datascientist]™, integrates and streamlines access to datasets and allows scientists to efficiently exploit multi-dimensional data and gain insights, in a matter of minutes rather than months. This is useful for companies wanting to accelerate product development as well as the exploration of novel pathways and ingredients, ultimately reducing time to market.
Our platform can explore connections in complex data that would otherwise not be detectable by humans: for example, to guide scientists through formulations or sets of ingredients, via complex biological systems such as the microbiome, the ecosystem consisting of trillions of bacteria found in and on our body including the skin, scalp and gut, and identify possible beneficial effects with great potential to improve our health, wellness and appearance. Being able to understand the microbiome and generate new hypotheses quickly allows companies to develop better products faster.
How does your technology work?
Our platform e[datascientist]™ leverages artificial intelligence (AI) and network science in order to surface scientific connections and explore multi-causal relationships. The platform can achieve this in collaboration with or without bioinformaticians and data scientists. It can therefore help reduce the repetititive, routine work required by such specialists, enabling them to spend more time addressing complex challenges.
Biological systems are full of synergistic interactions between various factors including microbiomes, environments, immune systems, host genomes, and nutrition. In such biological systems, causal relationships are seldom simple and linear, but rather complex and multi-dimensional. Given this significant complexity and the multi-omic ‘big data’ wave, studying and understanding causal claims of microbiome-based solutions can only be done by applying network science and other advanced analytical tools.
Network science helps us understand how different factors influence the skin microbiome, and how this affects host immunity, down to the level of individual consumers or patients. This requires the e[datascientist]™ platform to manage heterogeneous data from disparate sources in a unified, digitized environment. This trusted ‘data fabric’ is accessed through an intuitive, user-friendly application framework that supports scientists through their entire innovation journey.
How can your platform provide impactful results to personal care formulators?
The global beauty and personal care industry is increasingly focused on providing evidence about the health, efficacy and performance aspects of its products. There is also a greater commitment to sustainability, both in terms of how products are made and the downstream effects on the environment. One really exciting aspect of microbiome science is that it provides opportunities to identify and produce compounds and novel ingredients for products, for example natural and organic alternatives to existing, more harmful ones. In this and in many other contexts, we help scientists generate novel insights, including the generation of evidence that can support their product claims, all at unprecedented speed.
How can clients benefit from your data? Can clients combine their own findings with your data?
At Eagle Genomics, we use the term ‘trusted data fabric’ to describe the data structure that is the foundational element on our platform. This enables reliable and repeatable science, bringing together and managing heterogeneous data and metadata from disparate sources. These data and metadata first require standardization. To this end, data curation is the essential first step to integrate data from enterprises (our clients) and our knowledge partners, with publicly available data sources.
We work with global organizations, including Unilever, Cargill, and others, which have stored data in distributed locations. Our platform is also being used to provide visibility to ‘lost’ datasets - so called ‘dark data’ - which we can help onboard and make functional. The number of users that can access the platform can be tailored to the specific needs of a particular company and/or department, ranging from a few up to a ‘theoretically unlimited’ number.
Using external datasets and elevating internal data to the platform essentially means being able to see novel solutions and hypotheses that scientists would have never previously expected or considered. Unilever, for example, uses metagenomic data – genetic data from the microbiome – to understand how microbes interact with the human body. As part of this work, we enabled one of the first uses of a microbiome-specific scientific product claim. This was for a Unilever toothpaste product, determining its effect on improving the oral microbiome ecology.
In what ways can you contribute to improved sustainability for your customers, and/or sustainability claims?
Eagle Genomics is focused on enabling organizations to reduce the footprint of their R&D activities through the adoption of a digitized ecosystem for in silico experimentation. e[datascientist]™, enables data to be reused, allowing for repeated value generation. Our clients have used existing data to transition from synthetic to natural ingredients, which can have beneficial effects on the environment and climate as well as our bodies.
In terms of sustainability, technologies involving microbes are currently experiencing an extraordinary degree of innovation, and at Eagle Genomics, we firmly believe that the microbiome is a key driver across numerous industries. For example, microbes and fermentates are increasingly being used to formulate new compounds of high industrial value. The data analytics capabilities required to tailor and enhance such processes and novel components are the key to unlocking these new innovations, which could ultimately also benefit our planet.
Why do you say that your platform helps with reproducibility in R&D?
The reproducibility of research results is of significant and growing concern in areas like life sciences R&D – equalling up to $28B per year in irreproducible preclinical research, according to PLOS Biology. A centralized technology platform like Eagle Genomics’ e[datascientist]™ enables sharing and reusing of research data across multiple organizations and users, improving the digitization, and reducing the “siloization”, of legacy scientific R&D systems. This digitization, enabled by a modern understanding of science coupled with rapid innovations in technology, dramatically reduces the unnecessary, potentially polluting repetition of ‘trial and error’ laboratory experiments through the repeatable and reproducible nature of in silico experimentation. This reduces cost, waste cost, waste, and time to insight while significantly contributing to improved sustainability.
What is a healthy skin microbiome and what role does it play in skin aging?
Our skin is home to millions of bacteria, fungi and viruses that compose the skin microbiota. There is no exclusive definition of a healthy skin microbiome, just like there is no perfect genome. There are multiple healthy skin microbiomes. This can also extend to the scalp and hair, as well as oral and genital environments.
By measuring individual profiles, our clients can develop customized solutions for personal care and medical products, such as those addressing body odour, psoriasis, rosacea as well as countless other conditions and/or chronic diseases. Network science is required to understand the connections between skin health and the skin microbiome, as well as the different factors that can affect them. To that end, we provide the platform that can enable scientists to unravel and quantify these complex and vital interactions.
References:
[1] Freedman LP, Cockburn IM, Simcoe TS (2015) The Economics of Reproducibility in Preclinical Research. PLoS Biol 13(6): e1002165. https://doi.org/10.1371/journal.pbio.1002165.
