With an increasing demand for innovative healthcare solutions, the pharmaceutical sector has transformed significantly in recent years. The effective ongoing incorporation of AI has emerged as a pivotal force, reshaping the traditional paradigms of drug discovery, development, and commercialization – further enabling Putnam’s mission to strategically support clients in making confident decisions and building value.
We sat down with Remco op den Kelder, Putnam’s CEO, to delve into the current landscape for AI within the life sciences. As a pragmatist and problem solver, Remco strongly believes AI is a critical enabler in our toolkit to help us solve some of our most challenging projects.
The essence of our mission at Putnam remains unwavering; we support our clients in making better, more confident decisions. Yet, the winds of change undeniably shape how we approach our craft to deliver this. At the heart of this evolution is the indispensable role of Artificial Intelligence (AI), which, over time, we believe, will seamlessly complement the skill set of our consultants – and it’s continuing to be a core differentiating factor for us.
There are two distinct ways that we’re approaching AI: how we integrate across the value chain of consulting and how we support our clients to better understand where they can integrate AI into their business, whether it’s helping prioritize use cases for AI or developing proofs of concept. We support clients to think through a strategic approach to algorithms and validation.
Our strategic approach to algorithms is a good example of our journey into AI. Here, the expertise of our seasoned consultants intertwines with the computational capabilities of AI to chart a course through the vast landscape of possibilities. The strategic approach is twofold, with the scientific lens focusing on evaluating existing algorithms for specific diseases. We don’t simply identify algorithms; we provide a structured framework to assess them, ensuring our clients leverage the most effective tools for optimal patient outcomes.
With Navigator.ai, Inizio’s proprietary AI platform, we’re able to rapidly build and deploy custom tools to offer unparalleled insights in a compliant environment. One example is our product pipeline tool, AssetNav, that enables quick identification and prioritization of assets to power decision-making.
The validation process illuminates the path from data to actionable insights. In a world inundated with information, our consultants’ work is complemented by AI tools to draw nuanced insights. Our medical insight platforms are an example of collaboration, where the convergence of scientific rigor and statistical assessment ensures that only answers with a 90 to 95% probability of being accurate are considered. It’s a scientific dance, validating outcomes and shaping solutions that resonate with unwavering accuracy for our clients.
Moreover, the exploration of AI extends into qualitative research analysis, where technology augments our capacity for nuanced comprehension. By coupling scientific expertise with AI capabilities, we envision a future where the arduous task of reviewing interviews and generating summaries becomes a seamless, insightful process. It’s not about replacing human engagement; instead, it’s about empowering our teams with the tools to dig deeper, ask clarifying questions, and extract profound insights from the data sets at their disposal.
As we embark on the transformative journey of AI integration, the stage is set with challenges that echo the complexities inherent in our pursuit of innovation. The questions reverberating through our corridors revolve around the ‘how’, ‘what’, and ‘when’ of AI. For example, how do we leverage AI to identify rare disease patients, and what strategies can we employ to build robust bridges for data, laying the groundwork for informed decision-making?
Identification of rare disease patients: A crucial quest for accelerated clinical trials
The quest begins with identifying rare disease patients, where the power of AI can potentially revolutionize the landscape. Imagine a scenario with an array of AI tools—each claiming to be the solution. The challenge lies not just in selecting a tool but in discerning which one aligns most seamlessly with treatment paradigms and patient needs. This challenge has become increasingly prevalent, especially in the context of clinical trial recruitment. Identifying the right AI tool holds the potential to accelerate clinical trials, ushering products to market with unprecedented speed. The inherent value of this identification process resonates not only in efficiency but in the tangible impact of bringing life-changing treatments to those who need them most. However, we know that when developing AI algorithms to identify undiagnosed patients, we still need to consider a variety of factors to ensure the tool is unbiased and can overcome a variety of implementation challenges.
Building bridges across diverse data sources: The conundrum of information overload
The second challenge unfolds in the expansive realm of data. In a multifaceted industry, where data flows from diverse sources—from advisory boards and expert consultations to physician interactions—building bridges across this information mosaic poses a formidable challenge. Historically, sifting through this wealth of data has been a Herculean task. Questions abound on synthesizing insights from disparate data sets, discerning challenges and opportunities, and ultimately creating a cohesive narrative to inform strategic decision-making. Enter AI—the catalyst capable of traversing these intricate data landscapes, providing a panoramic view that eludes human limitations. The unique capability of AI to synthesize vast volumes of information ensures that insights are comprehensive and consistent, transcending the variability that human interpretation may introduce. On the other hand, we have seen how human training and iteration can optimize results.
Multi-disciplinary Problem-Solving
Tackling these challenges requires more than just technological capability—it demands a multi-disciplinary approach deeply rooted in expertise. Our success narrative in overcoming data challenges hinges on three pillars: (1) the strategic expertise that underpins every facet of our consultancy, (2) the unwavering focus of our teams on fully understanding the clinical and scientific landscape, and (3) our profound track record in delivering analytics and AI capabilities and solutions.
As we peer into the future, the horizon is ablaze with the transformative potential of Artificial Intelligence (AI). The upcoming years bring an era where AI becomes an integral part of our daily operations, a tool not just embraced but actively complementing the course of our strategic discussions.
As a sailor, I see the AI journey as navigating with a map from the 1800s: there is plenty of guidance, yet a lot remains to be written. The journey will offer a realm of immense promise and potential pitfalls. The key will be to not be afraid to experiment; however, do so in a safe, transparent environment to ensure no unintended harm is done.
Keep AI at the forefront: Unleashing the power with caution
The foremost counsel is to keep AI at the forefront of your strategic considerations. Recognize the discomfort that may accompany this technological shift and approach it with a sense of mindfulness. In an industry where consequences directly impact patients and healthcare professionals, the imperative is to tread with caution. By keeping AI at the forefront, we can leverage its potential while safeguarding against unintended consequences.
Engage rather than rely: A nuanced approach to AI integration
A critical distinction lies in how companies approach AI—engage with it rather than relying solely on its capabilities. Full reliance may breed complacency and blind spots, potentially leading to oversights that can have far-reaching consequences. Engaging with AI involves a symbiotic relationship where human expertise collaborates with AI capabilities. This nuanced approach ensures that while AI augments processes, human expertise remains a crucial factor in decision-making.
Try fast, fail fast: Embrace iteration and learn rapidly
The mantra of “try fast, fail fast” encapsulates the essence of iterative experimentation. Embrace a culture of experimentation, where trying new approaches and technologies is not just encouraged but integral to progress. The dynamic nature of AI demands a hands-on, exploratory mindset. By trying fast, companies can swiftly identify what works and where value lies. The act of failing fast implies a rapid feedback loop, enabling quick adjustments based on real-world insights. In the ever-evolving landscape of AI, the ability to iterate rapidly is a key driver of success.
Recognize when you’re not ready: Prudent decision-making
Equally important is recognizing when you’re not ready for full-scale AI implementation. This humility in acknowledging the limitations of readiness prevents premature adoption that could lead to suboptimal outcomes. Deciding when to wait a little longer is a strategic move that aligns with the principle of measured progress. In the fast-paced realm of AI, strategic patience becomes a virtue, allowing companies to align adoption with their preparedness and maturity.
Fusing intellectual curiosity with Artificial Intelligence (AI) is a distinctive advantage. Driven by insatiable curiosity, our teams navigate beyond conventional boundaries, setting Putnam apart.
Strategic framing, where AI is not just a brainstorming partner but a strategic ally, becomes pivotal. This collaborative approach transcends ideation, ensuring that visionary solutions crafted are not only groundbreaking but also ready for seamless implementation. Client-centric engagement, augmented by emotional intelligence (EQ), remains paramount, reinforcing the indispensable nature of the consultancy skill set.
2024 will be seen as the year where we migrate from experimentation to full scale implementation; however, it will be critical to maintain diligence to ensure we capture the full potential, in a responsible manner that ultimately will help our industry better address some of the key unmet needs.
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