Pioneering for patients: biotechs’ role in accelerating global innovation

Platform technologies, AI and global clinical trials offer different but synergistic angles on reducing cycle time for drug development

If the odds of success are to improve in drug development, and more, better drugs to be brought to patients more rapidly, companies will need to find ways to de-risk and accelerate their innovation processes. Platform technologies, AI-driven drug discovery, and global clinical trial footprints all have the power to do exactly this. But to what extent?

Despite the biopharmaceutical industry’s extraordinary success over the last 20 years in pioneering life-changing therapies for patients, the drug development enterprise has not become more efficient. The likelihood of any individual therapy in development becoming successful has held steady at around 10% for the last 20 years, according to a McKinsey & Company analysis last May.

Moreover, it could take years to fully understand the potential of some new treatments. Investments in cell and gene therapies accounted for 30% of all VC funds that went into therapeutic-based biotech companies in 2019-2021. But only time will reveal the long-term impact of the new therapies emerging from these investments.

It seems clear, therefore, that companies need to find ways to de-risk and accelerate their innovation processes if they are to improve the odds of success. Three developments in the industry could do just that.

The first and most mature is platform technologies — defined here as a new therapeutic modality or technology that adds a novel feature to an existing modality and is the foundation for a company’s therapeutic pipeline.

The second is artificial intelligence (AI)-driven drug discovery, which brings the opportunity to reconfigure how drug development happens, including insights that human design alone could not uncover.

And the third is the globalization of drug development, which can change the economics of drug development, the predictive value of how clinical trial results will map onto performance and, most importantly, open the door to engage more patients around the world.

What remains in question, however, is the extent to which each of the three drivers will de-risk or accelerate drug development.

At one end of the spectrum, a driver may be a niche activity with a limited or short-lived impact. At the other, a driver could exert an outsized impact, transforming both the global industry and disease treatment standards. Early evidence combined with the perspectives of biotech industry leaders gives insight as to where each currently lies on this spectrum, as well as their future potential.

Platform technologies

Views on the power of platforms to accelerate innovation in biopharmaceuticals have swung back and forth for decades. Notable successes have encouraged companies and investors to prioritize investments in platforms over individual assets, while failures have swung the pendulum back the other way.

Today, successes such as the mRNA-based COVID-19 vaccines developed by Moderna Inc. (NASDAQ:MRNA) and BioNTech SE (NASDAQ:BNTX)/Pfizer Inc. (NYSE:PFE) and the RNAi therapies from Alnylam Pharmaceuticals Inc. (NASDAQ:ALNY) for genetic diseases have reinvigorated interest from public and private investors, other biopharma companies, and regulatory agencies. In short, there seems to be renewed conviction that platforms will be key to accelerating innovation.

Our view is that platform technologies are beginning to play a focused role in the biopharma industry.

It has become generally accepted that a platform can be applied to other therapeutic areas within the primary use case — that mRNA prophylactic vaccines can be used for infectious diseases beyond COVID-19, for example. Platforms therefore have the potential to be a key differentiator for companies across many therapeutic areas. Whether they will have still broader, outsized impact, with single platforms developing different products for different diseases, each with their own set of development and regulatory criteria, is yet unknown.

It may prove difficult to de-risk an entire platform based on the first indication alone. For new modalities, a lag is frequently observed between the first and second approval, and often between the second approval to the third. Similarly, a platform looking to bridge across multiple diseases or from prophylactic to therapeutic indications, like mRNA today, can also prove challenging — while the safety may be de-risked, the efficacy profile is not guaranteed.

VC funding reflects the state of play. The number of platform biotech companies backed by VCs tripled between 2019 and 2021, and platform companies came to account for 67% of total biotech VC funding.

Moreover, despite their earlier-stage pipelines, biotech platform companies that completed an IPO on NASDAQ in 2019-20 raised more capital through IPOs and out-licensing deals than non-platform ones, according to a BioCentury analysis.

Regulators are also lending support to platform therapies. Just as agencies in the U.S., Europe and China have developed orphan drug designations and accelerated approval pathways to support the development of novel therapies in indications with unmet need, so too are they considering similar approval pathways for novel platform technology assets.

FDA’s approval of Omicron-specific mRNA boosters in the U.S. without in-human trials following the success of the first mRNA COVID-19 vaccines (monovalent and investigational bivalent) is a case in point.

Despite all this progress, however, platform companies overall have exhibited less market capitalization growth than non-platform ones, perhaps reflecting some lingering doubts as to their full potential. Those doubts could well evaporate if platform technologies continue to accumulate successes in the clinic and more platform-based drugs are approved.

Alnylam, which has commercialized five therapies, was valued at $25 billion in December 2022, putting it among the top 5% of all listed biotech companies by market capitalization.

Important too, however, will be evidence that any given platform technology can be applied to other use cases — for example, that mRNA can be used as a therapeutic. To generate that kind of evidence, more investment and more time will be required.

The stakes are high, as new cell and gene therapies, precision medicine, and new delivery methods will all rely in part on platform technologies for their success. Hence, if investments are forthcoming and platforms can continue to demonstrate their worth, they could find themselves at the core of the next generation of life-changing therapies within a decade.

AI-driven drug discovery

AI-driven drug discovery is itself a platform technology but presents a special case study, not least because early expectations for the technology have been so high.

Many in the biotech industry already believe that AI-driven drug discovery will reduce the disease burden of patients by accelerating drug development and reducing the cost. Others go further still, anticipating it will uncover complex mechanisms and therapeutics that humans alone cannot, aided by the promise of generative AI and other foundation models.

VC investments into AI-driven drug discovery companies have surged on the back of such expectations, helping to spawn a 5.5-fold increase in the number of new AI-driven drug discovery companies between 2011 and 2021 (not shown), and a 10-fold increase in AI funding between 2015-2021, according to McKinsey’s analysis.

These companies fall into three broad groups. The first focuses on therapeutic design, using algorithms to identify targets and create drugs to modulate chosen targets. Most biotech companies working in this area do so in partnership with large biopharma companies such the partnerships between BenevolentAI S.A. (Euronext:BAI) and AstraZeneca plc (LSE:AZN; NASDAQ:AZN), and CytoReason Ltd. with Pfizer Inc. (NYSE:PFE). Only 15% have their own, early-stage AI-driven pipeline.

The second group focuses on AI-led development, which includes auxiliary preclinical services as well as methods to expedite clinical trials by, for example, streamlining trials, forecasting the probability of success, modeling twin clinical trial arms to reduce patient enrollment, and leveraging precision genomics for targeted patient recruitment. A third group of companies covers both design and discovery.

Early results in both fields have been promising. Though the data exhibit significant variations, they suggest AI-guided drug discovery could cut the time it takes to submit an IND to 3-5 years from the 6-10 it often takes using traditional methods.

Insilico Medicine Inc., for example, designed and entered a novel therapy into Phase I trials within 30 months, while AbCellera Biologics Inc. (NASDAQ:ABCL), partnering with Eli Lilly and Co. (NYSE:LLY), used machine learning to identify a mAb as a therapy for COVID-19 in four months.

Importantly too, regulators have begun to accept AI as a tool for innovation, easing its likely integration into company processes. EMA, for example, recently approved Unlearn.AI Inc.’s platform to simulate control arms for clinical trials.

This progress leads us to the view that AI is evolving towards playing a focused role within the industry, with most companies using AI for drug development to some degree, helping to de-risk and accelerate the process.

Some biotech leaders are skeptical that it will go further and come to play an outsized role. But others are optimistic. They believe the breadth of AI algorithms being developed and early evidence of their success will, over time, lead to measurable, proven impact that makes AI integral to drug discovery. Indeed, AI will become a commodity rather than a differentiator for developers.

In a 2022 interview, Daphne Koller, CEO of insitro Inc., told McKinsey: “[Within 15 years,] it’s going to be more akin to computers as a tool than it is to combinatorial chemistry, in the sense that it will touch every single facet of how we discover and develop medicines, and accelerate and improve every single one of them.”

Other proponents of AI-drug discovery see a day when it will outperform humans. “The algorithms can get better over time and are constantly learning,” said Molly Gibson, co-founder and chief strategy and innovation officer at Generate Biomedicines Inc. “You could then start to program therapeutics versus discover them. Nature has given us this huge set of beautiful proteins to learn from, and it’s given us the rules that have been discovered through evolution. We can learn those rules, extract from them, and generate proteins that have never existed before.”

Global clinical trial footprints

To accelerate drug development, some biotech companies are expanding out of their traditional markets in Europe and the U.S. to conduct clinical trials into new geographies.

The move is explained by an increase in the number of trials conducted and a doubling of the number of patients participating in them since 2010, with the numbers growing fastest in oncology and CNS.

This has made it harder for companies to find sufficient trial participants, particularly given increasingly strict enrollment requirements such as certain biomarkers associated with precision medicine. The result can be longer enrollment timelines that ultimately delay patients’ access to new drugs. Patient recruitment timelines for oncology and CNS Phase II and Phase III trials take an average 20 months longer than first forecast, for example.

A global clinical trial strategy that accelerates access to more patients could help overcome such delays as well as reduce costs. Development costs alone can be upwards of 80% of the cost to bring a new drug to market, and some countries such as Australia, China and South Korea often have lower investigator costs than the U.S.

Reducing development costs — and thus changing the overall commercial business case — can be another approach to expanding patent access. A global strategy would also help ensure trials include a more diverse set of patients, thereby producing data, and ultimately therapies, more relevant to them.

In a Fireside Chat at the 2022 BioCentury-BayHelix East-West Summit, John Oyler, CEO of BeiGene Ltd. (NASDAQ:BGNE; HKEX:6160), suggested that companies that have long recognized the need to put patients first now need to adopt a “patients without borders” mindset too.

Relatively few biotech companies currently conduct global clinical trials, which means the approach has had limited impact on overall drug innovation and development timelines thus far. Some biotech companies may be hesitant to adopt a more global approach because of the recent economic downturn. For others, capabilities are a limiting factor, as many conduct trials with the assistance of CROs and other partners who may not operate globally.

In the longer term, however, establishing a global clinical trial footprint is a strategy few biotech companies will wish to ignore. Beside addressing the growing challenge of finding trial participants, it has the potential to cut trial enrollment timelines, perhaps by more than six months, and put patients from around the world at the center of drug development.

That would be outsized impact indeed.

Progress for patients

It is important to bear in mind the ultimate goal of all these developments: better therapies brought to more patients faster than before.

Platform technologies, AI-driven drug discovery, and global clinical trial footprints all hold great promise, be that by driving innovation or by helping ensure an increasingly diverse set of patients have access to the treatments that result from innovation. We cannot yet know their full potential.

But progress to date is surely evidence that there is more to be made.

This article is based on insights from the 2022 BioCentury-BayHelix East-West Summit, McKinsey & Company's presentation at that summit: "Creating Breakthroughs: What Will Define Successful Biotech Companies of the Future?” and interviews conducted by McKinsey with leaders in the biotech industry.

Olivier Leclerc and Franck Le Deu are senior partners in McKinsey’s Southern California and Hong Kong offices, respectively. Rajesh Parekh is a senior partner in McKinsey’s Bay Area- Silicon Valley office, where Jennifer Heller is a partner. Elizabeth Rowland is an associate partner in McKinsey’s Philadelphia office.

Signed commentaries do not necessarily reflect the views of BioCentury.