Accelerate Biotech Innovation

Impacts of Modern Transcriptomics Data Analytics Platforms

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In the past decade, the groundwork has been established for researchers to leverage the power of data to advance their science. This has occurred alongside an explosion of affordable data generation and the development of extensive, publicly available data sets, like genetic sequences on GEO or proteins on PRIDE. At the same time, there was a significant rise in biotechnological advancements: mRNA vaccines were developed in record time, CAR-T therapies and liquid radiotherapies were approved by the FDA, and breakthroughs in precision medicine for Alzheimer’s treatment were made.
All these advances would not be possible without modern solutions, enabling global collaboration, eliminating repetitive tasks, and generating valuable insights.

Also, McKinsey’s 2022 Technology Trends report highlighted an increased interest and digital innovation such as cloud computing, applied artificial intelligence, and machine learning across various industries, including the life sciences.

Researchers have just started to leverage next-gen digital technologies to handle vast datasets, improve their pipeline predictions, and better define their experimental approaches. Such digital solutions save time by removing manual data analysis and avoiding human errors, leading to faster data-driven conclusions that ultimately result in faster milestone achievement.

Thus, it’s crucial for modern biotech companies to reevaluate their technical infrastructure and replace unsuitable systems and processes that hinder their ability to accelerate innovation.

Although biotech and pharmaceutical companies have made significant efforts in generating data, many are still constrained by their self-made data-analysis processes rather than enabled by them – resulting in an analytical bottleneck. Scattered scripts that are difficult to update, time-consuming to run, and limit collaboration resulting in slow progress that hinders an organization’s ability to leverage insights.

BigOmics takes a fundamentally different approach to setting up our customers for success so they can focus on developing state-of-the-art therapeutics for the greater good. By establishing a central source of truth for omics data, BigOmics’ Data Analysis Platform, Omics Playground, brings together teams in research, development, and informatics and allows them to mutually gain key insights to push their science to the next level. With this, we’ve empowered hundreds of scientists at leading biotech companies and prestigious academic institutions to speed up their R&D programs. 

Download the full Case study to learn how.

«For us, the benefits were immediate. All the little things add up to the whole system being more intuitive, more efficient, and ultimately empowers scientists to look into their data without constantly asking our Bioinformaticians. »
Yasuo H.
Global Head of Technology Research

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