With development cycles becoming longer and longer, trial complexity increasing and greater scrutiny being placed on the economic value of new treatments, pharma R&D business models are under significant pressure to improve efficiency.
In an industry survey of pharmaceutical executives and professionals undertaken by ICON, the challenges most frequently cited are:
These operational issues reflect the difficulty of designing studies that address critical patient and investigator needs, as well as evolving regulations.
Patient identification and recruitment, and risk-based approaches to study monitoring, are expected to have the most impact in transforming the efficiency, speed and productivity of clinical development.
Declining pharmaceutical R&D efficiency and the resulting deterioration in return on investment is largely driven by lengthening development cycles. These, in turn, typically involve increasing trial complexity and regulatory approval delays. These complexities and delays are symptomatic of deep structural changes in therapeutic markets that conventional clinical trials are simply not designed to address. These changes include smaller targets, personalised medicine and value-based care.
Driven by scientific advances in areas including biochemistry, genomics and biomarkers, the market for new therapies has moved towards targeted therapies and orphan indications. The smaller potential markets mean the R&D enterprise - and clinical trial designs and procedures - must be tightly focused on patient needs, relevant clinical and research expertise, and maximising efficiency in demonstrating safety and efficacy.
New product offerings target specific biomarkers, such as biologic chemotherapy agents, or even individual patients, such as CAR-T immunotherapy. Similarly, therapies that combine mobile sensors and devices with drugs and delivery devices require evidence of real-world efficacy and safety that cannot be generated in a controlled environment.
In addition to efficacy and safety, clinical trials increasingly must demonstrate a meaningful impact on patients' lives. This is particularly true for high-cost therapies targeting smaller patient groups. Screening patients to identify potentially better responders and linking payments to individual patient outcomes are among the measures payers are negotiating with sponsors to ensure they are getting value for the money they spend.
Emerging technology capabilities are expected to play a vital role in transforming clinical trials - including leveraging big data and predictive analytics. Integrating study and electronic health records may increase data collection reach and efficiency, and help better integrate trials into clinical practice.
Patient-focused technologies, including mobile sensors, smartphone apps and telemedicine, are seen as ways to collect richer patient data, develop new end points and help design novel kinds of trials that may better demonstrate realworld clinical and functional value.
While the technical challenges of applying new technologies - such as big data, AI, and wearables and mobile devices - to clinical trials are significant, their value already has been confirmed in many studies, saving millions in development costs. They make possible innovations that are fundamental for transforming clinical trials, such as seamlessly combining phase I and II of clinical trials, developing novel patient-centred end points, and collecting and analysing real-world data.
The cost pressures on drug development are driving the search for savings. While large-scale operational efficiencies are being instituted in many pharmaceutical organisations, efforts need to be integrated if they are to be effective.
There is a growing understanding that improving R&D efficiency and return on investment will require a holistic approach to transforming trials, rethinking and redesigning the trial product itself and the enterprise that supports trials from the ground up. ICON is addressing this need through its Transforming Trials initiative.
