How AI influences data management in product acquisition

Calithera is testing clinical trials on its products to learn about their safety, whether they are useful for patients with a specific condition, and how they work in combination with other medications. The company has to collect information about hundreds of patients. While some of its trials are in its infancy and include a small number of patients, others go beyond more than 100 study centers around the world.

Behrooz Najafi, a specialist at Calithera, said: “In the world of life sciences, one of the biggest challenges we face is the amount of data we generate, more than any other business.” (Najafi is also the chief medical officer at the medical company Innovio.) Calithera should maintain and correct the viewing information and ensure that it is readily available when needed, even years from now. It must also comply with FDA requirements for data processing, storage, and use.

Even something that seems as simple as upgrading a file server should follow FDA’s standard procedure for testing and reviewing a few. Najafi says all disputes related to the following could add 30% to 40% to a large company like its own, total cost and working hours. These are items that can be donated for research or other value-added items.

Calithera has left much to be desired and expanded its ability to track its knowledge by placing it in what Najafi calls a “storage container” secure, secure storage space, part of a larger cloud-based document management program, especially driven by artificial intelligence. AI does not sleep, does not get tired, and can learn to distinguish between different types of writing and different types of information.

Here’s how it works: medical or patient information is organized into AI, which recognizes certain aspects of accuracy, completeness, compliance, and much more. AI can play out when there are no test results, or if the patient has not provided the necessary documentation. It knows who is allowed to access other types of information and what they are and is not allowed to do with it. It can detect the damage of redemption and remove them. And it can register all FDA or any other regulatory requirements.

“This method relieves us of the burden,” says Najafi. Once they find that their research site is located on the platform, Calithera will know that AI will ensure that it is safe, complete, and compliant with all the rules, and will report any problems.

Managing drug availability information to match research requirements and requirements for regulators can be, as Najafi observes, tedious and expensive. Life science companies can borrow data management systems and platforms for other industries, but they need to be adapted to ensure security and reliability, and more sophisticated methods, which are a way of life for pharmaceuticals. AI is able to effectively manage the process, improve security, flexibility, and reliability of information-release for pharmaceutical companies and research organizations to use in their core business.

A difficult place to manage data

Compliance ensures that new products and equipment are safe and effective. It also protects the privacy and personal information of thousands of patients who participate in clinical trials and market research. No matter how big they are – more or less international organizations trying to sell a single product to sell – the manufacturers must follow the same procedures to record, evaluate, validate, and protect any information about medical examinations.

When researchers conduct blind research, the gold standard of clinical practice is the need to keep patients’ information anonymous. But they should easily explain the information later, so that it can be identified, so patients in the receiving cohort can receive experimental treatment, so the company can track – sometimes for years – how the business works in real life.

The burden of data management is a challenge for both emerging and medium-sized companies, says Ramin Farassat, chief logistics and companies company at Egnyte, a Silicon Valley software development company that develops and supports the AI-linked data management platform used by Calithera and others. several hundred life- science companies.

“This method removes our burdens,” says Najafi. Once most of its research facilities are on the platform, Calithera knows that AI will ensure that it is secure, complete, and compliant with all regulations, and will highlight any problems.

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This was created by Insights, the hand of material contained in the MIT Technology Review. It was not written by the authors of the MIT Technology Review.

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