BOSTON, Mass., August 30, 2023 - TetraScience, the Scientific Data Cloud company, today announced a partnership with DataHow, a provider of a digital bioprocess development platform, to help customers transform bioprocess design and optimization using Tetra Data - the life science industry’s only AI-ready scientific data.
“DataHow facilitates bioprocess design and optimization with self-learning and hybrid models, transfer learning and digital twins,” said Alan Millar, Ph.D., VP, Tetra Partner Network. “These technologies must be fueled by large volumes of contextualized and harmonized scientific data. By combining DataHow’s capabilities with AI-ready Tetra Data, we can transform the development and optimization of bioprocesses.”
DataHow’s customers include 12 of the top 20 global pharmaceutical companies. Their platform, DataHowLab, addresses the key operational challenges in biopharma process development: time, resources, risk, and manufacturing downtime, as well as the productivity of teams. DataHowLab accelerates process design and development through sophisticated data analytics that produce better insights for faster decision making. Their digital twin capabilities enable bioprocess engineers to simulate change variables, generate predictions, and dramatically improve the design space. Through model-based process development, DataHowLab reduces experiments by as much as 60% in Phase 1 and 2 screening as well as in Phase 2 study optimization with CDMOs (Contract Development Manufacturing Organizations).
The Tetra Scientific Data Cloud™ is a cloud-native platform purpose-built for science that engineers scientific data into an open, vendor-agnostic, AI-ready format - Tetra Data. The partnership with DataHow will help customers fuel bioprocess models with much larger volumes of contextualized and harmonized data (Tetra Data), enabling automatic learning from new data and driving efficiencies across multiple products and/or process features.
“We are delighted to partner with TetraScience whose ability to replatform and engineer scientific data for AI provides essential building blocks for scientific AI/ML and the adoption of digital twins,” said Moritz von Stosch, Ph.D., Chief Innovation Officer, DataHow. “Our partnership will help bioprocess engineers make significant strides in process optimization as well as knowledge and tech transfer that can be used for subsequent experiments.”
“Scientific data must undergo a very precise and sequential engineering process in order to yield data sets capable of being effectively exploited by AI,” said Patrick Grady, TetraScience Chairman and CEO. “The Tetra Scientific Data Cloud is capable of producing fundamental breakthroughs derived from the large scale, organized scientific data necessary to fuel AI. We welcome DataHow to the Tetra Partner Network so that our combined expertise can enable data-driven decision-making to exponentially accelerate and improve scientific outcomes.”
About TetraScience
TetraScience is The Scientific Data Cloud company with a mission to accelerate scientific discovery and development and improve and extend human life. The Tetra Scientific Data Cloud(™) is the only open, cloud-native platform purpose-built for science that connects lab instruments, informatics software, and data apps across the biopharma value chain. It delivers the foundation of harmonized, actionable scientific data necessary to transform raw data into accelerated and improved scientific outcomes. Through the Tetra Partner Network, market-leading vendors access the power of our cloud to help customers maximize the value of their data. For more information, please visit tetrascience.com.
About DataHow
DataHow is the provider of the digital bioprocess development cloud focused on accelerating process development, optimizing manufacturing processes and increasing robustness by using hybrid modeling and transfer learning solutions. Our cloud solution and services are tailored to upstream (cell culture, fermentation, seed train, etc.) and downstream (chromatography, ultrafiltration, diafiltration, etc.) biopharma operations providing the user with essential insights for process development, characterization and scale-up. Our unique Digital Twin technology allows us to handle all process units and their interactions, and to transfer knowledge between scales, projects, and product targets. With our approach we want to support the decision process of process experts, scientists and operators by leveraging in our technology all available process data and knowledge. DataHow was incorporated in 2017 as a spin-off from ETH Zurich and operates with 45 team members across 3 continents. www.datahow.ch