We’ve previously outlined how AI can help in the future of knowledge work, focusing on creating evidence-based content. The theme is that AI will help where it can, usually on the more tedious data gathering, allowing humans to focus on the most interesting and engaging parts (frankly, where the humans work best!).
Continuing on that theme, the next series of posts will get even deeper into specific use cases, focusing on how AI can help in Medical Affairs / HEOR activities ranging from Strategic Planning to Scientific Communications Platforms to Landscape Shifts (and Congress Management).
So, without further ado…
Strategic Planning & AI: Teaming up like Peanut Butter & Jelly
A crucial role for Medical Affairs involves leveraging their medical expertise to help with strategic planning within the organization. Strategic planning is a huge effort that involves many, many activities, so we will not comprehensively enumerate them here. Instead, we will focus on a few core activities and how AI helps to more efficiently perform some of the less glamorous work.
With that context, here are some of the Strategic Planning activities, and how AI can help…
Situational Analysis: Where are we today?
The first step in a strategic analysis is to deeply understand where an intervention or therapy area stands, today. Who are the competitors? What are the competing interventions? How do they perform?
In fact, this is precisely the type of task that AI (and Evid Science in particular) is good at. At Evid Science, our AI scours the literature to pull out the interventions, outcomes, results, affiliations and sponsors, and presents it in an easy-to-use and understandable format.
With these results, you can:
- Assess the current competition, narrowing down on specific competitors or indications
- Compare all of the therapies in an area across various end-points
- Understand who is sponsoring what research, and track which interventions already have compelling real-world results as well as trial results
- Keep current on today’s situation, even as it changes tomorrow
- Even discover the experts in a particular disease who focus on a particular intervention
In the most basic sense, the situational awareness can only come from sifting through lots and lots of results data. So why not let an AI help you do that?
SWOT: Unearth the Key Differences
Often, the initial data gathering is not enough, however. And while the machine can gather data and help answer some basic questions (as above), significant value comes from humans doing analysis over the machine-gathered data.
Consider the effort of SWOT analysis.
In a SWOT analysis, four specific questions are asked:
- (S)trength: Where is our offering strong?
- (W)eakness: Where is our offering at a disadvantage?
- (O)pportunities: Where are there opportunities for our offering?
- (T)hreats: What challenges exist for our offering?
Interestingly, the results data from the medical literature can often underpin these answers. So by combining data from the AI with human ingenuity, one can:
- Perform a meta-analysis to find key outperforming outcomes relative to the competition (a Strength), or underperforming (a Weakness)
- Find gaps where no data exists (Opportunities)
- Find commonalities among competitors that are positive (Threats)
- Find investigator-initiated studies in new indications (Opportunities, Strength)
- Track competitor results (Opportunities, Threats)
An AI isn’t smart enough to find the key differentiations among the results for you (though we are getting closer!), but it can provide you with data at the volume and breadth of AI, so you can do it in a fraction of the time.
Gap Identification: Finding the Opportunities Between
A Gap can be construed in a few ways – perhaps some key evidence is missing requiring a new trial or evidence to be synthesized from results across a few articles. Or, the gap is more metaphorical, in that there is a gap between how the results are presented and how they are being perceived. In which case, perhaps if they are framed in the context of competitor results or other investigator-initiated results, they will become clearer. In either case, finding the gaps requires having the data in the first place. And just like a SWOT analysis, the AI should gather the results for you, so you can focus on finding the holes.
In fact, in some recent work, we’ve tried to facilitate just that. In a research paper we highlight how AI-data can support visualizations for gap analysis – in the image below, we see how the machine can prepare the data, for the human to then interpret (in this case, mapping interventions for Crohn’s disease).
Experts: Their thoughts and Insights
Another key aspect of Strategic Planning is external stakeholder engagement. This largely involves two main tasks: (1) find the experts, and (2) talk to them.
Finding the experts by hand is tedious. It’s time consuming to compile the list, and finding them in the first place can be challenging when bibliometrics (such as h-index), might not be enough to find the experts you really need. But again, finding experts is a task ripe for an AI. So, in our view, let the AI do (1) so you can do (2).
At Evid Science, the outcomes-results uncovered by our AI are all backed by scientific papers, and therefore associated with authors. So, our data can be sliced and combined to identify specific experts in very specific ways – i.e., based on the outcomes and interventions they publish. For instance, below we find the expert in Scalp Psoriasis who published on response for ustekinumab and who is located in Germany.
So, while the AI can’t have the insightful conversations, it can at least point you to the right person to chat.
Congresses: Understand Trends of the Cutting Edge
As a final activity, consider the task of updating your strategy based on the latest, cutting edge results. Of course, some will come from the literature, but many will also come from the latest and greatest publications in the narrower Congresses. Within a specific disease area there are certainly conferences that one watches to find the trends, the latest results, and the up-and-coming researchers.
Again, AI can be a significant lift here. For instance, we’ve previously profiled how AI could pull results, not just from papers, but from congress abstracts. This helps inform:
- The latest results in the specific areas of interest
- The trends and themes that are emerging
- The researchers working on the state-of-the-art
This is by no means a comprehensive list of all of the activities that go into Strategic Planning, but hopefully it shines a light on how many of them can be accelerated by the use of AI. And as always, if you want to chat further, we would love to hear from you!