Tomorrow’s cures are hidden in today’s R&D data. Here’s how to find them.

Emily Whitehead was six years old in 2012 and had suffered from two relapses with acute lymphoblastic leukemia (ALL) when she became the first child in the U.S. to be successfully treated with the then experimental CAR-T gene therapy now known as Kymriah. Whitehead had the kind of response to the therapy researchers dream about, even though it would take five more years for Kymriah to become the first gene therapy to be approved in the U.S.

Between 1972, when Dr. Theodore Friedman, MD, published the first scientific paper about gene therapy, and 2017, when Kymriah was approved in the U.S., the cell and gene segment saw more than 1,800 clinical trials, the creation of 16,000 U.S. patents, the accumulation of more than 35,000 scientific papers and over $4.5 billion in investments in gene therapy companies. While the development of gene therapies for cancer and rare conditions is a major scientific achievement, a 40-year wait is long time for those in need of a cure.

The slow pace of cell and gene therapy development is not an outlier. The average length of time it takes to develop a new drug is 14 years, and that timeline assumes there are no delays due to safety. Delays in drug development stem from the risks inherent in the R&D process—the time and effort spent mitigating these risks means most of the work in life sciences R&D will not result in drugs that reach patients. What’s more, the average cost of developing just one drug can range from $1 billion to $3 billion, according to industry estimates. Unfortunately, this cost is doubling every nine years, a trend known in the industry as Eroom’s Law.

Due to the slow and resource-intensive R&D process, life sciences R&D can only focus on a subset of patients and diseases, which results in substantial inequities in who benefits from new treatments. Less than 4% of private investment in healthcare R&D targets the developing world. And even in developed, first-world countries, most R&D participants are from majority populations. For example, 20% of the Americans who suffer from medical conditions are Black, while they make up only 2% of clinical trial participants. 

Despite the challenges stacked against it, I believe our industry is experiencing a defining moment in life sciences R&D. We may be on the precipice of reversing Eroom’s law thanks, in part, to the explosion of data generated by the healthcare ecosystem about human biology and medical science. Recent studies have found medical knowledge is growing at an exponential rate, almost doubling every two to three months. This galaxy of data holds the answers to medicine’s biggest questions—the cures for cancer and Alzheimer’s and hundreds of rare diseases. Life sciences companies likely already have much of the data they need to create tomorrow’s cures—they just need help tearing down the silos where that data resides.

Through our work, side by side, with life sciences companies and our investments in clinical trial design and execution optimization, we have been able to accelerate study enrollment by greater than 10 times and have lowered study costs by tens of millions of dollars. While those first steps have had substantial impact, we recognize we're still a long way from our vision. To achieve our goals we’ve built a strategy around five different pillars—or our five “hows”:

1. By catalyzing scientific innovation to address the most pressing human health needs, through deep scientific capabilities—starting with target identification and working toward creating breakthrough medicines
2. By accelerating drug development and reducing risk, from portfolio to patient
3. Through maximizing R&D participation and value across patient populations and therapy areas with the greatest need
4. Through demonstrating the value of medicines to regulators, payers and providers throughout the life cycle
5. Optimizing clinical practice and patient care through predictive medicine and digital technology

At ZS, we believe these five hows help us build partnerships within life sciences companies and with the broader healthcare ecosystem. With this strategy we can unlock the future of life sciences innovation to drive outcomes where they matter the most. 

The field of biomedical research is undergoing a renaissance of its own, due to an explosion of knowledge about human biology and innovative new modalities. The genomics revolution and the rapid decline in the cost of sequencing has created an abundance of data that can fuel scientific discoveries for decades. The innovative technologies available to capitalize on these discoveries are growing swiftly, as well.

For many years, pharma has had only one or two modalities to work with—small molecule chemistry and protein chemistry. Now there are oligonucleotides, conjugates, cell therapies, gene therapies and stem cell therapies. These discoveries have resulted in an overflowing toolkit of modalities to fix biology, modify biology and change the course of illnesses.

In addition to understanding new modalities and how to use them, there’s been a fundamental change in how research is done. In the past, the field of discovery was driven by biologists and chemists. That work is being done by data scientists and technologists now. In the future, we’ll see life sciences companies developing deep data science and omics capabilities to probe—and program the universe of new biology.

If the advancements in biomedical research really do lead to a revolution in the discovery of new assets, they will need to be ushered through the clinical pipeline much more quickly and efficiently than they are today. Despite significant efforts by regulators to shorten the approval process, clinical trials remain an extremely lengthy process that’s only getting longer. Most clinical trials are needlessly complicated and extraneous amendments often force investigators to miss enrollment targets and timelines.

That’s why life sciences companies can’t continue to conduct clinical trials the same way they always have. Trial designs adopted out of necessity during the pandemic helped demonstrate clinical development can happen more rapidly—and cost effectively—when trial designs are more human-centric, less disruptive to clinical care and lower the burden placed on trial patients. For example, digital and decentralized trials, which leverage the collection of data from patients going about their daily lives at home, have empowered sponsors to look beyond traditional sites and reach a broader community. In addition, platform studies and synthetic control arm studies have successfully reduced the number of patients needed for trials.

While much of the discussion around diversity in R&D focuses on phenotypic diversity, especially race and ethnicity, R&D also needs to look at molecular diversity and ensure representation of all the molecular subtypes of patients.

In ZS research examining diversity in clinical trials, we found patients are eager to join trials, but sponsors are missing opportunities to offer them due to assumed lack of interest. Black patients, for example, are more likely to sign up to participate in clinical trials when shown data about people in their community who are interested in the clinical trial. What’s more, clinical trial sponsors and clinical trial participants also have very different motives for being involved in trials. While sponsors are motivated by their desire to improve existing treatments and contribute to science, patients are driven by personal benefits.

Life sciences companies can also demonstrate their commitment to equity by developing treatments for infectious diseases and illnesses that afflict third-world countries whose residents have a limited ability to pay for them—and ensuring existing treatments are available to all patients. 

When launching a new therapy, it’s easy to develop tunnel vision and focus narrowly on gaining regulatory approval. While regulatory approval is  absolutely a critical step, companies must ask questions about the enriched population to test, how to provide access to the therapy, determine pricing, educate physicians about prescribing and convey benefits to patients. To do that well, life sciences organizations should have a robust integrated evidence strategy.

For example, companies often develop an evidence plan within medical affairs, a real-world evidence (RWE) plan within the RWE team and a payer evidence plan through the global health economics and health outcomes research (GHEOR) team—all of which live in their own silos. If these were all integrated, companies could proactively answer stakeholder questions, focus on meaningful studies and progressively produce relevant and rigorous evidence.

Medical affairs, which is a linchpin between the commercial and development arms of life sciences organizations, plays a major role in facilitating this kind of knowledge sharing. The epidemiologists and informaticians within the medical function could also help broader functions leverage real-world and other data sources to take on systemic, data-driven decision-making processes. As medical science liaisons educate physicians on medicines and their uses, they gain valuable data they can bring back to commercial and development. This crucial feedback loop generates evidence that will ultimately help healthcare professionals and patients.

Imagine a treatment paradigm in which primary care, as a specialty, is as targeted and complex as oncology. Today, oncologists routinely interpret and make treatment decisions based on data such as tumor type, phenotypical factors, molecular characteristics, the patient’s genetics, family history, diagnostic procedures and exams. What could physicians achieve if this level of detail was available for all their patients? How would they know which drug to use, or how to use it, to treat a given condition? That, we believe, is a question life sciences companies will be equipped to solve.

We envision a future state of life sciences R&D where, when new therapies are launched, they'll be accompanied by diagnosis and patient identification algorithms and data to support dosing, treatment duration and potential therapy combinations. While developing innovative new medicines is important, one of the most important ways the industry can drive outcomes is by making sure those treatments are used on the right patients in the right way.

During the pandemic, the life sciences R&D industry proved it was willing to take risks, adopt innovative clinical trial designs and remove barriers to data sharing with internal stakeholders and with the broader R&D ecosystem. To sustain this advancement far into the future, leaders must be comfortable with change—including changes in how clinical trials are conducted, with how they use and share data, as well as how they operate as part of the healthcare ecosystem. If leaders get stuck in the old way of doing R&D—ways that are slow, expensive and risk averse—they’ll miss out on a historic opportunity to participate in our new data-driven world.

There are three steps life sciences leaders can take immediately to help them meet the moment:

1. Leaders must dismantle internal and external silos to participate more fully with the interconnected R&D ecosystem. That could mean creating or strengthening partnerships with academic research organizations, biotech companies or consortia across the life sciences industry.
2. Leaders should embrace and advance data-driven decision-making and avoid relying on past experience to guide decisions. This may require investing in technology and retraining and upskilling people to promote cross-functional expertise and relationships.
3. To deliver health outcomes for all, life sciences leaders need to involve more stakeholders, patients, investigators and coordinators in the drug development process. Leaders cannot risk becoming too insular; they must stay connected to what’s happening in healthcare more broadly to build assets that deliver positive outcomes to patients.

We can’t say for certain what the future will look like, but we do know  change is a constant. For life sciences R&D to deliver true innovation, it must be agile enough to adapt to change constantly and embrace it. As life sciences leaders prepare for the future, ZS will continue to work with our partners in the healthcare ecosystem to help deliver effective, sustainable and accessible solutions: new treatments for rare diseases, affordable ways to deliver existing treatments to larger populations and technologies that make innovation feasible for companies large and small.

This article includes contributions from leaders on ZS’s R&D excellence team, including Sarah Jarvis, Qin Ye, and Mike Martin.