The post-COVID biotech boom left many companies with ambitious pipelines, high valuations, and expensive development plans. The market that followed has been less forgiving: investors now want earlier clinical signals and clearer evidence that a program can compete globally.
As part of The Medicine Maker’s series on the evolving investment environment in biopharma, we spoke with Lingshi Tan, Executive Chairman of Caidya and co-author of a recent paper in Nature Biotechnology on early clinical development, about the forces reshaping drug development after the pre-COVID valuation boom.
In this first part of our conversation, Tan discusses why early human data has become a critical value inflection point, how funding models are becoming more disciplined and global, and why the next generation of biotech companies will need to think beyond a single market from the outset.
Could you give us a brief “helicopter view” of the current drug development landscape – and how it has evolved over the past several years, particularly in the post-COVID era?
COVID became a unique turning point for clinical development. The dramatic need for accelerated clinical development crashed head on with unprecedented restrictions on access to medical care.
This launched a range of innovative approaches, many of which are still working their way through the system today. Decentralized trials and remote monitoring became widely adopted worldwide. Regulatory authorities, which had already become more flexible, introduced new approval channels designed to accelerate time to market. Industry collaborations became more common.
Looking back from our 2026 vantage point, I now view these initial responses as accelerants to fundamental changes that had already begun to germinate pre-COVID. The transition to precision medicine, radical breakthroughs in biology insights, and the application of new technologies have today established an almost entirely new platform for the future.
Lengthy traditional pre-clinical analysis, pervasive reliance on animal models, and lock-step synchronization of regulatory gateways with the rigorous application of three distinct phases of clinical development, are all being challenged.
It feels as though we are at the very early stages of momentous change. Take just two approaches in today’s discovery/development landscape that were difficult to imagine back in 2019: using AI to identify and select drug targets, and apply existing therapies to new indications, leapfrogging much of the scientific regulatory hurdles demanded for new chemical entities (NCEs). Or the novel clinical approaches designed to gain preliminary insights from in vivo human responses in order to simultaneously refocus and de-risk subsequent clinical development and regulatory approval.
If I take a step back, what strikes me most about the current landscape is that drug development is becoming both more innovative and more fragmented at the same time.
On the innovation side, we’re in a remarkable period – cell and gene therapies, RNA platforms, and next-generation biologics. Scientifically, the toolbox has never been richer.
But structurally, the system is under pressure. Costs continue to rise, timelines remain long, and the productivity of R&D hasn’t improved at the same pace as the science. That tension is really defining the current moment.
The other major shift is geographic. For a long time, drug development was largely centered in the US. That’s no longer the case. We’re moving toward a much more distributed, or multipolar, ecosystem where innovation and execution capabilities are emerging across regions.
Post-COVID, there’s also been a mindset shift. The pandemic showed us what’s possible when speed, alignment, and urgency come together. Now the challenge is how to retain that agility in a much more capital-constrained and disciplined environment.
At this pace, it is hard for me to visualize exactly what the global discovery, clinical development, and regulatory landscape will look like five to eight years from now!
In particular, how have funding models and investor expectations shifted in recent years?
It’s a great question, since the models of the past – and the structure of the industry itself – have already begun to radically change again, for the third time during my career. In the early 1990s when I joined Schering Plough and then Pfizer, the industry was dominated by a dozen or so publicly listed companies whose in-house small-molecule discovery-driven growth would soon give way to massive consolidation via acquisition that included everything from OTC drugs to personal care and medical devices.
But the game was about to change. Genentech and Amgen, venture-funded companies founded in 1976 and 1980, still flew under the radar of most investors. Their explosive growth in the 90s and Roche’s acquisition of Genentech charted a very different path to success. Venture funds proliferated in hopes of incubating more blockbuster biotech firms focusing almost exclusively on leveraging the US market’s high prices for innovative biologics. IPOs and Big biopharma provided attractive exits, but generally only after positive Phase II data made FDA registration a high probability.
Today’s investors and aspiring biotechs find themselves in a very different environment compared to the pre-COVID run up in valuations when capital was abundant, valuations were elevated, and non-traditional investors – including crossover and institutional funds – played a larger role alongside traditional venture capital. With US market scale and profitability no longer guaranteed and development costs continuing to rise, today’s funding model has changed.
Success as an investor will increasingly require the capability to scour the world for compelling science, structure collaborative risking-sharing transactions, launch multiple “probes” to identify and sequence the most attractive indications and regulatory pathways, and then rapidly double down on the drive toward registration in multiple markets. It will be interesting to watch how this may shift the roles of early-stage VCs, mid-market funds, and big bio-pharma firms.
Deloitte’s 2025 “Measuring the Return from Pharmaceutical Innovation” report found that projected R&D returns for the top 20 biopharma companies were ~5.9 percent, but would fall to ~3.8 percent if GLP-1 assets were excluded. The already intense pressure on these companies to refresh aging portfolios now demands that they simultaneously de-risk R&D pipelines and accelerate their expansion.
For a group of companies long viewed as slow moving, risk-averse, and wedded to in-house R&D, the transformation has been striking. In-licensing and acquisition of new drug candidates by big-biopharma has grown dramatically during the past decade, growing to nearly 50 percent of their pipelines. Deals are being done earlier in the development cycle, with a growing share targeting biotechs outside the US. This in turn requires a level of scientific, medical, and regulatory depth – along with deep pockets and global experience – that even the most sophisticated venture investors find hard to match.
The funding environment today is fundamentally more disciplined than it was just a few years ago.
In the past, there was a greater tolerance for risk, particularly in early-stage biotech. Capital was more readily available, and programs could advance further before being rigorously challenged. That’s no longer the case.
What I’m seeing now is a much stronger focus on capital efficiency and early value inflection. Investors want to understand not just the science, but the development strategy – how quickly you can generate meaningful data, how you’ll differentiate, and how you’ll manage risk.
Another important shift is that funding is becoming more global. Cross-border partnerships – particularly involving China – are increasingly common, and companies are thinking more strategically about where to develop assets, not just where to discover them.
Overall, the bar has been raised. And in many ways, that’s a healthy evolution for the industry.
Your recent Nature Biotechnology comment argues that early clinical development has become the critical inflection point in modern drug development. What has changed in the industry to make execution at this stage so important today?
In the funding environment we just discussed, generating early-stage translational data that boosts the probability of success offers the critical bridge across the “valley of death.” While traditional pre-clinical processes remain important, I see them being supplemented by patient databases and AI-supported targeting that can significantly de-risk first-in-human trials designed to test very early indicators of both safety and efficacy.
Demonstrating a drug candidate’s differentiation at the earliest possible stage becomes essential. Data that support both clinical superiority and/or a faster path to initial launch – even in a relatively small patient group, has the potential to dramatically improve overall returns when compared with an expensive five- or six-year slog through pre-clinical and Phase I only to miss a Phase II endpoint on which an investor has placed all their bets.
Historically, much of the perceived risk sat in late-stage trials. But that’s changed. The true inflection point has moved much earlier, into first-in-human and early proof-of-concept studies.
There are a few forces driving this. The most obvious is economic; late-stage failures are simply too costly in today’s environment. But equally important is that we now have better tools in translational science, biomarker development, and patient selection. We can ask smarter questions earlier.
What’s also changed – and this is something we’re seeing very clearly – is that early clinical development is becoming more global. More first-in-human studies are being conducted outside the US, particularly in China, where timelines can be faster and execution more streamlined.
So, success in early development is about making the right decisions early, dose, population, signal, and setting up the entire downstream program for success. If you get that right, everything becomes more predictable. If you don’t, it’s very difficult to recover.
In part two of our conversation, Tan turns to China’s rapidly evolving biopharma ecosystem – and explains how its speed, integration, and approach to early clinical development are reshaping assumptions about how, and where, innovative drugs are brought to patients.
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