Calithera is conducting registered clinical trials to study their safety on its products, regardless of whether they are effective in patients with certain genetic mutations, and how well they work in combination with other therapies. The company must collect detailed data of hundreds of patients. While some of its trials are in the early stages and involve only a small number of patients, others are spread across more than 100 research centers around the world.
“In the world of life sciences, the biggest challenge we face is that the huge amount of data we generate is greater than any other business,” says Behros Najafi, Calithera’s leading information technology strategist. (Najafi is also the Chief Information and Technology Officer for health-care tech company Innovio.) Calithera must store and manage data while making sure it is readily available when needed, even years from now. Specific FDA requirements regarding how data is generated, stored, and used should also be complied with.
Even as simple as upgrading a file server, it must adhere to strictly defined FDA protocols with multiple testing and review steps. Najafi says all these compliance related data disputes can add 30% to 40% to the overhead of a company like it, both in direct costs and staff time. These are resources that could otherwise be directed towards further research or other value-added activities.
Calithera has slashed those additional costs and greatly improved its ability to track data by manipulating it through a secure “storage container”, a protected area for controlled content, part of a larger cloud document management application. Artificial intelligence. AI never sleeps, never gets bored, and can learn to distinguish between hundreds of different types of documents and forms of data.
Here’s how it works: Clinical or patient data is placed in a system and scanned by AI, which identifies specific features related to accuracy, completeness, rules, and other aspects of the data. AI can flag when there is a missing test result, or when the patient has not submitted the required diary entry. It knows who is allowed to access certain types of data and what they are and what they are not allowed to do with it. It can detect ransomware attacks and eliminate them. And it can automatically document them all to the satisfaction of the FDA or any other regulatory body.
“This approach lifts the burden of compliance from us,” says Najafi. Once the data of many of its research sites have come to the platform, Calithera knows that AI will ensure that it is safe, complete and will follow all the rules. Mark any problems.
Managing drug discovery data to comply with research needs and the needs of regulators, as Najafi observed, can be cumbersome and expensive. The life sciences industry may borrow advanced data management techniques and platforms for other industries, but needs to change to handle security and accreditation levels, and detailed audit trails, which are a way of life for drug developers. AI can streamline these functions, improve security, compatibility and data validity – freeing drug companies and research institutes from overhead to apply to their core mission.
A complex data management environment
Regulatory compliance helps ensure that new drugs and devices are safe and function as intended. It also protects the privacy and personal information of thousands of patients who participate in clinical trials and post-market research. Regardless of their size – large global organizations or small startups trying to market a single product – drug developers should follow the same standard methods for documenting, auditing, validating and protecting every piece of information associated with a clinical trial.
When researchers run a double-blind study, the golden standard for proving the effectiveness of a drug, they have to keep patient information confidential. But they should then easily release the data so that it can be identified, so that patients in the control group can get the test drug, and so the company can track કેટલીક sometimes for years કેવી how the product works in real-world use.
The burden of data management falls on emerging and mid-sized bioscience companies, says Ramin Farasat, chief strategy and product officer at Silicon Valley software company Agnite, which builds and supports the AI-enabled data management platform used by Calithera. Science companies.
“This approach removes the burden of compliance from us,” says Najafi. Once data from many of its research sites comes to the platform, Calithera knows that AI will make sure it is safe, complete and compliant with all regulations, and will mark any problems.
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This content was created by MIT Technology Review’s custom content arm, Insights. It was not written by the editorial staff of MIT Technology Review.