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Batch release is another way we are using here. So this actually is a very nice collaboration tool between the CMOs and the sponsors. They can actually work on any particular batch at the same time.
So the manufacturer, the CMOs can do their manufacturing release, the quality release can happen from the sponsor’s side. So let’s say if you’re 100 page paper batch record, right?
The co-pilot actually tells you you have a problem in page number seven, page number 19, and page number 23, that’s it. You just go to those pages, you see what the problems are, you solve the problems, you move on.
You really don’t need to basically do the full exhaustive, let’s say, review each time, right? And again, then that becomes an issue in terms of how you see this, how you perceive this.
The tools are now there to help you, right? If you still want to basically review all the 100 pages, that’s up to you. That’s your quality standard, you can stick to that.
But from a perspective of the tools being there, the tools are there, that will point to you where it needs your attention. And then you can choose how to spend time there.
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Frequently Asked Questions
Mareana has helped numerous firms in the Pharmaceutical, Chemical, Medical Device, and Industrial Manufacturing industries.
Batch release is the process of reviewing and approving a manufacturing batch before release. It enables CMOs and sponsors to work simultaneously on the same batch, allowing manufacturing and quality reviews to happen in parallel for greater efficiency.
An AI co-pilot analyzes batch records and identifies specific pages that require attention, helping reviewers quickly locate and address potential issues instead of manually reviewing the entire document.
Yes. For example, in a 100-page batch record, the AI tool can highlight only the pages with potential problems, allowing reviewers to focus their efforts where they are needed most and significantly reducing review time.
No. AI serves as a support tool that guides reviewers to areas of concern. Organizations can still perform a complete manual review if that aligns with their quality standards and procedures.
Key benefits include faster review cycles, improved collaboration between stakeholders, reduced manual effort, quicker issue resolution, and more efficient use of quality and manufacturing resources.
Quality teams remain responsible for all final decisions. AI provides recommendations and highlights potential issues, but reviewers determine how extensively to investigate and whether additional review is required.
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