Nimbus Therapeutics showed the promise of AI-assisted drug discovery by completing in 6 months research that would normally take 2 years - which got it a landmark $4 billion cash deal with Takeda last year.

But how have other AI-assisted drug discovery companies fared?

The overall AI drug discovery space remains on fire, with $4 billion invested last year alone according to Bloomberg.

While Nimbus's success stands out, the outcomes for others are more nuanced.

Despite large headline deal sizes, a deeper analysis of notable 2023 deals shows the upfront amounts paid to AI discovery partners are sometimes less material to their overall financial position:

BioMap <> Sanofi: The $10M received upfront is a tenth of the $100M Series A BioMap raised in July 2021.

Phenomic <> Boehringer Ingelheim: The $9M upfront is impressive given the company launched with just $6M in seed funding in 2020.

BigHat Biosciences <> AbbVie: The $30M upfront represents a meaningful win for a company that has raised a cumulative $100M.

Valo Health <> Novo Nordisk: The $60M in upfront and near-term milestones is a solid outcome for a company that has raised $450M total.

Exscientia <> Merck KgA: The $20M represents a smaller portion of the $400M+ in equity raised for this UK-based public company.

When looking further into the past to deals from prior years, there are other notable wins. Publicly-traded Recursion Pharmaceuticals stands out, having partnerships with Bayer, Roche, and Takeda.

Another public company partner is Vancouver, WA based Absci Corp, which struck a deal with AstraZeneca in December 2023. While the overall deal value of $247M was announced, the upfront portion was not disclosed. Given Absci is subject to stricter disclosure requirements as a public company, one can assume the upfront amount will eventually be released, although it is unlikely to be substantial.

Time will tell if these deals turn into major wins, or remain relatively minor contributors to financial performance.

One key difference is Nimbus was willing to hold the asset for longer, until strong Phase IIb results created a value inflection point.

That illustrates a larger theme - while AI drug discovery has huge promise, achieving the biggest wins involves not just the best models, but old-fashioned persistence and risk taking.