It costs $2.5 billion to bring a drug to market, and every dollar delays getting much-needed medicines to patients. Pharmaceutical sponsors and industry service providers continue to seek innovative ways to improve and accelerate clinical trials. Regulators are also looking for innovations to advance the use of real-world evidence to support the development of drugs and biologics.
This focus is leading the industry to create a more technology- driven environment for clinical research. Whether you consider advances in new therapies and diagnostics, efforts to improve safety and efficacy in clinical research, or strategies to accelerate development while reducing costs, emerging technology tools and platforms are playing a critical role. These technologies are creating efficiencies that help lower development costs, fueling more research and development growth, and most importantly, bringing new products to patients more quickly. But these new technologies alone aren’t fuelling innovation – it’s how these technologies are leveraged.
Here are seven innovations accelerating clinical research:
1. Data-driven analytics and insights improve trial design and planning
Gaining access to non-identified global patient data sets and expertise to design machine learning algorithms to mine this data enables use of evidence-based insights to shape protocols, enhance site identification and selection, and expedite patient recruitment in ways that were never possible before. Traditionally, drug trial sponsors have relied on investigators’ relationships and estimations from previous trials for site selection. However, this approach lacks accuracy, and sites often overestimate their potential patient pools.
When sponsors have access to non-identified global patient data sets, they can use analytics to determine where target patient populations are located before they select trial sites, which speeds recruiting and avoids the protracted timelines and waste related to underperforming sites.
2. Real-time data feeds and supported analytics capability drive better trial execution.
Integrated workflows, portals, patient-facing e-tools (eg, eConsent), mobile apps – supported by real-time data feeds, integrated systems, and coupled with analytics – make trial execution progress visible. This improves information exchange for patients, sites, contract research organisations (CROs), and sponsors, and provides
actionable insight to improve speed and quality of trial execution. Investigators use these specialised platforms and apps to interact with sponsors and patients. Examples include electronic consent, which supports better patient understanding of trial protocol and gives sponsors real-time visibility to critical activities occurring at trial sites. Mobile apps support collecting site information and reporting site status to sponsors and enable workforce efficiencies in the field.
3. Predictive analytics improves risk monitoring
When sponsors leverage artificial intelligence (AI) and machine learning to analyse multiple non-identified global healthcare data sets, they can make evidence-based predictions to improve decisions at every stage in the development and commercialisation process. For example, risk- based monitoring and analytics platforms use advanced and predictive analytics to mitigate study risk while improving the speed and quality of operations. These platforms provide a central repository for data that can monitor safety trends across sites, subjects and regions, to make predictions about site performance and patient response. This allows investigators to proactively identify and mitigate safety risks and to customise allocation of monitoring resources rather than spreading monitoring resources evenly across every site regardless of performance. This reduces error rates and source data verification backlog, while streamlining data entry and accelerating database lock.
4. Wearables deliver more data faster
Connected devices provide access to new forms of patient data in real time, while putting less burden on the patient to attend more on-site visits. These data streams are changing the way investigators monitor patients, which increases the speed with which they can detect safety events and allows site staff to proactively monitor patient behaviour and promote adherence to treatment regimens. Additionally, these devices produce important digital biomarkers to predict the incidence of disease or other adverse health conditions. Consider the adoption of continuous glucose monitors in diabetes research; these devices capture hundreds of data points each day, enabling clinical investigators to track the patients’ glucose levels around the clock rather than relying on occasional Haemoglobin A1C needle-stick-tests. Investigators have more data to consider and more context for determining things like whether a patient’s glucose levels are trending up or down and how long they have been in or out of range.
5. Digital biomarkers offer new benchmarks
Digital biomarkers can include both user-generated physiological and behavioural measures collected with the built-in sensors and processing units of digital devices, such as smartphones. This approach enables the gathering of a wide range of data and allows researchers to gain better patient insights.
For example, devices like asthma inhalers are evolving into smart medical devices with attached or built-in digital sensors capable of measuring and tracking usage and adherence. These digital measures provide investigators with new benchmarks to identify, assess and track patients. With home monitoring and mobile Health devices, patients’ physiological, behavioural and environmental data can be collected and analysed in real time to predict asthma episodes for individual patients. The ability to capture this information in a real-world setting allows physicians to intervene and offer patients the help they might need as they need it.
6. Virtual trials accelerate research
This innovative model leverages wearable devices, secure online patient platforms, apps and telemedicine in combination with occasional home health visits to allow patients to participate in a trial without having to visit a site or reduce the number of physical visits in the study. The elimination of travel dramatically expands the geography from which patients can participate, which accelerates recruitment and opens the trial to a broader and more diverse patient population – helping sponsors meet requirements for more minority populations in clinical research. Investigators can also leverage apps and devices to ensure patients adhere to medication protocols and remind them if they miss a treatment or survey deadline. This helps drive patient retention and speed of data collection, with lower overhead and fewer manual tasks.
7. AI and machine learning improve productivity
AI and machine learning will impact many areas of clinical development, including safety. As the number of data sources and channels for drug safety reporting continue to expand, the system is being taxed beyond capacity. Compounding this challenge is the growing number of marketed drugs and expanding global use. This increases the cost of pharmacovigilance (PV) and exposes patients to greater risk. In response, PV professionals are implementing a series of AI-driven tools to automate manual reporting tasks, translate unstructured documents into structured formats, and develop algorithms that can automatically review data sets and identify safety signals without human intervention. This enables PV teams to more rapidly identify and address potential risks while lowering the time and cost associated with these steps.
Looking to the future
Technology-enabled innovations promise to reduce time and cost for sponsors supporting the drug development process. However, the real winners are patients. Each of these advancements is making it easier and safer for patients to participate in research while accelerating their access to sorely needed treatments. These tools are also making it easier for sponsors and investigators to engage patients in the research process.
But these benefits are only possible if sponsors have access to advanced digital platforms and non-identified global healthcare data sets, as well as partners with deep clinical and technology expertise. This combination of tools and talent make it possible to drive better, faster, more reliable insights at every stage in the development cycle, which will drive new clinical innovations for years to come.
By Josh Rose
Source: Pharma Times
Avivi joins Bayer fresh off a yearlong stint as chief marketing officer of Advance Auto Parts, which followed about three years spent as marketing chief of another auto parts company, Tenneco. Rounding out her nearly 30-year career in marketing are leadership roles at consumer goods giants Kimberly-Clark and Procter & Gamble.
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