Dare to Dream Ball

As development moves towards combination and sequencing strategies, trial design must also clarify whether the objective is to establish the value of a regimen or the incremental contribution of an individual component. Choices around background therapy, co-initiation versus add-on design, comparators, rescue rules and Estimands should be made accordingly, with benefit interpreted against the additional safety, treatment burden and cost that combination treatment may bring (Solitano et al, 2025).

We sat down with our colleague Claire Newton to learn how more than 25 years of developing therapies for rare and serious diseases have shaped her approach to drug development — because while the science, regulatory landscape and development pathways may be complex, the goal remains simple: getting the right therapies safely to the patients who need them. For more than 25 years, Claire Newton has worked to turn ambitious science into therapies for patients living with rare, ultra-rare and serious diseases. But across gene and cell therapies, siRNA and biologics, she has seen that great science is only the beginning — development programmes must also navigate complex regulatory pathways, manufacturing challenges, limited patient populations and difficult decisions about risk. That experience has shaped Claire’s approach: keep the patient at the centre, while giving teams the clarity, pragmatism and pace needed to move promising therapies forward. At Adnovate, she brings that perspective to complex development programmes, helping cross-functional teams make informed decisions and build development strategies that can ultimately deliver for patients.

In partnership with Alun Bedding, PhD — a consultant and executive coach with 35+ years in pharma leadership — we sat down for a candid Q&A on where clinical development is headed. Alun talks through why Bayesian methods are still misunderstood by sponsors, and what separates the organisations that use them well from those that don't. He also makes the case for keeping patients in the room during trial design, arguing that a trial which finishes recruiting with imperfect statistical power can ultimately serve patients better than a well-powered trial that never completes.