Innovation is the lifeblood of biotech companies, driving not only their own growth but also improved health outcomes for people worldwide. However, biotech business models center on the development and commercialization of core IP, and are therefore a prime target for theft.
There are, of course, significant financial ramifications to IP theft, which in the U.S. alone costs the economy up to $600 billion annually. Now, lawmakers are piling on additional pressure. The U.S. Biosecure Act, which has just passed the House of Representatives, proscribes U.S. companies from sharing data with specified Chinese biotech companies. Given just how deeply U.S. biotech relies on Chinese contract manufacturers to develop therapeutics, the law will create a significant operational headache.
Another complicating factor in the drive towards better IP protection is that biotech companies are increasingly migrating their operations to the cloud. While offering scalability and flexibility, the cloud also exponentially increases data use within organizations. Even the most advanced security teams find themselves challenged by the sheer volume, variety, and velocity of data now flowing through enterprise systems.
What’s more, data in the cloud moves with ease and rapidity. Data scientists, for example, may replicate entire tables from one environment to another for analysis without realizing the potential exposure of sensitive information. Similarly, employees might inadvertently copy text from proprietary documents to share via email, increasing the risk of data leakage. In today’s digital age, both structured data (like databases) and unstructured data (such as emails and documents) are constantly being viewed, copied, modified, shared, and moved within and outside the organization.
This dynamic nature of data handling in the cloud demands a rethinking of traditional IP protection strategies. Traditional security models are proving inadequate because they are not designed for the fluid, decentralized nature of cloud environments. Instead, biotech companies must look towards more sophisticated security strategies.
The very first step biotech businesses should take is to gain a holistic understanding of their data estate, including visibility into where and how data is shared. Given the huge volume of data in play, the use of innovative AI-powered systems is inevitable.The Bedrock AIR platform is one such system. The platform can efficiently manage and secure enormous datasets by comparing the similarities of billions of files, each potentially many gigabits in size, without compromising on speed.
This capability is enabled by the platform's data fingerprinting technique. For example, a biotech business can take a 100-gigabyte file and condense it into a series of vectors that are just 10 kilobytes each. The platform then scans for matching vectors across its network, enabling rapid discovery of IP data in a distributed and scalable manner.
The approach also allows for partial matches between gene sequences, giving bioengineers the ability to verify that one sequence is 99.9999% similar to another sequence. This is important for IP protection as it can pick up matches that would be missed by traditional similarity detection frameworks, such as when a bioengineer makes a small nucleotide change that completely changes the appearance of a genome sequence.
The Bedrock data security platform provides additional IP defenses through comprehensive entitlement mapping and automated policy monitoring and validation, providing unprecedented protection for users.
The Bedrock AIR platform is already being used by biotech companies to protect and manage their most important data.
For example, one major biotech company came to Bedrock Security with the challenge of protecting over 10,000 unique gene sequences. The company had found that traditional security measures failed to keep up with the variations that might occur in genetic data during research processes.
With Bedrock’s AIR platform, the company is now armed with a system that not only recognizes data, but also understands the context of individual nucleotides within synthetic DNA sequences. The platform can thereby comprehensively safeguard the company's genetic sequences, identifying both exact copies and derivative versions no matter where they travel in the digital landscape.
The implementation of Bedrock’s system has transformed the company’s approach to data security. By creating detailed fingerprints of each gene sequence, the platform tracks and monitors assets across all digital touchpoints. Anytime a gene sequence or its derivative appears in an unauthorized location or headed towards an inappropriate data store, the system flags it immediately. This capability ensures that the company can react swiftly to secure the data before any potential leak occurs.
Of course, the challenge of protecting IP is not confined to any one sector; it's a universal issue facing businesses across all industries. The success of businesses' IP protection efforts in the cloud era hinges on their ability to adapt and implement more sophisticated, context-aware security solutions like data fingerprinting. For organizations aiming to thrive and maintain their competitive edge, the evolution of security strategies isn't just an option—it's a necessity.
To learn more about how the Bedrock platform can protect IP in even the most complex of IT environments, see a live demo today.