Technological innovations are improving the efficiency and productivity of clinical trials in the central nervous system (CNS) environment.

In August, Novartis launched the first large-scale research study in multiple sclerosis (MS) using Apple’s ResearchKit software, while AstraZeneca announced its collaboration with US biotech company Berg to develop drugs to treat Parkinson’s disease and other neurological diseases using artificial intelligence (AI).

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The use of new technologies such as mobile apps, AI, and wearables has recently become popular in CNS drug development, introducing the use of novel outcomes, increased patient engagement, and reduced patient burden. The traditional research model requires a substantial investment of time and money in designing a study, identifying clinical sites, and recruiting patients, even before receiving any feedback from regulators on the study’s feasibility. Despite some regulatory and operational concerns, new technologies are helping the pharmaceutical industry move closer to the shared goal of making clinical trials more patient-focused.

AstraZeneca’s new collaboration with Berg aims to shorten the often time and resource-intensive process of bringing a new drug to market. The collaboration came shortly after the company faced a serious setback, with the failure of a trial investigating an immunotherapy drug designed to treat lung cancer. The company is looking to speed up the progress of its expanding product pipeline.

In July, GlaxoSmithKline (GSK) announced its new collaboration with AI company Exscientia, with the aim of cutting development time down to a single year. One important attraction of using AI in drug discovery and development is its ability to generate data. Berg is drawing on publicly available data and tissue samples from both healthy and diseased patients, which can then be analysed and combined with patient clinical information for companies to better identify and recruit patients for clinical trials. Using different patient-derived data such as records on tissue / blood tests and clinical symptoms will help manufacturers select only the patients that are most likely to benefit from the candidate treatment.

"Berg is drawing on publicly available data as well as tissue samples from both healthy and diseased patients."

Novartis’ new MS study elevateMS allows participants to contribute using smartphones, which allows them to participate from any location. This provides researchers with access to valuable data regarding the daily challenges experienced by patients. The mobile app was developed by patients, neurologists, and disease advocates, and was built on the Apple ResearchKit platform, first used by GSK in a rheumatoid arthritis study.

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Novartis’ forward-thinking approach of using the mobile app will eliminate the need for clinical visits and is expected to widen the population that can participate in the trial. Together with the increasing innovation of wearable technologies, the use of mobile apps in clinical trials will allow manufacturers to collect clinical outcome data directly from patients, making trials more cost-effective and reflective of real-world situations.

Rapid advancement of new technologies in research and development (R&D) will likely help manufacturers increase sales in the next ten to 15 years, and will bring long-term benefits to the industry as a whole. This is particularly so for drug development targeting the CNS, where there are significant challenges involved in bringing products to market such as high attrition rate, slow rate of disease progression, long and costly trials, and difficulty in tracking patients’ clinical outcomes.

As access to data and computing power continues to improve, we are likely to see more innovations in the coming years, which may finally tackle manufacturers’ long-term struggle with productivity in CNS research.