For years now, I've documented AI in drug discovery startups and pharma's use of AI in drug discovery. When I started, you could read those posts in a few minutes. So it was easy to stay up to date. Now they're each epic. So it's harder to find signals in the noise. To help, I created this post. My goal here is to highlight key trends and statistics related to AI in drug discovery. Like my other posts, it will help if this one is interactive. So if you have ideas for trends and statistics you would like to see analyzed, please post them in the comments. Now on to the data!

Startup formation may be slowing

Data I've gathered suggests that AI drug discovery startup formation has peaked. It's possible this will change as I become aware of newer startups not yet in my database. But my qualitative sense of the market aligns with this quantitative analysis. We may have hit peak startup.

AI in drug discovery startups founded per year

Most startups focus on new or repurposed molecular entities

I use arbitrary categories in my startups post. But they're descriptive. And as this chart shows, based on the data, the majority of startups focus on new and repurposed molecular entities. This includes generating novel drug candidates, repurposing existing drugs, designing drugs, and validating and optimizing drug candidates. In fact, this represents about half of activity amongst startups. This also means there is far less competition in other areas of the drug discovery process. (PS: Sorry some of the labels got cut off. It's an issue with Google Sheets, from which I generate the charts. I'll see if I can fix it in future.)

AI in drug discovery startups by category

Investment continues to increase, but the pace is slowing

Funding has increased every year since 2016. And there were huge increases year-over-year in 2017 and 2018. But the pace of growth appears to be slowing as the market matures.

AI in drug discovery funding per year

Venture investment is shifting to later stages

Funding data looks a bit different when you focus on venture capital (seed through series F). Rather than slowing, funding is shifting to later stages. This is another sign of a maturing market.

AI in drug discovery funding by venture stage

US startups dominate the industry

A few countries account for the majority of AI in drug discovery startups:

Geographical map of AI in drug discovery startups

 

Among these countries, the US is by far the leader. And only a few countries have more than one startup on the list: 

Top countries for AI in drug discovery startups

Several cities, including outside the US, have become hotbeds of activity

While the US dominates as a country, several dispersed cities have emerged as hotbeds. They have commonalities. They tend to be areas of high startup activity in general, like San Francisco. Or they tend to have strength in both machine learning and biology research, like Toronto.

Top cities for AI in drug discovery startups

Methodology and next steps

I compiled the data above using my own datasets, such as on startups using AI in drug discovery. I also used data from third-party sources such as Crunchbase. I'm generating the charts using Google Sheets. This is all somewhat of a beta, so if you see something buggy, please let me know.

I intend to expand this analysis over time. If you have ideas for trends and statistics you would like to see here, please post them in the comments.

Written By:
Simon Smith

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