Clinical Trial Solutions: Technology the Key to Improving Efficiencies and Retention in Clinical Trials

In Clinical Trials by Barbara Jacoby


The use of technology has become ubiquitous in clinical trials as the industry looks to streamline and improve processes.

Most pharmaceutical companies and contract research organizations have adopted technology solutions, including electronic data capture solutions and clinical trial management systems to increase efficiencies, reduce costs, and improve the patient experience. These solutions have been instrumental in improving clinical trial processes. Past reliance on paper records made for a cumbersome, time-consuming process by making data management highly complex. However, many of the biggest issues remain — in particular, recruitment and retention of patients.

Patient-Centric Trials

One of the big problems for clinical trials is the high rate of patient drop out. Improved retention calls for a more patient-centric approach and technology is integral to putting patients at the center.

The use of electronic clinical outcomes assessments (eCOAs) and electronic patient reported outcome (ePRO) solutions to capture patient data has been found to improve compliance levels. This is because electronic devices can be used to motivate and engage patients and because ePROs simplifies the questionnaire process for patients.

Gathering patient feedback on the overall experience is another key aspect to patient engagement. This can be done through social listening strategies to monitor online conversations. Social listening allows sponsors and CROs to learn what’s being said about the trial and gives immediate insight into how patients are responding to information about the specific therapy, medication for a disease state in general, and new diagnoses for a disease state.

Digitization and the expansion of the market to start-ups, as well as technology giants, have led to an explosion of patient-centric technologies for clinical trials.

Examples include:
An app developed by a University at Buffalo researcher that lets patients quickly assess clinical trials, including the time involved, and if there is a study close to them.

An app from Geospace that lets providers match patients to clinical trials in real time.

The use of wearables also allows clinical trial sponsors and CROs to gather data without requiring patients to visit the trial site every week. Perhaps the best-known wearable now is the Apple Watch, which received FDA approval in 2018 for two applications — an EKG and a pulse monitor.

A growing number of companies are offering apps and wearables to assist with clinical trials. For example, Novartis is working with Science 37, which designs decentralized clinical trial technology, to use digital technologies to enhance clinical trial participation. The technology allows some aspects of clinical trials to be conducted from the patient’s home or from a local doctor’s office.

Another company using technology to enable clinical trials to be done remotely is AOBiome, which also worked with Science 37 to conduct a study of patients with mild to moderate acne from their own homes. Patients were loaned an iPhone and given a data plan and connected to dermatology experts via a Network Oriented Research Assistant (NORA) platform.

Charting a New Course

It’s well known that bringing drugs to market is expensive — as much as $2.9 billion according to the Tufts Center for the Study of Drug Development — and time-consuming. Complex clinical trials and difficulties in managing data and patients contribute to those costs. Today, advances in AI solutions play an integral role in taking cost out of clinical trials and improving efficiency. For example, AI can be used to better identify the right patients for a trial, which then enables companies to engage with those patients directly. This is made possible first by drawing on key data — from electronic medical records, from physician notes, data from images and scans, and other patient information — then assessing this data against the clinical trial criteria.

A common problem with clinical trials is the protocol design. AI can be deployed to compare large data sets from previous trials to determine similarities and areas of concern and use that information to improve the protocol design of the forthcoming trial.

Adherence to the protocol is another problem that researchers have identified. One company noted that blood samples during monitoring showed that up to 40% of patients don’t take the drug as required, often skipping the drug for up to two weeks.

Facial recognition technologies from companies such as AiCure can determine if a patient has taken the drug. Alerts can be sent to investigators if the drug has not been taken.

For investigators and other site staff, the complexity of inputting data into many different sponsor and CRO systems adds further complexity. Technology that digitizes standard clinical assessment, automates data capture, and shares data across those many different systems vastly reduces the burden on busy site staff.
The use of cognitive technologies can create action steps for clinical staff based on specific protocol requirements, such as tests that a patient needs to carry out. They can also help with setting up patient visits and filling patient data into EDC systems.

And robotic technologies can automate repetitive tasks, which not only saves clinical staff time, but reduces errors. Such tasks include creating standardized contracts such as confidentiality agreements. Once a trial is under way, robotic technologies can be deployed to determine patient data points to be captured in line with the protocol, check for missing data, and highlight inconsistencies. Once the trial has been completed, natural language processing capabilities can be deployed to fill in standard information in the final study report.

AI algorithms can also offer predictive data on a number of important issues — whether the drug will have a positive or negative outcome for the patient, the likelihood of patient dropout, and the likely success of the trial. Technology has been an important driver in advancing the clinical trials market. Next-generation solutions are integral in improving and expanding clinical trial capabilities.(PV)