Can Hootsuite like interface tackle data management challenges in ADC manufacturing?

By Jane Byrne contact

- Last updated on GMT

© GettyImages/metamorworks
© GettyImages/metamorworks

Related tags: Antibody drug conjugates, payload, Oncology, impurity profile

Data management in antibody drug conjugate (ADC) manufacturing is challenging says ADC/Labs, which is trying to help scientists in the field get around such obstacles.

Over 180 ADCs are currently in clinical trials and at least 50 biopharmaceutical companies are operating ADC development programs, with the market expected to grow from US$2-3bn in 2021 to US$13bn in 2026, according to a Kuick Research report. 

Despite the projected growth of ADCs beyond oncology and into treatments for other diseases, their development faces key data management issues, said Joe DiMartino, who manages a software platform called Luminata, at ACD/Labs.

ADC/Labs, he said, wants to determine how pharma companies manage their data, how they view their data, and what systems are in place when something in the development process goes askew.

Its software tool, which now has enhanced functionality, supports ADC development from the initial establishment of the most advantageous combination of ADC components through optimization of the conjugation and purification process, characterization of the final product and process intermediates, and understanding how process changes impact the impurity profile and efficacy of the product.

Molecular complexity

Although some ADCs involve a direct linkage between the antibody component and the drug, it is far more common for an ADC to consist of three main structural units: a monoclonal antibody (mAb), a small molecule drug - the payload - and a linker covalently connecting the mAb to the payload.

Due to their molecular complexity, ADCs require a number of analytical techniques to characterize their structures, drug antibody ratios (DARs), and impurity profiles, according to DiMartino.

These techniques generate different types of analytical data in different file formats and are often managed by different groups, he said.

“ADC development involves many team members, for the antibody aspect there is the bioprocess engineer, then, in terms of the small molecule aspect, there is the process chemist and/or analytical chemist who stores all that data, that is where the disconnect happens, all of the information is not in one place,”​ he told BioPharma-Reporter.

Given the wide range of analytical techniques employed during the development and manufacture of a typical ADC, the associated analytical data is spread across multiple, separated instrument databases, CDSs, and other data silos.

“Historically, we have all this technology, we have all of these instruments and all of these places where you can store knowledge and what I have seen is a lot of people are using Excel and placing that on SharePoint. It is kind of scary when, in terms of drug development, all this great knowledge in an organization is stored as an Excel spreadsheet, with, perhaps, ten versions of the spreadsheet on SharePoint.

“All these numerical values are being placed together to make critical decisions but relying on someone writing it in or copying and pasting data, so there are a lot of possibilities for man-made transcription errors, if using Excel.”

If an issue arises during the complex ADC development process, such data storage methods do not make for an easy fix or understanding of what went wrong and at what stage, he said.

Another consequence of the volume and variety of analytical data, and the range of different data sources, is that bringing all relevant information together is a manual and time-consuming process.

Also, he said, it is sometimes only done at the point of reporting rather than as an ongoing procedure. 

Rich data interface  

The Luminata tool, he said, enables scientists involved in the development and manufacturing of ADCs to see the big picture and make better informed decisions faster from a single software interface.

“Our database platform allows the storing of rich analytical data. It allows you to open all raw analytical data formats, such as chromatograms​, LC-MS and LC-UV, and then store that knowledge all together. In the case of ACD/Labs, we take data from validated GMP instruments and store that in one location, to inform decision making. There is an audit trail. You can visualize live data.

“So if manufacturing challenges arise, the scientist can determine why one linker did not work, for instance; the platform makes it easy to visualize and navigate the analytical data corresponding to each stage of the ADC production process,”  ​added DiMartino. 

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