An engineering approach to derisking R&D for novel drug modalities

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Drug development is, generally, an expensive proposition: the total cost of successfully developing a pharmaceutical drug now exceeds that of a signature national infrastructure project. Indeed, it takes approximately $2.6 billion to bring a single drug to market, excluding any post-approval R&D efforts.1 For reference, it took $1.5 billion to build the world’s tallest building, the Burj Khalifa in Dubai, in 2010.2

Not only are the economic stakes in drug development alarmingly high, but also these major investment decisions must be made in the face of considerable uncertainty. Fundamental questions about the etiology of the disease being studied, as well as the mechanism of the molecule being tested, are often unanswered at the early stages of drug development—and sometimes this remains the case all the way through to approval. And this does not even account for the typical operational factors that could jeopardize the success or timeliness of a program, such as supply chain or vendor management considerations.

The challenges of drug development are particularly acute for innovative modalities

For novel modalities, these challenges are often exacerbated. There remain significant unknowns around the platform itself (such as potential for off-target effects with CRISPR mediated gene therapy) as well as novel supply chain challenges (such as complex supply chain for autologous CAR T-cell therapies).

Furthermore, in today’s increasingly competitive environment, the bar for what is considered success for a clinical development program has been elevated from simply approval to speedy approval. Being first to market has been known to provide a sustained market share benefit to a product, beyond just the benefit of providing additional time on the market with exclusivity.

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Given all of these challenges (Exhibit 1), executives in pharmaceutical R&D groups—in particular those working on innovative therapies—are under enormous pressure to make good decisions that will deliver successful and timely approvals for the programs they are overseeing as well as identifying and rapidly killing off discovery and development projects that are destined to ultimately fail.

1
A changing landscape in pharma research and development poses growing challenges.

An approach to derisk drug development: ‘Failure modes analysis’

One approach that has its origins in the field of engineering and is under-utilized in drug development is known as “failure modes analysis.” This involves undertaking a systemic and holistic risk assessment across the four key success factors, and cataloging all the ways a program could fail, even at the earliest stages of development (Exhibit 2). For risks (or failure modes) that are deemed to have a significant enough likelihood and impact, abatement plans can be put in place preemptively to improve the change success of the program.

2
Risk assessments for clinical stage assets should be comprehensive.

While this approach is applicable—and can provide considerable value—to any drug development program, they are particularly effective in situations where there are more unknowns, or existing teams are less familiar with the modality, asset, or disease.

Novel modalities, or assets recently obtained through M&A, are prime examples of this.

R&D in the ‘age of agile’

R&D in the ‘age of agile’

We have been deploying this tool for several years to assist biotech and pharma companies in derisking clinical programs, and have refined our toolkit to one that includes four elements:

  • Framework for risk ideation that enables uncovering risks across the full range of functions and activities that could impact a program
  • Multidisciplinary workshop–based approach that brings together people from across silos in the organization, brings them up to speed with a common fact base on the program, and primes them to brainstorm
  • Scoring methodology to prioritize risks that are uncovered, so that the team knows what could really move the needle and where to focus efforts
  • Structured follow-through to build abatement plans with relevant functional leaders for the top risks, as well as escalate the right items to senior management as necessary

What we have learned by applying our risk assessment methodology

We have now applied this methodology across more than 20 assets across all stages of clinical development, and several common themes emerge:

  • The voice from the frontlines often does not find its way to the top. Invariably, critical issues are not wholly unknown to the organization, but the magnitude of their implications has not fully been escalated to the appropriate level for action to be taken.
  • Very few people in the organization have the full picture. Especially in larger organizations with functional leads split across a range of assets, it is the rare individual with a truly comprehensive view across all aspects of an asset that can think through the relevant interdependencies in advance.
  • Tremendous value in an open and multidisciplinary approach. The classic functional org structure for pharma R&D groups has many advantages but can sometimes lead to siloed thinking. Bringing people together from across functions can create magic.
  • Chemistry, manufacturing, controls, and intellectual property are often neglected till the last moment. Perhaps due to the specialized skill sets and knowledge involved in these functions, we find that critical risks in these functions are often missed by broader teams.
  • Commercial input is often provided too late in the process. Almost every organization we worked with could have benefited from targeted commercial input earlier in the process. This is increasingly true in a world where approval is the minimum bar, but differentiation is the key to unlock value.

Pharmaceutical R&D executives have a great many challenges ahead of them as they seek to bring new innovations quickly to market. Executives working on innovative modalities arguably have more challenges than most. Especially in such situations—with the broad range of unknowns, high development cost, and often challenging supply chains—applying a failure modes analysis can quickly take some unnecessary risk out of a development program.

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