CIO Bulletin

Collect, centralize, and harmonize your scientific data to accelerate and improve scientific outcomes: TetraScience

TetraScience is the Scientific Data Cloud company with a mission to accelerate scientific discovery and improve and extend human life. While the company was founded in 2014, TetraScience began its Scientific Data Cloud journey in 2019 with the origin of the Tetra Data Platform (TDP). The Tetra Scientific Data Cloud™ is the only open, cloud-native platform purpose-built for science and provides life sciences companies with the flexibility, scalability, and data-centric capabilities to enable easy access to centralized, harmonized, and actionable scientific data.

TetraScience has built the largest integration network of lab instruments, informatics applications, CRO/CDMOs, analytics, and data science partners, creating seamless interoperability and an innovation feedback loop that will drive the future of life sciences and the delivery of life-saving therapeutics. TetraScience’s team combines deep domain knowledge, the industry’s only open, purpose-built scientific data cloud, and a global community of instrument, informatics, data science, and integration partners to drive the future of life sciences and harness the power of the world's scientific data. Backed by Insight Partners, Alkeon Capital Management, Underscore, and Impetus Ventures, TetraScience currently counts over 100 leading pharmaceutical and biotech companies as customers.

TetraScience Sciborgs Drive Better Science

Consider cyborgs - humans enhanced with tech components. They’re omnipresent: Arnold Schwarzenegger as the T-100 in Terminator. Steve Austin, saving the world as the $6,000,000 man. Jean-Luc Picard as Locutus of Borg, the biggest threat to Star Trek’s Federation. Genos, the wandering apprentice from anime series One-Punch Man.

The fusion of technology and science to meld the biological to the technological represents raw, synergistic power: both leading to a 1+1 = 5 type of outcome. A true differentiation for those who’d harness this type of hybrid individual. For others thinking about Sciborgs, check out the recent post by Jorge Conde from a16z, in which he discusses the biopharma SaaS landscape and refers to ‘multi-lingual founders fluent in both tech and biotech. Already in 1980, Steve Jobs hypothesized that human augmentation would radically increase problem-solving and usher in a new era: “Computers are like ‘bicycles for the mind’; they take us far beyond our inherent abilities. And I think we’re just at the very early stages of this tool: we’ve come a very short distance, and it’s still in its formation, but that’s nothing compared to what we’ll see in the coming years.”

Over the past three years, TetraScience has uniquely built a foundational employment brandthat few can match. Thanks to extensive market research, internal training programs and experiential “on-the-job” learning in specific customer accounts on demanding scientific use case challenges, TetraScience’s Sciborgs match a specific phenotype despite their diverse backgrounds:

Sciborgs have personally felt the pain of inefficiency in laboratory, manufacturing, and “dry-lab” workflows. They commiserate, empathize, and synthesize learnings with customers to improve and standardize scientific workflows across the industry.
Sciborgs show great impatience with the current state: They saw change coming, the need for it, and embraced it. They plumbed up automation cascades using open-source Python libraries in graduate school. They developed lightweight dashboards for their company division. They used R to show statistical plots to support their decisions. They played with image feature recognition in their spare time. These “purple squirrels” didn’t wait to be “told” to learn - they embraced the future state.
Sciborgs live at interfaces: Science and technology. They are neuroscientists who love Python scripting. Chemists who revel in automation of continuous manufacturing processes. Antibody and immunology researchers who utilize R and Tableau to tell stories about their data. Data scientists modeling results from offline CMC experiments to implement real-time release testing.

The behaviors above speak to will, but what about skill? Tetra Sciborgs aren’t just any data advisors!

Nearly all have Ph.D.s in a relevant scientific domain, or MS degrees in Engineering or Computer Science.
All have background knowledge in technical system architecture at the enterprise level.
They are intellectually nimble - they can quickly switch contexts to different phases of drug manufacture, integration modalities, or learn the nuances of a given scientific use case.
Finally, in case you missed it, above - they’ve lived in the lab in a prior life, where extraction of data from proprietary systems, processing, and preparation was still an ad hoc effort not covered by any solution currently on the market.

Artificial Intelligence and Machine Learning (AI/ML) are potentially transformational techniques underpinning self-operating “black-box” automated workflows for human problem solving like image recognition or the identification of potential lead drug candidates. While productized data integrations are upstream preconditions, the missing and essential piece is the Tetra Scientific Data Cloud TM, the biopharma industry’s only purpose-built, enterprise-grade, cloud-native data engineering platform, specifically designed to provide labs with the flexibility, scalability, and data-centric capabilities to enable easy access to centralized, standardized, compliant, engineered, liquid, and actionable scientific data – aka Tetra Data. Think about Sciborgs like the “drivers” of this change, using the Scientific Data Cloud as their toolkit. This enables these individuals to go “up the stack” from bottom-shelf data ingest and integration into the realm of use case optimization and data science ROI.

Patrick Grady, Chairman & CEO