Transformation Challenges

Finally, we explore the major transformational challenges (behavioral, technological, regulatory, etc.) that continuous-based manufacturing and supply models need to overcome. Four key areas are identified regarding transformation to continuous processing, namely:

  1. Fostering a multi-disciplinary approach across technical and manufacturing disciplines, including requirement for better connectivity between discovery, development, and manufacturing organizations.
  2. Technology integration across Pharma and Bio-Pharma supply chains including diagnostics to enable patient centric supply chains.
  3. Derisking investment decisions and overcoming barriers.
  4. The role of policy across pharma supply chains.

These are explored with recommendations for industry, supply chain practitioners, academia, and regulators and where appropriate, comments from the literature included.


Fostering a Multi-Disciplinary Approach across Technical and Manufacturing Disciplines

Changing the Mind-Set

Changing the mind-set of industrial and institutional professionals, such as regulators, manufacturers, and process engineers, to continuous processing and a retraining of staff will be essential for achieving substantial transformation. At a technical level, this will require developing better capabilities both in continuous synthesis and in the design of continuous drug product manufacture, right through to downstream pack and distribute technologies that can accommodate product variety and flexibility.


Transforming Control Regimes

Sampling and testing aliquots of material to confirm quality and manual feedback loops in various Quality organization setups will not be possible nor adequate in continuous manufacturing. If the continuous processing needs the process dynamics to be controlled automatically, as in the flight dynamics of modern flight control systems, the oversight in the field will not be the paper screening of Food and Drug Administration's field inspectors but the approval of the control system and the assurance that the operational parameters are as intended. The quality evidence provided in today's paradigm is either based on manual or simple computerized systems because the integration across systems is according to discipline not according to products. For example: an analytical LIMS system manages all chromatographic data within an organization. The complexity per data entry (meaning per sample) is simple, but because the integration is vertical along all such procedures within an organization, the sheer amount of similar data is overwhelming and here the complexity starts (operator, equipment tag, reagents, injections, sample number, etc.). In the laser printer case, an integrated Photodiode can measure the deposition density of the toner in-line, its data is only used to control this particular printer at the given optimal time-point and guarantees the optimal quality of the printout. Occasional verification is sufficient to verify proper function of all systems and the self-surveillance of the system can help to manage operation.


Tackling Organizational Inertia

The current modalities within many large firms in established industries, particularly in those that are highly regulated and technology intense, has involved "committee-based" decision making, often through multi-layer matrix organizations. It has been suggested that this has driven a risk avoidance and tick-boxing culture at a functional level, which promotes incremental innovation despite long product life cycles, at the expense of genuine cross-functional radical innovation. Regulatory contexts inadvertently lock-in these behaviors and preference to established processes. However, in some organizations, we are now witnessing the creation of "autonomous multifunctional teams," with substantially more devolved responsibilities, to drive more radical transformations - teams that are given the resources, timeframes, and mandates to deliver. Although these are relatively new developments, examples from both the aerospace and pharmaceutical sectors, who both exhibit similar organizational characteristics, partly driven by their industry structures, product architectures, and regulatory frameworks, suggest the "continuous processing" models will require such multi-functional teams to develop specific supply chain models. These multi-functional teams have the opportunity to enhance connectivity between discovery, development, and manufacturing organizations, particularly important in large pharma. In addressing these organizational silos, which are often functional and discipline based, we can encourage the breakdown of unhealthy sub-cultures (that can promote incrementalism and silo behaviors), to take on more challenging cross-functional targets. This will involve developing a new crop of technically based leaders, working within both their own organizations and external parties. Reconstructing industrial "systems" will involve new partnering models with external players focused on delivery against system outcomes. Industry evolution more broadly may result in refocusing industrial activity of the main players on specific elements of the value chain; restructuring activities on value adding activities, perhaps involving mergers and acquisition of firms that operate across the supply chain where vertical integration is critical to product/service delivery.

Interestingly, as current processes and trends move to demands for an ever growing granularity of control per individual control event, the increasing complexity of products and technologies will challenge the existing approach of batch-lot control with its technical limitations, driving firms and regulatory agencies to a system change for the next generation of products. This change in paradigm emerges surprisingly perhaps from the combination for more assurance within the context of increasing complexity, requiring more "systems" cross-functional approaches to quality assurance and new product introduction.

The organizational issues raised here are further explored in the white paper by Krumme et al.


Technology Integration across Pharma/Bio-Pharma Supply Chains Including Diagnostics to Enable Patient Centric Supply Chains

Integrated product and product-service replenishment models, driven for example by remote diagnostics or near real-time demand signals, will require technology advances that can enable/drive more patient (or institutional user) centric supply/demand models, reducing the reliance on intermediaries. The product categories, patient populations or therapy areas where tightly coupled supply chains might emerge will inform the technology requirements across the product-process-supply domains. Key criteria will be product volume and variety, volume uncertainty and lead-time requirements.

The emergence of new supply models will require policy and regulatory advances that support more direct supplies.

Within the process technology choices during various stages of industry transition, the hybrid batch/continuous models that might progressively support change may be a key consideration in the "road map" to continuous manufacturing and supply. These industrial transition points will themselves have critical dependencies on a number of new technologies, such as better analytical systems, new catalysts, new enzymes, novel control systems, and so on, which in their various combinations will be required to drive success.

At the molecular level, these developments will not only require a rethinking of current molecular discovery to scale up processes, but also require engineers, chemists, and software designers to work together in new ways. Conceptually, organic chemists often work out how to make their target molecule by working backward and reducing the complex molecule to simpler ones step by step on paper, only to reverse the process in the laboratory and build the molecule up. An example of such multi-disciplinary activity is the potential of molecular discovery, scale-up, and crystallization - these processes are being pioneered in the Cronin lab to try and develop this chemistry into "reactionware". This is not so different from the development of continuous processes from batch to flow. The difference with "reactionware" is that the scaling of the system is much easier and faster because of the ability to rapidly prototype the flow systems using plug and play plastic modules. Of course, we propose going several steps further and using standard modules that can do advanced operations such as separations, crystallizations, and forming composite or formulated products. If the units are cheap, scale up via reactor numbering up is potentially transformative in terms of cost, time, and configurability and mobility.


Derisking Investment Decisions and Overcoming Barriers

Managing the uncertainty and risk of novel processing routes in Clinical and Commercial supply chains will be critical within any industry adoption of continuous technologies. This calls for industry wide pre-competitive activities to derisk projects and build industry capabilities together with institutional players and regulators.

Another key requirement is lowering barriers to entry - through shared facilities and infrastructure, PAT capability advances at sector level that provide product-process quality assurance, and the proactive development of appropriate regulatory contexts.

Any new technology carries opportunities and risks. In the originator's pharmaceutical business, the main risk is the approval of the compound, driven by the success of the clinical program and the convincing power of the dossier. For a single compound, this is a complex function of a variety of factors, some of which are better manageable than others. The performance and properties of the molecule on the receptor is one element, the biopharmaceutical adequacy of the drug product to the kinetic properties at the receptor and the route to get there is the other and at the end of the day, the feasibility and robustness of distinct process trains for a particular drug product design is of the essence. The magnitude of the risks is typically much larger on the clinical side for originators and hence the focus on secondary risks needs to be minimized. This can be accomplished by a variety of approaches using:

  • Technology platforms that are applicable to multiple projects
  • New technologies only late in the clinical programs or as life-cycle management tools
  • New technologies in a dedicated spin-off that offers the technology for the industry as a whole and hence spreads the risks across multiple products and companies

To value the opportunity and risks adequately, one should not solely consider the technology platform and the success of a specific product or clinical performance, in fact they mostly have nothing to do with each other, other than the fact that a platform has been picked for a particular program. Instead, it is essential to understand what a particular platform delivers in terms of functionality, cost, timelines, and robustness, and quantify those factors. For continuous processing, this reduces the risk to the pure technical risk and other aspects that drive in the long run the success of the process technology on its real merits.


The Role of Policy and Regulatory Regimes across Pharma Supply Chains

Societal expectations, in developed and emerging markets, will increasingly demand more affordable and/or specialized products available to those who need them.

Institutional pressures on affordability and the demographic impact on national health budgets are expected to drive more efficient supply chains and business models that no longer tolerate the inventory buffers of today. However, the transition to more efficient supply models will require institutional partnerships (government, regulators, and research bodies) with technology and industrial players.

From a regulatory perspective, we anticipate process engineering, analytical methods such as spectroscopy, and data analysis and statistics become progressively more important. Real time access to data and data analysis become the norm, with large-scale sampling and dynamic control methods influencing the regulatory paradigm.