In this installment of QbDVision’s Knowledge Management Lab, we discuss how deploying a Digital CMC platform within your organization can enable digital tech transfer in an industry still using document-based transfers as the primary mode of operation.
Question: Can a Digital CMC platform reduce tech transfer times from months to weeks and dramatically lower costs while reducing risk and improving the likelihood of success?
The analysis in this whitepaper demonstrates that the answer is, in fact, YES. Digital CMC reimagines data management where information is tracked in structured repositories at a more granular level. In this structured approach, each element of data is a node and the nodes can be connected to create a multidimensional data set that can be easily searched and analyzed. These structured repositories are based on the vertical integration of the knowledge base where requirements (patient, product, and process) are integrated with risk assessment tools, manufacturing data and analytics, and the tangible assets of production. All of these dimensions of data converge to define and justify the specific control strategies for the manufacturing process.
Once CMC information is digitized, it can be transferred instantaneously from the sending site by creating a digital representation of the manufacturing process at the receiving site. With two digital datasets, the tasks of gap and risk assessment related to the transfer are dramatically streamlined. The sending and receiving site processes can be compared on an element-by-element basis with differences or changes easily identified, visualized, and assessed for risk. The traditional tech transfer time can be reduced from months to weeks for sourcing, planning, and execution activities with projected cost savings ranging from 77% to 83% due to time and personnel savings alone.
Digital CMC platforms like QbDVision can enable data exchange more securely than trading PDFs via email accounts. For transfers between organizations in different countries, digital tech transfer ensures information is standardized and consistent. Finally, digital tech transfer based on structured data frameworks ensures that the benefits extend beyond the transfer project into preparations for commercial manufacturing, continuous process verification and post-approval change management.
Why We Need Digital CMC
Technology transfer is a constant logistical challenge for pharmaceutical and biotech companies throughout the development lifecycle. Many companies have virtualized their operations over the past few decades leading to more frequent transfers. In spite of the increased transfer volume, the industry primarily uses the same antiquated approaches of document-based transfers between teams, sites, and organizations.
Traditional drug development programs have seen timelines primarily gated by clinical trial studies. This has, in theory, given the CMC and manufacturing teams “plenty of time” to execute tech transfers. However, in practice, “delay and defer” is the rule, and tech transfers generally must be delivered under compressed timelines with poor advanced planning and execution.
The aggressive and unprecedented development timelines of COVID-19 vaccines have exposed many of these tech transfer challenges and inefficiencies within the industry as never before. Clinical trial studies advanced at a pace not historically seen and were no longer the gating workstream, putting manufacturing squarely on the critical path. The additional challenge of making the vaccine in volumes – also not previously imagined – required far more transfers than normal, making traditional tech transfer approaches inefficient and unable to adequately meet these demands. There is clearly now an expectation among multiple stakeholders that manufacturing development should keep pace with clinical science. But, how do we keep tech transfer from being the bottleneck in the development of future, innovative therapies? Deploy Digital CMC.
Who Has My Binder?
According to McKinsey & Company, A typical tech transfer project takes 24 to 30 months and includes a number of phases such as Sourcing, Planning, Technical Transfer, Regulatory Preparation and Submission, and more. Each of these phases often involve large numbers of specialized personnel, and the transfer of information is primarily document-based. This journey consists of several physical workstreams, including those that acquire, install and test equipment and processes. The opportunity for improvement comes not from improving the physical aspects of a transfer, but from the large volume of reports, data tables, specifications, etc. that are often sent via email from site to site with little thought given to workflow, collaboration, change management, or future use of the data. Cloud-based collaboration tools, such as SharePoint, have yielded incremental improvements at best with information still maintained in documents in complex folder structures that are difficult to navigate. These documents, electronic or paper and regardless of format (e.g. Word, PDF, etc.), are unstructured narratives of information with each document containing lots of key individual pieces of information and data. These documents have to be combed to extract the key technical information regarding product and process requirements, risks, analytical methods, and much more. Making matters worse, all of this information is again summarized into a new set of tech transfer documents describing gap and risk assessments, risk mitigation activities, and various plans.
So, the whole process accomplishes transforming one set of documents into another set of documents and the problem remains the same; information is still buried in documents. Further, a key assumption in the document-centric approach is that everything is known upfront, written down, and nothing will change at the sending site. This is rarely seen in practice as the processes at the sending site do not necessarily remain static.
The logical false corollary is that the only thing needed to improve tech transfer is simply writing better documents or worse, better templates. When in fact, this document-centered approach is a key contributor to the extended time and costs of tech transfers.
Structuring CMC Data is the Key
Instead of storing information in documents, what if you could store the key CMC information at a more granular level where each element of data is a node and each node can be connected to other nodes? Now, you have a multi-dimensional data set aligned to commercialization phases that can be quickly searched to find a node of interest. AND, you can immediately see how this node relates to other nodes in the data set. If this data set represents all of the information related to your manufacturing process and control strategy, then it is all easily accessible and searchable without having to go through the process of extracting it from volumes of documents.
Making CMC data more atomic in this fashion goes a long way toward addressing the challenges of tech transfer. But, it doesn’t go all the way. Ensuring that this data is structured with the appropriate context within a product-centric model optimized for commercialization and post-approval operations is critical. A rational structure overlaying granular, connected elements of data creates a vertically integrated knowledge base where each node of information can be displayed in multiple dimensions of context. For pharmaceutical and biotech products, the International Conference on Harmonization (ICH) has provided an architecture that is endorsed by regulatory agencies and the industry globally. The figure below illustrates a vertically integrated information structure specific to drug development where requirements form the foundation of the Digital CMC knowledge base, and context builds over time to provide a complete story of control with appropriate justification. This structure also aligns nicely with the requirements of pharmaceutical development as outlined in ICH guidelines Q8 to Q12.
Vertically integrated knowledge management structure for a Digital CMC platform.
Stage 1 of this framework starts with the requirements-based structure where patient, product, and process requirements can all be defined and tracked individually with all their associated information.
Stage 2 of vertical integration brings the tools of quality risk management (QRM) as described in ICH Q9 and Q10, into the framework. With QRM integration, each requirement can be separately assessed for risk. Furthermore, process requirements can be digitally linked to product requirements; and product requirements can be linked back to patient safety/efficacy attributes. This creates risk-based traceability as recommended throughout ICH Q8 – Q10.
Stage 3 integrates raw material and manufacturing data into the multidimensional data set. This data can be analyzed to identify trends and assess process capabilities. The integration of process data drives a key feedback loop enabling a consistent focus on those areas which need the greatest attention.
Stage 4 folds in the tangible assets of production, specifically raw materials, components, and equipment. Visibility into these dimensions is often limited and not easily accessible. By tracking these assets with respect to qualification, performance, and supplier risk, a comprehensive view of the entire production process comes into focus (ICH Q10).
Stage 5 uses all of the other stages to justify the control strategies identified for the validated process. With the strong, foundational knowledge base represented by Stages 1-4, it becomes easier to define a robust control strategy and defend that strategy going forward. This Digital CMC construct also simplifies the management of the inevitable process changes and impact assessments post-approval.
We have taken data from its aggregated, unstructured form in documents, reports, spreadsheets, etc., and converted it into structured elements that are contextualized to produce a comprehensive Digital CMC dataset. Each data element is easily accessible. Process Relationships and interdependencies jump off the page, and true process understanding is achieved… Huzzah!
Digital CMC → Digital Tech Transfer
Structured data is no longer optional. Traditional approaches to process development, manufacturing, and validation for a new drug product can take as long as 7-8 years to complete. During this period of complex activities, vast amounts of data are generated that are core to product formulation, manufacturing process, recipes, materials, equipment, and more. It is highly likely that, at some point in the history of the development or manufacturing program, a tech transfer will need to take place from one site to another site. This could be to move to an increased scale of production, expand existing capacity, or bring manufacturing back in-house. Although tech transfers can be accomplished using traditional, document-based approaches, more efficient transfers can be greatly facilitated with modern, structured data frameworks.
How does the dynamic change if this data is being captured over time in a Digital CMC dataset? If the evolution of your manufacturing process is captured digitally within an atomic structure, the transfer begins with a click of a button. INITIATE.
Digital tech transfer is initiated when the entire sending site process description is cloned into a new process structure for the receiving site; unit operations, steps, materials, equipment, process parameters, material attributes, in-process controls, all of it. Further, each element of the sending and receiving sites automatically linked together so they may be compared throughout the transfer process. No digging through documents and reports to find the specifications, descriptions, and justifications.
Next Step: MODIFY. After cloning, individual aspects of the cloned process can be modified to represent the process for the new scale or site. Using a bigger bioreactor from a different supplier? Find it quickly within the structure and edit it with the new information.
Next Step: GAP ASSESSMENT. You now have two Digital CMC datasets that can be compared on a node-by-node basis. Another click of the button allows you to see this information side-by-side to quickly identify gaps and differences and drill down further into the datasets to further investigate these when needed.
Next Step: RISK ASSESSMENT. Having identified the gaps and differences between the sending site and the receiving site, which ones matter? Which ones represent the greatest risk to the successful transfer of the process. With gap assessment at the node level, each node pair can be separately assessed for risk when risk assessment capability is already integrated into the Digital CMC knowledge structure.
Next Step: RISK MITIGATION. With the risks identified, you can develop a focused technology transfer plan. Begin the work to mitigate the risk and learn how the receiving site process performs relative to the sending site process. Characterization studies, supply chain management, quality management, etc. will all need to be activated to confirm the new process meets the required specifications and to provide the justifications for any regulatory approvals or notifications related to the transfer.
Next Step: EXECUTE. Finalize by evaluating operational readiness, qualifying the process performance at the new site, and completing a final review.
The outcome of a digital transfer strategy is a complete set of process data for each sending/receiving site pair. The data elements are always current because they are no longer tied to documents. The endless document routing has stopped. Team collaboration is enabled on a Digital CMC platform and tech transfer reports that take months to create and review are now updated in real-time and ready at the click of a button.
Document-based tech transfer gets bogged down at each step and begets more transfer documents and reports that compound the problem when it is time to prepare regulatory submissions. Now imagine doing this for multiple sites for just one product. Stop the insanity! Leverage the power of Digital CMC!
The ROI of Digital Tech Transfer
Switching to a Digital CMC platform will have significant positive benefits beyond reducing the frustration of the tech transfer exercise. Digitalization coupled with a structure that aligns to commercialization phases, activities, and information value brings significant efficiencies lowering the overall costs of tech transfer and getting therapies and vaccines to the market faster. But first, let’s look at the current state of the industry.
A 2020 McKinsey report, cites the average tech transfer ranging from 24 to 30 months broken down by the following stages and standard time frames for each stage:
ISPE’s good practice guides on knowledge management and technology transfer provide additional detail around the planning and technical transfer stages where the activities are broken down into the following stages:
- Form Technology Transfer (TT) team and develop charter
- Consolidate knowledge for transfer
- Agree to high level TT proposal
- Identify Risks, Conduct Risk Assessments, and develop TT plan
- Operational Readiness
- Process (Procedure) Qualification
- Finalize technology transfer and perform review
Putting these analyses together, we see that over half of all tech transfer time spent is attributable to planning and executing the transfer, including the work to consolidate and organize the critical product information and evaluate the corresponding risks. These extended time frames are in large part due to information management challenges resulting from the document-centric approach. The McKinsey report goes on to cite the resources required for a typical tech transfer for a vaccine candidate. The assumptions and associated costs for the sourcing, planning, and technical transfer phases are summarized in the table below.
Based on their estimates and a 28-month tech transfer, the cost can range from $38M to $389M in personnel costs alone. Let’s assume that the introduction of a Digital CMC platform to enable digital tech transfer reduces the time frame of 16 months for the first three phases to 16 weeks. Let’s also assume that the number of FTE’s can be reduced by 30% because full parallel teams working to consolidate knowledge for each site are not needed. The table below summarizes the costs required for the typical digital tech transfer associated with these phases of the process as compared to the traditional approach.
The deployment of software solutions focused on commercialization and the product life cycle makes digital tech transfer possible, and the cost reductions are dramatic. One may argue that these assumptions are not realistic, and it is not possible to reduce a 16-month cycle to 16 weeks. But the cited McKinsey report is arguing that to get ahead of the COVID-19 pandemic and similar situations in the future, there is no choice and digital technologies and automation are the only way to do it.
Of course, this analysis only looks at time and labor costs. The reality is that the analysis is more complicated because of the additional risks associated with delays due to poor planning, poor understanding of the process or analytical methods, and material/CAPEX costs related to additional work because of manufacturing deviations or qualification failures at the receiving site. A highly structured, digital approach to tech transfer can reduce the challenges and associated costs with each of these scenarios further improving the ROI of digital tech transfer.
From Tech Transfer to Tech Sharing
The lexicon in the industry has always been one of “transferring” technology between sites or between organizations. But is this an artifact of the document-based approach where binders of documents were literally handed over from one team to another? It falsely assumes that things can be “frozen” and ready for transfer at the time of initiation and is blind to the notion that information can be linked together and kept in a connected context throughout the life of a transfer.
With the advent of digital, cloud-based solutions that teams from both the sending and receiving sites can access, perhaps a better term is “technology sharing”. What would be the impact if teams from both sites could share and collaborate within a single cloud-based environment? Can Technology Sharing be performed on a rolling basis as a way to further reduce the pressure on short timelines? What happens when tech transfers are happening simultaneously between three or four different organizations/sites? A single, collaborative environment could allow for all of these activities to take place in parallel. More importantly, cloud-based, Digital CMC platforms like QbDVision can enable data exchange more securely than trading PDFs via email accounts. For transfers between organizations in different countries, digital tech transfer ensures information is standardized and consistent. Finally, digital tech transfer based on structured data frameworks ensures that the benefits extend beyond the transfer project into preparations for commercial manufacturing, continuous process verification, and post-approval change management.
A Digital CMC platform, like QbDVision, opens up a world of possibilities for dramatic improvements in efficiency. With QbDVision now deployed within organizations to enable collaborative Technology Assessment and Sharing under some very challenging circumstances, we look forward to sharing the results (pun intended), when possible, via case studies in future installments of the Knowledge Management Lab.
QbDVision is a breakthrough CMC management platform for biopharma organizations. It’s the first and only solution that enables teams to transform fragmented data and siloed knowledge into true process intelligence: the smart, holistic guidance you need to accelerate new products to patients.
Looking for more on tech transfer – watch our on demand webinar centered around Streamlined Tech Transfer.
- You know where to find everything you need to streamline product development: in a structured framework that helps your teams work smarter, faster, and more collaboratively than ever.
- You know how to build robust, agile processes that your teams fully understand and control.
- You know why every input produces its output, and where they may lead to product and process risks.
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