Operational Efficiency in Clinical Research: The Power of Systems Thinking

This article is the start of a movement. But before we dive in, here a short intro:

Hey, I'm Zina Sarif, CEO @ Yendou , a data and workflow automation platform designed for ClinOps teams. Each week, I chat with executives from the Life Sciences Industry to discuss the game of clinical trials, the rising costs, the urge to innovate, the pressure for speed, and how to navigate operational inefficiencies on the road to commercialization. This newsletter is my response to all the requests to share my thoughts publicly. To receive the issue in your mailbox ?? subscribe here.

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There was a man named Paul Strassmann. He served as the former Chief Information Officer at the Pentagon, and prior to taking up that role, he authored a book titled "The Business Value of Computers.”*

I would have recommended reading his book, but unfortunately, it is no longer in print, and Paul is no longer with us. Otherwise, I would have harassed him into publishing another edition.

In his book, he analyzed IT R&D spending of successful companies and non-successful companies and arrived at the realization that both allocated an equal 2% of their budgets to IT R&D.

The difference was that non-successful companies invested the 2% in management productivity, whereas successful companies directed it towards operational productivity.

Management Productivity vs. Operational Productivity:

Management productivity tools address behaviors of a system, whereas operational productivity tools tackle systems.

Robert Pirsig once said, “If a factory is torn down but the rationality which produced it is left standing, then the rationality will simply produce another factory. If a revolution destroys a government, but the systemic patterns of thought that produced that government are left intact, then those patterns will repeat themselves.”

The factory is a behavior. Its rationality is a system.

The government is a behavior. The systemic patterns of thought that produced it are the system.

Understanding Clinical Trials and Systemic Approach:

In the realm of clinical research, we must ask ourselves: what are the behaviors and what constitutes the system? As of today, every vendor in the clinical trial space, except for tech-enabled CROs, is focused on fixing behaviors rather than addressing the system. By doing so, we might make slight progress, but we will inevitably escalate the R&D costs of late-stage drug development. Then data shows,

solutions that solely fix the behavior of a system tend to create new problems.

This has occurred before. Technology companies faced this challenge 20 years ago, and it is happening once again to industries that were slow to adopt technological advancements, like Drug development companies. This shift has been accelerated by the pandemic and the growing influence of clinical trial technologies.

Learning from History and Challenges in the 2000s:

George Santayana once remarked, “Those who cannot remember the past are condemned to repeat it.”

But let us not be condemn again. My role is to share with you my learnings, so we have the opportunity to learn and gain insight from history's lessons.

The early 2000s marked a difficult period for enterprise businesses. Executive boards assessed the outcomes of years of investment in computer technology, aimed at digitizing their organizations and gaining a competitive edge for quicker revenue generation. Ultimately, they discovered that there is no relation between spending on computers, profits, and productivity.

Let me repeat:

The correlation between computer spending, profits, and productivity is not straightforward.

It's not about how much you spend; it's about how you allocate those funds.

Behavior maintenance (managment productivity) consumes an Enterprise budget, while restructuring systems (operational management) consolidate Enterprise’ digital transformation.

So, how does this translate to late stage drug development?

Looking at Clinical Operation through the System Lens:

Currently, an estimated 94% of clinical trials experience delays.

"What causes clinical trial delays?" I ask pharma and CRO executives, directors, and project leads. "low patient recruitment," "long contracting timelines," and "non-collaborative stakeholders." They say

"What causes slow patient recruitment?" I ask again, this time including Investigators and study coordinators.

"Strict eligibility criteria of the study protocol" and "incorrect site selection." They reply

"What causes long contracting timelines?" I inquire.

"Non-collaborative sponsor/CRA/Site…" and "slow feedback loop." They answer.

The answer to "what causes clinical trial delays?" Clearly lies within the clinical trial itself.

The dynamics between sponsors and sites might increase or decrease the delay (the behavior) that is latent within the structure of the clinical trial.

That is the central insight of system theory.

To cite Meadows: "Once we see the relationship between structure and behavior, we can begin to understand how systems work, what makes them produce poor results, and how to shift them into better behavioral patterns."

We live in an era of rapid technological change, accompanied by increased complexity. The pandemic exposed the limitations of a disconnected clinical research landscape and emphasized the importance of digitalization. However, the primary challenge we face, namely the persistent decline of R&D productivity, continues to persist.

If we took the time to analyze IT R&D investments in late stage Drug Development, we might arrive at the same conclusion that IBM reached in the early 2000s: there's no direct correlation between software/Hardware spending, profits, and productivity.

I firmly believe that reevaluating our approach to clinical trials will help us to manage, adapt, and recognize the diverse array of choices before us. Viewing clinical trial and all stakeholders involved as elements within the larger system of clinical operations will enable us to identify the causes of problems and see new opportunities.

So, what is a system?

Understanding Systems:

As defined by Meadows, “A system is a set of things - people, cells, molecules, or whatever - interconnected in such a way that they produce their own patterns of behavior over time. The system might be buffeted, constricted, triggered, or driven by outside forces. But the system's responses to these forces are characteristic of itself, and that response is seldom simple in the real world.”

When it comes to late-stage drug development, the system itself triggers its behaviors! While external events can unleash these behaviors, the same events applied to a different system will yield different outcomes.

Consider for a moment the implications of this idea:

• Contract Research Organizations (CROs) rarely cause delays in a sponsor's clinical pipeline delivery. Although they operate with a business model centered on billable hours, sponsors are the ones responsible for their pipeline delays due to their business policies and their decision to entrust their R&D goals to CROs with a misaligned business model.
• Patients don't spontaneously drop out of clinical studies. Instead, the conditions of the clinical trial are set in a way that enables such behaviors to arise.
• Research sites are not solely responsible for variations in patient recruitment rates. Fluctuations are inherent in the structure of clinical trial allocation/site selection in relation to disease burden distribution and access to care.
• Pharmaceutical companies alone are not solely accountable for the rising cost of therapeutics in high-income countries. Global price increases and increased healthcare spending result from a complex interplay of disease burden, pricing, the investment and regulation policies in these nations, which had neglected research infrastructure and made the economy vulnerable to drug supply interruptions.

The issue with the statements above is they challenge our ingrained tendency for logical reduction as a form of rational analysis. The simplistic understanding of problem-solving as the ability to trace a direct path from cause to effect and the urge to control the world around us and to look at things in small pieces, and fix them one by one.

Impact of Reductionism in Clinical Trials:

The issue with reductionism tho, is that complex problems are often integrated into larger systems, and the solution of logical reduction will create further problems.

As an example here, in late-stage drug development, we can see how the reductionism of logic in simplifying the problems of clinical trials leads to a much bigger issue: An over-saturation of vendor tools involved in clinical studies and the consequential revolt of research sites against a sponsor-imposed digital administrative burden. Thus, impacting Sponsor-Sites relationships and furthering the decrease of R&D productivity.

An EDC, eConsent, ePRO, RAVE, and eImaging platforms might address the issue of accessing anonymized source data remotely.

However, slow patient enrollment, a high number of protocol amendments, and long contracting timelines, for example, persist despite the analytical ability and technical brilliance that have been directed towards solving clinical trials since the pandemic boom. No one deliberately creates those problems, and no one wants them to persist, but they persist nonetheless. That’s because they are intrinsically systemic problems - undesired behavioral characteristics of the system structure "Clinical Operation" that produced them.

They will cease to exist only when we see the system as the source of its own problems and find the courage and wisdom to restructure it. The alternative is a significant IT investment in management productivity to manage the behavior of the system, hoping to contain its behaviors while ignoring the structure that causes their expression - a Teufelskreis.

The great news is that the solutions are in our hands. The disturbing part is that the solutions require us to see, think, and do things differently.

A New Perspective:

This series of chapters aims to illuminate a different way of thinking. It delves into what it means to “re-imagine,” “re-think,” and “transform” clinical opeeration to break Eroom’s law.

My hope is to get you to see the world differently and point you to recognize the opportunities that lie in looking at structural problems without being distracted by the noise of their outer behavior.

To be clear, my intent is not to disregard reductionism attempts (ePro/Consent/Reg, EDC/Imaging, etc.) aimed at addressing late-stage drug development challenges in favor of systems thinking. I genuinely believe that we need both approaches, much like we require cars for long-distance travel. But for cars to fulfill their promise, someone has to restructure the roads and possibly build highways to blitzscale their mobility potential.

Thinking about clinical trials as an element of the system clinical operation enables us to ask a deeper question: How is everything connected?

Answering this question takes us on a journey of understanding the mechanics of drug development, comprehending interconnections, designing predictive behavioral models, and most importantly, giving us the creativity, courage and the permission to reconstruct what has remained broken for generations.

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Side note: Accessing Strassmann's Wisdom:

While most of Strassmann’s books are no longer in print, you can access a few second-hand copies from retired business nerds, and he kindly put most of his speeches online at strassmann.com.

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