Parthenon Therapeutics founder, board of directors at multiple biotechs, Inst. Experiential Artificial Intelligence Professor Northeastern U
As recently as two decades ago, the clinical trial success rate for cancer drug approval—entering phase one and ultimately receiving regulatory approval for launching onto the market—was about 1 in 10.
Since then, there’s been significant advances in both our understanding of cancer biology and resistance mechanisms catalyzed in part by disruptive technologies such as high-speed sequencing, immunotherapy, cell therapy, epidemiology and preclinical models. This has helped us invent novel therapies and continue our battle against this insidious disease. Indeed, we now know far more about a vast array of devastating diseases than at any time in history.
The result? No change! We are still stuck at no more than 1 in 10 drugs tested in early-stage clinical trials making their way to cancer patients, and the track record for non-cancer therapeutics perhaps has trended better in some instances compared to oncology, but still not faring much better.
I am a company builder, leader, investor and board member with a focus on building biotech companies and teams with humanist values at their core. I’ve founded a number of companies looking to advance life-changing therapeutics against diseases inadequately addressed by our current approaches. In my view, we need a new approach when it comes to impact and efficiency.
The Impact Of Innovation
Paradoxically, we are witnessing an explosion in life sciences data and technologies, fueled in part by innovations in capturing big data and more efficient processes for extracting actionable insights including AI and cloud computing. The explosion in data makes it more fascinating—and challenging—to manage that inflow. Data science and artificial intelligence have now all become buzzwords and pillars in the biopharma industry.
But, if the past is prologue, much of these data will never have a direct impact on patients. Early studies that generate headlines excite the scientific community and give hope to patients and advocates but rarely make it into development, and even those that progress to a late stage often fail, unable to withstand the rigors of the clinical trial environment.
Expanding Skills, Building Moral Leadership
Preclinical research is often limited by nonhuman models and the difficulty of extrapolating safety and efficacy data to humans. But the rate of preclinical translational impact into successful clinical impact speaks to the need for increased training in methods and skills that can provide greater predictability for successful drug development.
I suggest scientists across the life sciences cultivate skills in bioinformatics, generative AI and systems biology for unrestrained hypothesis generation and testing and achieve greater clarity and confidence on which research to pursue and to deliver above average probability of success. This can start with upskilling even after graduation by leveraging some of the emerging academic platforms or continuing to reshape our training programs.
While we can expect that all research should be reproducible and impactful, it is also unrealistic to expect that all research should have the same time frame for real world impact. Even good ideas can fail. But when up to 90% of early biological research is not reproducible by the industry and/or results can’t be reliably validated, then I think we need to question the full impact of that research, and the process by which it found its way into a translational engine.
Addressing this “preclinical reproducibility crisis” is both simple and difficult: I suggest we train and incentivize the next generation of scientists to understand the realities of what it takes to develop a successful and impactful novel medicine for patients, to appreciate their pivotal role in the value chain, and to ask themselves whether their idea will help patients—or potentially harm them—before investing time and money into wasted effort.
Let’s focus more on “what is the unmet medical need?” What is the clinical utility of “a great new scientific idea” if the medical need has already been satisfactorily addressed, leaving little scope for a new approach unless it is substantially superior to the current standard of care?
But I think training the next generation of scientists needs to go beyond expanding scientific skills to also include a focus on moral leadership where we ask ourselves the most meaningful questions upfront: Does our work have the potential to help patients? Will it harm them? And let’s use these questions as the foundation for our professional values, informing the work we do, the criteria we set for our research, and the integrity we demonstrate when we quickly jettison bad ideas and move on. Let’s re-create an environment that allows a robust debate about data—i.e., emphasizing the scientific method as practiced for hundreds of years.
Should Scientists Take An Oath?
I believe we should go even one step further with a certification program that incorporates mathematical life sciences, quantitative modeling, computational science, pharmacology, and leadership and ethics. The certification could even be framed within a “scientific oath,” not dissimilar to that taken by other professionals such as physicians. We could also implement a new generation of “board” or “bar” exams administered as a requirement for meaningful and responsible execution of work.
It seems that Gen Z is ready to take us on. A 2022 survey by Deloitte Global shows that Gen Z prioritizes working for organizations that are supportive of making their voices heard and that are committed to driving change. Now, it’s our turn as scientific leaders to build rigor and structure in our training programs and corporate cultures to support and mentor their ideals to create environments that foster genuine scientific debate and critical scientific exchange.
At the companies I’ve founded, we have seen this as essential to fulfilling our mission to create life-changing medicines. By building a multifaceted talent pool, with a diverse and deeper mix of skills and perspectives, and with a strong sense of moral scientific leadership, company leaders can team with our younger colleagues to improve the rates of preclinical success and, importantly, to deepen our impact as scientists. Our stakeholders and patients deserve nothing less. Time is of the essence.
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