A Development Roadmap for Combination Products

Comparing progress against a set of criteria such as Design for Lean Six Sigma ensures that the somewhat synchronous development philosophies of devices and drugs are being considered appropriately.

By Bikash Chatterjee, Pharmatech Associates, Inc.

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Over the last decade, we have seen a growing number of innovative products combining the benefits of technology with drug and or biologic therapies. Combination products can range from the relatively simple, such as pre-filled syringes or injector pens, to highly complex systems (e.g., drug-eluting cardiac stents).

In 2003, Johnson & Johnson launched the first drug-eluting stent, thereby challenging the industry and FDA to establish a model for novel products balancing business and public-safety requirements. Since then, we have seen an influx of new and innovative therapies pushing the boundaries of the therapeutic and regulatory landscapes. Combination products seek to leverage the best of the device performance world in an effort to maximize therapeutic performance.

With this quest comes a new challenge. The development philosophies for devices and drugs are not the same, and marrying the two technologies carries its own unique set of challenges. In a marketplace in which Time-to-Market (TTM) defines what we do on a daily basis, the business goal often shifts to meeting deadlines as opposed to assuring the quality of the task. This represents a problem for all regulated systems but the impact of cutting corners in a combination product can be profound, both to the customer and the organization.

Execution must include a measurement of capability as part of the completion assessment. How do we meet the conflicting demands of TTM, cost and completeness? One solution is to borrow from proven operational excellence methodologies that have demonstrated their ability to optimize new product development effectively within both the drug and device industry.

This article discusses the technical considerations in developing a combination product and proposes a technology roadmap, leveraging the principles of Six Sigma and Lean Manufacturing for integrating the technical and quality elements in the development of combination products in the U.S.

Figure 1. Software, Device and Drug Lifecycles

Collision of Lifecycles

From a pure regulatory perspective, the challenge in developing a combination product is multifaceted. Depending on the product, there is likely to be combined oversight from both CDRH and CDER or CBER. This level of complexity raises the stakes during the product development lifecycle, because it potentially brings together three similar but not identical development philosophies. The basic elements of each lifecycle are shown in Figure 1 (above).

Embedded within each lifecycle are the fundamental quality elements necessary to ensure that the product performs predictably. The basic expectations are defined in 21CFR 820 and 21CFR 210/211. Add to this the requirements of ICH Q2, Q7, Q8, Q9, Q10 and ISO 2000/CE marking, and the potential for misstep is tremendous.

Successful programs integrate downstream considerations as early in the product-development lifecycle as is possible. Integrating business requirements in the concept phase can save an organization years of development time and millions of dollars, simply by not chasing a product design that is either not viable or not a frank commercial success.

Lean Six Sigma and the Development Roadmap

One key difference in developing a combination product is the necessary mindset shift from two individual components (device and drug) to a focus on combined performance. Applying a Six Sigma roadmap provides a structured framework to identify the key process input variables that control overall product performance, not just device or drug performance. The Six Sigma roadmap uses a fivephase project management process to drive improvement: Define, Measure, Analyze, Improve and Control (DMAIC). Step by step, each phase in the DMAIC process guides the members of the development team through the project in a way that provides the right data and best process understanding. Managing the project in this way allows the business to make the best possible decisions with the available data and resources. The concept behind the process is as follows:

  1. Define: Clearly define the problem and relate it to the customer’s needs.
  2. Measure: Measure what is key to the customer and know that the measure is accurate.
  3. Analyze: Search for the root causes and identify the most likely causes.
  4. Improve: Determine the root causes and establish methods to control them.
  5. Control: Monitor and make sure the problem does not come back.

A set of deliverables must be completed for each DMAIC phase to ensure all project requirements are met. As we evaluate applying Six Sigma principles to the development of a combination product, there are several models to consider. The classic Six Sigma DMAIC model provides a good framework for objective scientific inquiry, typically used to improve existing processes (and products). However, a Design for Lean Six Sigma (DFLSS) approach, with its focus on the development of new products and processes, would be more appropriate for this application.

DFLSS models provide a structured, phased approach to the design of a product, process or service, with Six Sigma Quality (target of 3.4 defects per million opportunities) and efficiency as key design criteria. Also, it’s easy to include risk management in the model, as Failure Modes and Effects Analysis (FMEA) is a standard DFLSS tool.

This DFLSS tollgate approach to product development has the additional advantage of providing a set of success criteria for the completion of key milestones within each phase of the process (so that the “gate” can be closed). Comparing progress against such criteria provides objective evidence of incremental team success (that can be celebrated and communicated to the rest of the organization) and ensures that the somewhat asynchronous development philosophies of devices and drugs are being considered appropriately. Possible DFLSS frameworks include the DMADV, IDOV and DCOV models. These are shown in Figure 2 (p. 36).

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