To succeed in AI, unlearn IT

Whilst predictions on the impact of artificial intelligence (AI) vary, they do share a common theme. It’s going to be massive. In fact experts estimate that AI will be contributing $14 trillion to the global economy by 2030. That’s larger than the GDP of any country bar the United States and China. Biotechnology and pharmaceutical companies can benefit from AI too. Having delivered over fifty projects in this area, we have identified the three key challenges they need to address to ensure success.

8 Minutes By Sara Enriquez Life Sciences 11/18/2020

At a Glance

The rapid growth of AI Is a game changer in practically every aspect of life. And there is no doubt the biotechnology and pharmaceutical industries can benefit hugely from it. Our teams have identified three key challenges that need to be addressed to ensure success:

  • A lack of understanding of AI.
  • Data constraints.
  • Understanding the talent you need.

The article also details how best to formulate a strategy and approach to ensure you successfully integrate AI into your organization.

AI offers biotech and pharmaceutical companies countless opportunities

Novel algorithms, greater computing power and huge datasets will support dozens of applications across the value chain. Pharmaceutical R&D can benefit too, in areas such as:

  • De novo small-molecule design.
  • New biomarker identification.
  • Targeted therapy development based on genomic data.
  • Drug interaction predictions.
  • Permeability and patient response.

Commercial and medical units in pharmaceutical corporations can leverage new computational techniques with:

  • Comprehensive KOL mapping.
  • Landscaping algorithms.
  • Virtual patient engagement assistants.
  • Marketing predictive analytics.
  • Sales force optimization.
  • Nonlinear relationship estimation with HEOR real-world-data.

But if you are to successfully tap the true potential of AI then we need to overcome the following three key challenges.

1. Decision makers lack an understanding of AI’s capabilities and limitations

This is understandable. It’s a new and still immature technology. And there are no established conceptual frameworks or strategies to help understand where the value lies. Or, for that matter, how it could fit into an organization.

Remember, AI is not a new form of IT.

In our experience, this leads to failure. That’s because IT can be summarized as automating information logistics (storing, sorting and transporting). However, AI automates much more complex cognitive tasks. For example, it’s the difference between an airplane’s autopilot system and the cockpit dashboard. The former is AI, as it is making decisions about direction, speed and altitude. Whereas the dashboard is presenting information and data – that’s IT.

2. Organizations face significant data constraints

Most AI solutions depend on historical data. And that can often be lacking, or of poor quality. Equally, it may not be available due to legal hurdles. Acquiring quality data requires long-term, sustained and cross-functional effort, and that’s where many organizations struggle. To scale capabilities you need to implement and adhere to data capture points across workflows. And that means your people have to care about this and put the effort in to ensure it happens

The right data may not be available internally.

You may need to consider strategic partnerships, acquisitions or licensing agreements to build up the right data assets. This needs to become a priority for senior management if the organization wants to unlock AI’s true potential.

3. Understanding the talent and structure needed to implement AI

One common misconception is the belief in an ‘AI expert’. This all too often leads to a costly arms race to equip your organization with the one person who can unlock AI’s value. More often than not this leads to disappointment.

It’s not about finding one person with specific technical skills.

It’s about having a team that can navigate the big picture, based on a thorough understanding of technical capabilities. Many organizations already have what is now called ‘AI’ in-house. They just don’t realize it. Because the underlying enabling technologies are not new. So rather than build new technical silos, empower existing teams to build the foundations that can accommodate AI and integrate it with their industry expertise and corporate vision.

AI demands a strategy, not a one-off initiative

Considering the three limiting factors together will help you create a coherent approach to AI. Remember, reaping AI’s benefits is a long-term effort at the intersection of fast-moving, converging technologies. This calls for a strategy, to manage risks, limit costs and navigate through uncertainty towards real value.

Start with opportunity discovery

This requires analyzing the AI landscape, considering your data resources and technology against organizational requirements. By doing this your team has the tools to brainstorm, evaluate and map opportunities into three categories:

  • Opportunities to implement immediately
  • Options for building data, technical and or talent foundations
  • Ideas that will benefit from strategic pathfinding.

Avoid focusing on quick-wins or lighthouse projects. These are often chosen for feasibility and distract from the long-term sources of competitive advantage.

There are four phases to implementing immediate opportunities, Proof of Value (PoV), Proof of Concept (PoC), implementation and, once operational, life cycle management. Let’s discuss the first two stages in more detail.

1. Proof-of-Value (PoV)

A quick but vital exercise where you explore plausible corridors of technical performance. Question the potential value to the business? What will it depend on? Remember, it’s all too easy to get carried away by new technological possibilities. So it’s essential to look at ROI. Doing PoV allows the Proof of Concept to be conducted in a focused manner. This is because key value drivers often only become clear when looking at ROI in a structured way.

2. Proof of Concept (PoC).

This is the most critical step. It brings science and its methods to data science. PoV establishes the capacity of AI tools to deliver value within the scope of the opportunity. The ideal way of executing the PoC is via sprints that each finish with go/no-go decision gates. This enables rapid re-categorization of ideas that lack feasibility, mitigating risks and costs. If an opportunity cannot be implemented immediately during PoV or PoC,  it could be because your organization lacks foundational capabilities to execute it, or AI cannot deliver on the expected use case.

Establish the right foundations and create data readiness

Achieving this requires the orchestration of various lines of work:

  • Historical data needs to be excavated, gathered and curated to assure quality.
  • Adjust  IT systems to facilitate information capture.
  • Remodel team workflows  to prioritize data capture.
  • Train people to understand data science and its value.

Finally, build a communication and scoping bridge between AI specialists and the rest of the organization.

What if your technology cannot deliver the desired results?

Be disciplined in strategic pathfinding to keep the aim on the strategic horizon. Your biggest opportunities may lie in technologies that are just emerging. Strategic pathfinding integrates AI technology monitoring and evaluation with a roadmap to build enabling and foundational requirements. Through pathfinding, you can prepare your organization to be in pole position for AI applications that blossom in three, five or ten years.

Ultimately, be aware of challenges and have a plan to overcome them

The range of AI use cases in the pharmaceutical and biotechnology industry is rapidly expanding. From the application of old-school decision trees, drug adherence prediction and even learning models that support or reject biomedical hypotheses; opportunities abound. However, to successfully leverage opportunities, make sure you are aware of the challenges and have a plan to overcome them.

Interested in any aspects of AI? Like further information on how you could integrate it within your organization? Then, please get in touch with our team today.

About the authors

  • Dr. Paul von Bünau, Managing Director, idalab
  • Sara Enriquez, Client Service Partner and Principal, a-connect

Need our expertise?
Let’s start a conversation

Demystifying the business improvement toolkit

12 Minutes Private Equity 12/13/2023

With the wide range of business improvement tools available, it’s natural to wonder which to use. For starte…

Developing Performance Management Processes and…

5 Minutes Life Sciences 12/15/2023

Driving sales and marketing in pharmaceutical companies has many challenges. Complex regulatory requirements, …

2024 Emerging Nutrition Trends

10 Minutes Food 12/19/2023

There’s little doubt that nutrition needs pose critical challenges around the world. And consequently, huge …

Discover the benefit of the…

5 Minute Private Equity 12/19/2023

Seven best PE practices that can be adapted by most companies to drive sustained growth. The key is to adopt …

The case for adding biostimulants…

11 Minutes Agribusiness 12/27/2023

With increasing EU support and their ability to meet consumer demand for a gentler impact on the environment, …

Unlock the true value of…

7 Minutes Life Sciences 01/03/2024

Legal Entity Optimization plays a critical role in mergers. If you master LEO strategy you can go beyond reduc…

When the global strategy is…

7 Minutes Food 01/04/2024

Expanding into a new territory presents exciting opportunities. But it can be littered with risk if the organi…

Four steps to unlocking Omnichannel…

15 Minutes Life Sciences 01/07/2024

The ever-evolving digital world is transforming the pharmaceutical landscape. This creates unique opportunitie…

Sustaining drug revenue or volume…

7 Minutes Life Sciences 01/10/2024

Entering the post- Loss of Exclusivity (LoE) zone is a complete game changer in terms of strategy and approach…

Six tips to ace your…

5 Minutes Food 01/10/2024

These six tips will help you ace any interview.