AI Simplifies Drug Discovery Data Management:

Calithera Biosciences is a small, Northern California immunotherapy company that has a pipeline of medications that are in different levels of the pre-market process to treat cancer and cystic fibrosis. As with any company that develops complicated new products, Calithera maintains an extensive database of information.

However, unlike companies with advanced technology in other industries pharmaceutical companies, drug discovery companies have their own US Food and Drug Administration always watching their backs especially when they’re evaluating their products on humans.

Calithera has clinical trials that are registered for its products to test their efficacy, their safety, for patients suffering from specific gene mutations, as well as the effectiveness of their use when combined with other treatments. The company is required to collect comprehensive information about many patients. Although some studies are still in the early stages and only involve a handful of patients, other trials involve hundreds of research centers across the world.

“In the life-sciences world, one of the biggest challenges we have is the enormous amount of data we generate, more than any other business,” says Behrooz Najafi who is Calithera’s principal information tech strategist. (Najafi is also the chief information as well as technology chief of the health technology firm Inovio.) Calithera must manage and store the information while ensuring that it’s available at any time even decades from now. Also, it must comply with the specific FDA specifications regarding how the data is created and stored. It must also be able to use the data.

It’s not that simple as updating a file server should be done according to a specified FDA protocol that involves multiple tests and review procedures. Najafi states that all this data-related compliance wrangling can add between 30% and 40% to the cost of a company such as his, both in the direct costs and the hours of employee time. These are funds that could be used for research or other activities that add value.

Calithera has escaped much of the cost and dramatically improved its capacity to keep track of its data by placing it in what Najafi refers to as the secure “storage container,” a secured area to store content that is regulated as part of a larger cloud-based document management system that is largely powered through artificial intelligence. AI is never bored and is never bored and can recognize between hundreds of different kinds of documents as well as forms of data.

This is how it works Clinical or patient information is transferred to the system and then scanned by AI that recognizes certain characteristics that relate to the accuracy, completeness, and compliance with regulations as well as other features of information. AI will alert you of any missing test result, or if patients haven’t provided an entry in their diary that is required. AI can determine who is allowed to access specific types of data, and the data types they can access, and what they’re not permitted to access. It can detect ransomware threats and ward them off. It can also automatically record all this at the request of the FDA and any other regulatory agency.

“This approach takes the compliance burden off of us,” Najafi states. When data from Calithera’s numerous research sites are in Calithera’s platform Calithera is aware that its AI will verify that the data is completely safe and in compliance with all laws and will alert any potential issues.

The management of drug discovery data to satisfy the demands of research as well as the demands of regulators is, as Najafi says, time-consuming and costly. Life sciences companies can take advantage of the data management methods and platforms designed for other industries, however, they need to be modified to meet the requirements of security and validation and the thorough audit trails, which are the norm to drug makers. AI can simplify these tasks by enhancing the security, accuracy, and accuracy of data, freeing costs for research and drug company organizations to use for their primary purpose.

A complex data management environment:

Compliance with regulations will ensure that the new medicines or devices have the safety and performance in the way they are intended to. Also, it protects individuals’ privacy, as well as the private information of the millions of participants in clinical trials as well as post-market research. No matter how big–whether huge multinational conglomerates or small startups striving to bring one product off the shelf, drug makers should adhere to the same standards to record the trial, verify it, and audit it and secure every bit of information related to a clinical trial.

If researchers conduct a double-blind investigation, the most reliable method of proving the efficacy of a medicine is to keep the patient’s information private. But they can easily remove the anonymity later and make it identifiable so that the patients who are part of the control group are given the drug of choice, and the company can monitor, sometimes for years– how the drug performs in actual use.

The burden of managing data is particularly heavy on new biosciences companies of mid-sized size according to Ramin Farassat, chief of strategy and product officer of Egnyte the Silicon Valley software company that develops and maintains the AI-powered data management system that is used by Calithera as well as a variety of other life science companies.

“This approach takes the compliance burden off of us,” Najafi states. When data from Calithera’s many research sites are on the system, Calithera is aware that its AI will ensure that it is secure, complete, and compliant with all applicable regulations and will alert any potential issues.

https://www.suryasys.com/a-tourism-industry-using-big-data-for-improved-business-production/