By Rahul Bhushan, managing director of ARK Invest Europe
The investment case for traditional drug development is broken. Right now, pharma and biotech stocks are delivering a return on research and development of a little over 4% – far below the upside expected when deploying risk capital.
However, the adoption of artificial intelligence is rapidly re-writing the rule book on how profitable this space can really be.
Ongoing AI developments are not only improving the economics of developing drugs but also cures, removing the need for ongoing treatment altogether.
Our research points to a near-future where innovative, forward-thinking pharma and biotech stocks can deliver returns of up to 47% on R&D. With those sorts of returns matching those currently being made by AI leaders in the wider technology space today, the upside on offer for early movers could be huge.
Expensive and lengthily process
The problem with the traditional pathway to drug development is simple – it is too expensive and it takes too long.
Once failed candidates and the time cost of money are taken into account, the average cost of getting a drug to market is $2.4bn and the average time taken is 13 years.
Because the process is so lengthy, companies only have a limited window to fully commercialise their drug before its patent runs out and generics flood the market.
And because it is so expensive, the only chance they really stand of breaking even during the window is to hit a large patient population willing to pay a hefty sum for treatment.
AI changes everything. Producing, processing, and applying drug development data autonomously reduces the incidence of failure and speeds up progression through each stage of the clinical pathway.
Within just a few years, we expect AI-driven drug development to have cut the average cost of getting a drug to market to $600m and the time taken to eight years.
The upshot of quick, lower-cost development? Companies have a much longer period in which to commercialise their drug, and a much lower break-even point.
Our research indicates projected 30-year cumulative cashflow for the average AI-designed drug will total $4bn, up from less than £1bn for traditional drug models today. By the time a traditional drug breaks even, an AI-developed drug could have already generated some $2.5bn in cashflow.
Finding cures faster
It’s not just drug development AI is transforming, either – it is also cures. The extraordinary data processing capabilities afforded by AI, along with ground-breaking techniques like gene editing, offer unprecedented insights.
Such scale of information would not have been available even just a few years ago. And the result is, pharma and biotech players are now identifying opportunities to cure diseases historically managed over a patient’s lifetime.
The best example, of course, is Cykel’s ground-breaking AI-based gene-editing treatments for patients suffering from sickle cell anemia and beta thalassemia.
Traditional wisdom would dictate that – while better for humanity – eliminating your addressable market by curing them is bad for business. This is a widely held misconception.
Cures command much higher prices than traditional treatments. The average price today exceeds $1m – nearly 15 times the average lifetime prescription cost necessary to manage a disease.
Likewise, cures are superior to drugs from a competition perspective. They capture a patient’s lifetime value right up top, bypassing future competition post-patient expiration entirely.
Put these two points together, and our research suggests AI-driven cures could become up to 20 times more valuable than a typical drug and 2.4 times more valuable than chronic prescriptions.
A more efficient sector
As technology advances, we expect the pharma and biotech spaces to bifurcate between AI-driven cure-seeking firms and those traditional firms failing to adapt.
Where the returns on drug development R&D will continue to languish below 4% in the latter camp, we see lower costs, quicker progress, and an expanded focus on cures driving the same figure up to nearly 50% for the former.
Of course, we cannot be sure exactly how events will play out, but one thing is for sure – developments in AI will make for an exciting end to the 2020s and beginning to the 2030s for investors in the pharma and biotech spaces.