February 12, 2020
Data management for advanced therapies, Part 6: efficiencies across the supply chain
Note: this post is the sixth in an eight-part series on data management strategies for personalized therapies, such as cell therapies, gene therapies, or neoantigen cancer vaccines. You’ll find the prior installment, on data considerations related to traceability, here .
A Biologics License Application is time-consuming and labor-intensive for the simplest of drug products. When it comes to personalized therapies, the complexity escalates in all directions.
The personalized supply chains for patient-specific treatments generate a very large volume of data, due to a distributed, patient-specific manufacturing process and unique compliance requirements. As a result, the data collection, analysis, and reporting processes necessary to complete a drug filing can become complicated and extremely resource-heavy.
In addition to supply chain complexity, operations and manufacturing costs can be very high —which adds to the already increasing pressure on the biopharma and healthcare space to reduce costs.
For more streamlined, cost-effective operations, advanced therapy teams must focus on improving efficiency across their workflows. Excerpted from Vineti’s Advanced Therapy Guide:From Complex to Controlled, here is a sampling of data management strategies that improve efficiency.
Data management automation to reduce costs
The R&D and clinical trial processes for personalized treatments are often more complex than traditional drug products. As we outlined in the first part of this series, each patient represents an individual manufacturing batch in an autologous therapy scenario, each with its own manufacturing data to be collected, analyzed, and reported.
Clinical operations are often manual in early phases, which is inefficient and can increase compliance and safety risks. And as patient volume increases, workflow management becomes more complex, requiring more time and resources. Thorough, accurate, automated data collection implemented early can make all the difference.
Pro tip: focusing on scalable data management from the beginning will provide efficiency and cost controls.
Digital stakeholder management
Unlike mass-produced drug products, personalized therapies often have a distributed supply chain and end-to-end manufacturing process. Different aspects of the process can take place in up to a dozen locations. Collecting and harmonizing patient data from multiple facilities — each using different systems and potentially subject to different regulatory requirements — will add time, resources, and significant cost to your R&D.
Streamlining stakeholder management through an automated solution will save time and help bring your operations under control. Consider some of the key information required for the CMC section of your application, all of which is dependent on distributed stakeholders – patient identification, COI, COC, patient material data collection, and labeling. To get complete CMC data, you must align and manage your stakeholders.
Pro tip: as early as possible, implement a digital supply chain management system for all stakeholders to standardize and control processes and ensure high-quality data.
Time management for starting material
Part of what makes personalized therapeutics unique is the living, patient-specific starting material. As we outlined in Part 2 of this series, living cells and the final drug product both require a controlled environment throughout all stages of the process in order to remain viable. And in the distributed ecosystem of cell and gene therapies, that often includes transportation to and from different facilities.
Logistics must be coordinated seamlessly to ensure that starting material arrives on schedule and in the required condition, while also allowing for flexibility if a complication arises. A successful data management strategy should therefore include logistics orchestration and Chain of Identity and Chain of Custody.
Pro tip: use a centralized data and supply chain management system to track progress and location of your raw material or product in real-time.
As we discussed in our last post, traceability requirements must be met from day one. Advanced therapy drug filings must demonstrate that safety-related specifications are being met, which requires the analysis and packaging/synthesis of very high volumes of data. At even moderate scale, capturing or managing this data manually is often not an option. And in a commercial filing, the FDA and EMA typically require that a compliant digital traceability system to be in place. Fundamentally, patient safety will depend on it.
Pro tip: automating compliance as part of your data management strategy will free up resources for more value-add activities.
Next in this series, we’ll summarize key data management strategies. If you have data-related questions for us in the meantime, please contact us.
A digitally-managed supply chain can streamline compliance, minimize risk, and improve the quality of your data. Find out more in Vineti’s Advanced Therapies Guide: From Complex to Controlled.
Data management for advanced therapies series:
Part 1: the need for new strategies
Part 2: unique data features
Part 3: working with living cells
Part 4: working with multiple stakeholders
Part 5: traceability
Part 7: summing up the strategies
Part 8: the benefits of a strategic approach
Heidi Hagen is the Chief Strategy Officer and a Co-founder of Vineti. Over the course of her career, she has overseen the operations and delivery for more than 100,000 doses of cell therapy. Christophe Suchet is the Chief Product and Compliance Officer of Vineti, and previously led IT systems for cell therapy pioneer Kite Pharma. If you’d like to see how Vineti’s Personalized Therapy Management (PTM) platform can help you solve your advanced therapy data challenges, please contact us to schedule a demo..