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Business Case for AI for Medical Insights
Christina Cullen
Apr 21, 2022

How to Build the Business Case: AI for Medical Insights

Artificial intelligence is a topic circulating across the life sciences. While the primary focus has been on research and commercial, Medical Affairs is now presenting use cases for AI. This guide explores how MA can build the business case for AI for medical insights.

In an industry altered by COVID-19, Medical Affairs continues to innovate its digital strategy. Teams have made notable shifts to adapt to a virtual environment, using new technology as a tool to better serve health care providers (HCPs) and patients. 

But there are still hurdles to face. Since the pandemic, volumes of disparate medical and scientific content are on the rise. Not only does Medical Affairs need to process this content, but it also needs to generate evidence and uncover insights for data-driven decision making. The time and capacity this requires could wedge the cycle to a halt.

If AI can be a partner in medical insights management, the productivity potential is monumental.

Examining Use Cases for AI: Medical Insights Management

While the two letters “AI” evoke images of the future and its possibilities, they also elicit doubt and uncertainty from many. There is a lot of hype around AI, and the truth is, it’s not all valid. This reality, coupled with fears of job replacement and technology takeover, leaves many wary of adoption.

In a recent study by Deloitte, life sciences enterprises considered these factors as the 3 biggest inhibitors:

  1. Identifying use cases with the greatest business value (30%)
  2. Integrating AI into the organization (28%)
  3. Data challenges (28%)

Despite these roadblocks, in recent years, there has still been wide adoption of AI across. A report by the Harvard Business Review states that successful projects have emphasized augmenting, rather than automating, workflows, as well as framing AI as a component of larger business and digital objectives. 

In Medical Affairs, AI can support business goals by accelerating the insights cycle.

Insights Feedback Cycle

In Medical Affairs, artificial intelligence can:

  • Improve productivity
  • Condense insights cycles
  • Refine data-driven decision-making
  • Synthesize insights across sources
  • And more

From literature reviews to clinical trials and real-world data, centralizing insights can have a major impact. But how can Medical Affairs make the internal business case to demonstrate this value?

Approaching the integration of AI for medical insights comes down to connecting the dots between individual contributions, the business, and patients. It’s about bridging the connection between Medical Affairs workflows and business objectives.

If Medical Affairs is able to show this value, it could make the case for AI and help turn decision-makers into advocates. 


Building the Business Case: Why AI? 

As Medical Affairs builds the case for augmenting insights management with AI, one of the first areas to address is reasoning.

  • What opportunities will AI bring to existing challenges or future innovations?
  • What are the barriers to adoption that should be discussed from the start?

Framing the case from the perspective of the executives will bolster the value proposition for Medical Affairs.

  • What are the organization’s current strategic business objectives?
  • How would a streamlined insights management process, enabled through AI, support these business goals?
  • Could this lead to better patient outcomes? 

In a Deloitte study titled “Artificial Intelligence for the Real World,” 250 executives were surveyed to better understand their AI goals.

The top 4 business benefits of AI were: 

  1. Enhance products and product features (51%)
  2. Optimize internal business operations (36%)
  3. Free up workers (36%)
  4. Make better decisions (35%)

AI for medical insights can achieve each of these performance objectives. With a shorter insights cycle, HCP and patient feedback can be incorporated into product decisions with more agility. Centralizing insights enables teams to access the same information, reducing the effects of siloed data and content and optimizing workflows.

By lifting the burden of manual tasks, such as logging or reporting, Medical Affairs is freed up to use their expertise and focus on better decisions, which ultimately stretches to each arm of the business. These benefits can then be connected to specific business goals, including revenue.


Reducing Costs

ROI is a topic of conversation in any business case, and it might be the first brought to the table. Pharma executives will need to envision the costs of implementation, both financially and operationally. As in most industries, artificial intelligence-based solutions are new, and so it is sensible to find hesitancy to invest in solutions without years of track record.

Opening the dialogue allows leadership to get a clear picture of the financial investment, begin to pull in internal and external stakeholders, and then lay the groundwork for short-term and long-term returns. 

This is also where the benefits can be presented. Medical Affairs are highly trained professionals, and their time is extremely valuable to the bottom line. By freeing up their time and empowering them with clear, real-time insights, they can put more time into high-value tasks that benefit the business.

It could also be valuable to frame AI not as its own singular initiative, but as a component of the larger digital strategy. As Medical Affairs continues to advance its use of technology as a whole, AI can complement these larger initiatives. This enables prioritization and agility. 


Identifying operational efficiencies

Time savings is a substantial, immediate benefit of using AI for insights management. When presenting the business case, there are real-world use cases that can be examined to calculate the actual amount of hours that can be reduced with AI augmentation.

For example, a recent real-world case study performed by members of Coherus, Moderna, Medistrava, and Sorcero found that when augmenting the manual literature review process with AI, the average MD/Ph.D. time to review reduced from 715 hours (average 27 min per article) to 75 hours (55 hours of review + 25 hours of QA). This was an 88% time reduction.


Intelligent Literature Monitoring Case Study


Specific workflows to examine within your own Medical Affairs team could include:

  • Literature review
  • Unifying data and content
  • Report creation
  • KOL engagement

It’s also recommended to consider time holistically. There will be a learning curve to new technology, and some team members may be hesitant. For most people, familiarizing oneself with a new system takes time. Best practices would be to build out the right training and support, complemented with the overall digital strategy, to ensure teams not only feel comfortable but enabled. 


Improving HCP and Patient Experience

Medical Affairs faces overwhelming volumes of data at a time when data-driven decisions are crucial for HCPs and patients. Both are seeking more personalized solutions backed by data, so having the ability to deliver and capture insights in real-time will set Medical Affairs professionals apart from the rest.

With an AI platform that can capture, enrich, and analyze data to export in the form of a report, information shared with KOLs can be targeted to each individual, and then feedback gathered can be directly brought back to the business. While developing this section of the business case, transparency and privacy are key areas to address. However you decide to implement an AI solution, data should be transparent and above the surface.


Selecting the right AI solution

When it comes down to it, the best way to know if an AI solution is right for your business is to dive into a better understanding of the technology. While, of course, it would be almost impossible, and certainly impractical, for every member of the business to become an expert, a general understanding is quite valuable. 

Learning more about AI builds confidence and trust, which allows teams to begin to separate signals from all of the hype. The more people know, the more secure they will be in their position to see the value, as well as where to best prioritize.

It comes back to not just implementing AI for the sake of it, but connecting it directly back to business goals. Finding ways to better understand AI, and in turn, share this information within your organization will help to bring others on board. 

Here are some factors to consider when choosing an AI for medical insights platform. 

  1. How does it integrate with current systems?
  2. Is it usable by both technical and non-technical experts? 
  3. Is it designed to augment workflows?
  4. Is it scalable across the business? 
  5. Is it transparent? 
  6. Is the technology really what it claims to be?

In this recent Medical Insights Management Webinar, Medical Affairs experts at Eisai, Spark Therapeutics, MedEvoke, Medistrava, and Novartis discuss what they value in an insights platform.


To watch the full webinar,  you can download the free webinar recording here. 

Watch the free webinar: Medical Insights Management: Better Insights Faster


Stakeholder Impact Across the Life Sciences

Another major component to consider in the business case is the human element. Who will be involved and impacted by bringing AI solutions into existing and future projects? Medical Affairs insights are meshed into the organizational web of strategy and decision-making, so as opportunities and capabilities expand, so will the potential for collaboration. 

IT support will be hugely beneficial in the layering of new technologies into existing systems. Additionally, other departments including finance, human resources, and legal should play roles in ensuring that everyone is aligned. National and global strategies should also be weighed out, as requirements and resources are likely to vary. 

Gaining internal buy-in across the organization is an obstacle to the business case. First, the cultural shift involves employee apprehension of replacement, as well as the hurdle of learning new technologies. There must be a recognition of value internally to be able to shift these fears into confidence, trust, and excitement. This involves top to bottom collaboration, feedback sharing, and continuous improvement. It’s true that not all AI projects are successful, so it takes a full data-driven strategy to succeed. 


How will AI solutions be implemented?

Continuous improvement is also the basis for successful AI implementation. By prioritizing AI for medical insights, it enables Medical Affairs to concentrate on specific workflows and use cases that garner the highest impact. Teams can consider piloting projects as they lay the groundwork.

During this period, organizations can gather the team that will be involved in the implementation, as well as outline responsibilities, strategies, and policies. Medical Affairs can collaborate to design AI-augmented workflows, align stakeholders, and share feedback. Decision-makers will be interested in the timeline, so be realistic, plan to run tests, and be open to adjusting when and where needed.


Launching the Business Case 

Innovating today will lead to the competitive advantage of tomorrow within the life sciences. For Medical Affairs, the ability to tie insights to business decisions in a real-time cycle will enhance processes, reduce costs, and better deliver the right solutions to patients. Every pharma organization is different and faces unique concerns over AI implementation, but a better understanding of its capabilities and benefits can lead to finding the right solution for your team. 

If you’d like to learn more about how 40% of the top 10 global life science companies are using Language Intelligence to improve productivity and drive strategy, schedule a discovery session today.



Christina Cullen

Christina is a skilled content marketer and storyteller with a knack for SEO.