More $10B+ biotech companies have been built by younger (under 40) CEOs than experienced CEOs. The dogmatic preference for experienced CEOs in biotech is a relatively recent phenomenon (last 15-20 years). It is a function of 1) all the next-gen tech of the genomic bubble of the late 1990s flaming out (gene, cell and antisense therapy v1, genomics v1) and 2) the success of the asset-centric build-to-buy model in biotech VC.
If your model is to fund assets carved out from big pharma, develop them to human POC, then flip them back to big pharma, it makes sense to hire ex big pharma managers to run the company. If your model is to build a large, lasting startup, historical data suggest you are better off with a younger, more technical founder. In a world where pharma is not doing as much startup M&A, where capital is readily available from Series B to public markets, and where you can get drugs approved relatively quickly, more startups have the option of becoming independent companies and not just trying to sell to pharma
I am not in this space myself, but I know a few founders who are and the perception is that they face meaningful headwinds from the late stage community due to their age and market preferences for asset-centric startups.
There is more capital available in terms of number of dollars invested in biopharma startups. This is true across the board from Series A to IPO stage. 2018 was a record year for VC investment in biopharma. 2019 is down a bit but still shaping up to be the 2nd highest year on record [0]
There is a lot of Series A funding, I referred specifically to "Series B to IPO" because most Series A funding comes from 5-10 VCs who start companies in house. Later stage funding comes from a wider number of investors
The IPO market is also more open now than all but a handful of previous years.
There is also more venture investment in "platform", as opposed to asset-centric companies now than ever before [1]. Of the companies that went public since Jan 2018, ~25% of the programs they are working on are gene and cell therapy. Traditional small molecule programs represent under 50% of programs these companies are working on [2]. Historically essentially all FDA approved drugs are small molecules or biologics, so this shift to gene / cell therapy platforms is pretty significant
That said, a platform is only as valuable as the assets it generates. The value of a drug increases exponentially as it becomes "derisked" through clinical trials, and the value of preclinical or earlier programs is not super high. In many cases later stage VCs won't invest unless there is a fairly derisked asset, or unless there is some really compelling evidence validating the platform (Arvinas is a good example of platform tech that is well validated, they went public at preclinical stage and are worth ~$1B).
This is a function of the structure of risk in drug development and I think that it is rational for more advanced assets to be more valuable than less validated, but potentially more impactful platforms. I wrote an article on the relationships between risk and value in biotech that quantifies some of these ideas: https://www.baybridgebio.com/drug_valuation.html
There is also often a valuation disconnect between tech VCs, who may invest at earlier stages and at higher valuations, and biotech VCs who would ascribe lower valuations and / or require more derisking of clinical risk. The biotech VC market is very hot compared to historical activity, but it is not quite as hot as tech VC in general.
There is def some deep age bias in biotech VC, it sucks and I / my friends experience a lot of it. I think it's an irrational bias and it will get competed away.
[0] https://www.baybridgebio.com/1h2019_report
[1] https://www.svb.com/trends-insights/reports/healthcare-inves...
I guess it's relative, I'm not even 30 :)
FWIW the pushback I get from big pharma is less around age but rather as an AI guy saying "look I solved that thing you've spent 20 years working on."
Have you tried selling to startups? From what I've heard they are better customers for AI drug discovery services as there is less entrenched interest in manual med chem and they value lower cost / fast iteration more