Coronado’s CSO champions data-driven innovation in clinical trials
At the helm of Coronado’s scientific strategy, Professor Visser-Rogers envisions a data-driven future powered by innovative methodologies and emerging technologies. Her approach emphasizes not only precision medicine and patient-centric clinical trials but also the critical integration of AI, advanced analytics, and adaptive regulatory frameworks to meet the industry’s pressing challenges.
Vision for Coronado Research: As the new CSO, what is your vision for the future of Coronado Research, and what strategic goals do you aim to prioritize in your initial months?
Data is at the heart of the vision for Coronado Research. The therapeutic development process generates a vast amount of data and metadata, and by better exploiting this, we can optimise the process creating real benefits for patients. We now have the technology to access and
manage this data, and the tools and novel methodologies to gain actionable insights from it, joining the dots between the various stakeholders. At Coronado Research, we are dedicated to advancing pharmaceutical research through innovative clinical trials, providing expert-driven advice and support. We are creating developmental processes that match the latest science, placing data at the centre.
The first challenge that we face is that some Sponsors are struggling to understand how they can deploy these latest innovations to maximise the value of their data. They have heard terms such as ‘Artificial Intelligence’ and ‘Machine Learning’, but don’t know where to start with them. Our initial goal will be to work with these Sponsors to help them develop their data and technology strategies, so that they can start to see the benefits that this evolved paradigm will offer.
Navigating Challenges in Drug Development: What do you consider the most significant challenges currently facing drug development, and how will Coronado’s strategies address these?
The current model is becoming increasingly unfit for purpose. While it has delivered some amazing breakthroughs, therapeutic development is currently set up for the blockbusters, the revolutionary treatments with huge global markets. As science changes, especially with advances in genomics and biomarkers and a growing emphasis on rare diseases, we are seeing this blockbuster model being replaced by a more targeted, precision-based approach. This new paradigm can mean lower failure rates and faster development times as we target the smaller, more
defined populations that are most likely to benefit, but there are significant challenges that Coronado Research is working to address.
These new trials will have an increased complexity and small target populations mean that the market for new treatments is shrinking, which coupled with increasing costs for drug development, can make these programs cost prohibitive. Digital health, Artificial Intelligence, novel analytical methodologies, and real-world data (RWD) will optimise development, breaking away from the ‘one-size-fits-all’ model and providing targeted therapies for those who need them most.
Trends in Precision Medicine: How is the shift toward precision medicine transforming clinical research, and what role do you see Coronado Research playing in that transformation?
The shift towards precision medicine is forcing clinical trials to focus on smaller, more defined patient subsets, rather than large, heterogeneous groups. This has led to the rise of biomarker driven trials, where a patient’s genetic profile is a key criterion for inclusion; adaptive trials, allowing flexibility and real-time modifications; and master protocols, which test multiple therapies for different indications within a single framework. Precision medicine also relies on the integration of complex data, which can include genomic data, electronic health records, and patient-reported outcomes. Real-world evidence (RWE) can supplement and complement clinical trial data in these small cohorts, contributing to the decision-making process through understanding prevalence, providing control arm benchmarking and enrolment feasibility estimates, as well as serving as a single-arm trial comparator. Rather than applying “one-size-fits-all” approaches, precision medicine requires specialist knowledge and bespoke solutions. Coronado Research is forging strong partnerships with biotechs, charities and patient interest groups, and
academic institutions, placing us at the forefront of these innovative and patient-centric data-driven, technology-enabled approaches.
Regulatory pathways are also pivotal in the development, approval, and accessibility of precision medicine therapies, often requiring a more adaptable approach. Expedited approval processes are available for therapies that address an unmet need and are particularly helpful in precision medicine where therapies may be aimed at rare genetic mutations or specific biomarkers. Conditional approvals also allow therapies to brought to market, while further data, often RWD, is collected to refine the therapy. This approach is valuable in precision medicine where patient populations are small and carrying out large-scale clinical trials is challenging (or, in some cases, impossible). Coronado Research provides experts across regulatory, data, and market access services, and provides a joined-up approach across the entire research continuum, looking at the end-to-end process and putting data at the heart.
Utilizing Emerging Technologies: How is Coronado Research leveraging new technologies like AI and machine learning in its research, and what potential do you see in these technologies for future clinical applications?
Large volumes of data are produced in the healthcare arena daily, and Coronado Research provides expert domain expertise to leverage new technologies that have the capabilities to gain insights and generate hypotheses from this data to optimise the drug approvals process. One example is in trial design and document generation. As biopharma looks to increase efficiencies, using the optimal trial design is of paramount importance. AI will be able to learn from prior trials to understand which designs have been the most successful and have been approved
previously by regulators, identify target populations, and select patients who have a higher probability of having a measurable endpoint. Generative AI can then create content using learned patterns based on training data, quickly drafting and refining clinical trial documentation such as trial protocols. Another example is in intelligent risk-based monitoring where advanced analytics, predictive modelling, and AI are leveraged to identify and mitigate risks in real time, improving data quality and enhancing patient safety, making the process more efficient, accurate, and adaptive to evolving trial conditions.
But these advances depend on the human-in-the-loop to maximise their impact. Systems are reliant on the humans that design, develop, and implement them. Technology will always rely on human knowledge to operate at its full potential whilst remaining ethical, responsible, and safe. As tasks are increasingly shifted to AI, there will be a need for specialised personnel to review outputs and ensure quality.
Role of Advanced Analytics: Can you share your perspective on the impact of advanced statistics and analytics in clinical trials and how Coronado plans to harness these tools?
As the science advances, new treatments develop, and the associated patient experience within different therapeutic areas evolve, so must clinical trial designs. Traditional trial designs are being replaced by more complex approaches that reflect the increasing sophistication of therapies and available methodologies.
Regulators have been increasingly supportive of complex and innovative clinical trial designs, recognising that they have the potential to improve efficiencies and extract the most value from data, which enables faster access to treatments. The FDA has produced various guidance documents such as externally controlled trials, adaptive designs, master protocols, and complex innovative trial designs. It has also introduced the Complex Innovative Trial Design Meeting Program with the goal of facilitating and advancing the use of complex adaptive, Bayesian, and other novel clinical trial designs. Historically, clinical trials adhered to a rigid structure, often using single-treatment, parallel-group designs, but this exciting regulatory shift marks a significance transformation in the way clinical trials will be conducted going forward. Coronado Research brings together a team of seasoned professionals who are thought leaders at the forefront of new developments, experts in complex clinical trial design and novel methodologies.
Patient-Centric Approach: How does Coronado Research integrate a patient-centered approach into its drug development programs, and what new initiatives are you exploring to further this commitment?
The approach to patient engagement within clinical trials is rapidly changing and the COVID-19 pandemic has only accelerated this, with an increased interest in data, analytics, and the clinical trial process. As the complexity of innovative drugs increases and the way we capture patient outcomes changes, patients are no longer viewed as anonymous ‘subjects’, but rather legitimate stakeholders who can make positive contributions. Collaborating with patients enriches clinical trials through understanding their preferences and lived experiences.
The way we engage with patients in clinical trials is also changing with a move towards technology-assisted patient outcome collection, bringing
the clinical trial process into patients’ own homes and local surroundings. These initiatives commonly fall under the banner of Decentralised Clinical Trials (DCTs) and offer the opportunity to increase diversity and inclusivity, ease recruitment, enhance retention, and decrease costs. But they are not without their challenges. One of these being the quality of the data captured, with an increased risk of bias and ease of manipulation. In traditional clinical trials, researchers have a higher level of control over participants and the data that they provide but technology enabled trials increase opportunities for protocol violations and data fraud. Coronado Research will be the “humans-in-the-loop” to ensure that these potential pitfalls are identified, minimised, and accounted for in analysis.
Mentoring Future Leaders: Mentorship has been a key part of your career. What advice would you give to young scientists and researchers aiming to contribute meaningfully to clinical research?
I would say that there has never been a more interesting and exciting time to work in this industry. Regulators are embracing advances in science and technology, and we are seeing a change in the way patients interact with clinical trials. We are just beginning our journey into this evolving landscape and are only starting to glimpse the potential of technology and advanced analytics in therapeutic development.
I am a technology adopter; AI and machine learning certainly weren’t on the syllabus when I was an undergraduate. As we see technology natives moving through our industry, people who have been fully immersed in technology from the start and have a natural fluency in using digital tools, I think we’re going to see more and more of what technology can offer our space, and I can’t wait to see it. So, my advice would be this: pay close attention to new developments and review emerging used cases, but be wary of hype and remember that as technology advances, the human-in-the-loop is going to be more and more important to optimise its impact and safeguard its integrity.
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