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Tracking the Digital Trends in Healthcare
Transformation of the clinical trials through digital technologies have given rise to digital patients
September 26, 2022
13 Min Read
Image courtesy of kaarle dev / Alamy Stock Photo
Nandha Kumar Balasubramaniam, Chetan Deshpande, Patrick Bangert, and Christoph Russmann Juergen Kuebler,
Clinical trials are the quintessential elements in the regulatory approval of a drug or a medical device that is critical for patient-centric care. The traditional methods for clinical trials from study design, and patient enrollment to sharing, and submission of clinical trial data to regulatory authorities for final approval are complex.
These inefficient, time-consuming, and costly processes, can be streamlined and made efficient through the increased adoption of Digital Technologies (for recruitment & retention, data collection, and analytics), which has led to the evolution of Digital Clinical Trials (DCT), including Decentralized Clinical Trials and Virtual Clinical Trials (VCT).
The pandemic has helped to expedite the adoption of many digital technologies for clinical trials, though many challenges remain.
In this article, we will highlight the current trends, opportunities, and challenges with the adoption of digital technologies for clinical trials.
Based on a report from BCG in 2022 (Digital Redesign for Clinical Trials), it is estimated that pharma companies spend more than $50 billion annually on clinical development.
Additionally, the clinicaltrials.gov website indicates that there are 423,000 registered studies as of July 2022, of which approximately, 100,000 are active, and planned studies. Of the total, 41% of trials are focused on drugs and biologics, while 10% are focused on medical devices, with the remaining focused on behavioral, and surgical procedures.
There is an increase in the number of clinical trials by sponsors, and despite the constraints introduced by the recent pandemic, the number of the clinical trial starts reached an all-time high of approximately 37,000 in 2021. Considering a large number of clinical trials and the amount spent on such trials by pharma and medical device companies, it will be critical to review the opportunities for transformation of clinical trials by the adoption of digital technologies, as well as the challenges, and outlook.
The traditional clinical trial is a complex process that necessitates patient travel to on-site locations, and to be physically seen by healthcare professionals to stay compliant with the trial requirements. Due to inconvenience caused by the travel to distant sites (patients), along with the costs (trial sponsors), patient dropouts are a major concern. For the same reasons, the traditional trials fell short in recruiting patients from diverse geographies, communities, and age groups. To overcome these challenges, Digital Clinical Trials were gaining momentum even before the onset of the COVID-19 pandemic but gained importance following the recent COVID-19 pandemic.
For certain kinds of trials, they gained popularity for the collection of routine health data that could be captured virtually.
These trials collected many types of data including safety and efficacy data from trial participants from the commencement of the study to execution to follow-up. DCTs are able to capitalize on the advancements, and increased adoption of mobile technologies (cell phones, wearable watches, glasses, etc), connected devices (monitors, implantables, wearables, apps etc.,), and electronic patient engagement applications (ePROs), and social media platforms (WebMD, belong.life, PatientPoint, etc.,) to conduct the clinical trials from the comfort of the patient’s homes. This patient-centered transition increases the overall efficiency of clinical trials throughout the value chain – study design, site selection, recruitment, monitoring, data management, analysis, and reporting.
Transformation of the clinical trials through digital technologies has given rise to digital patients – those who leverage electronic technologies to improve the efficiencies for their healthcare needs. Adoption of and implementation of Electronic Health Records (EHRs) for capturing the patient’s health data, was considered to be time-consuming by
Healthcare Professions, are considering it to be of immense value in clinical trials. But this captures only 40% of the patient’s health information (Medical History, doctor's Notes, Lab Results, Prescriptions, etc.).
The remainder of the 60% of the data comes from socioeconomic, behavioral, and financial data, and needs to be accounted for in the Electronic Life Records (ELR), as recommended by a Deloitte study in 2021.
In the case of clinical trials, it is important to note that some of the exploratory data on trial participants are not shared with the patients and their physicians and are also not included in the electronic health records (EHRs) of the patient.
Including all this digital data in a trial provides immense benefits to all participants – patients, sites, and sponsors of the digital trials. Overarching benefits include reduction of timelines, cost, and increased access to research studies, and treatments, and providing a platform for successful completion of the study. VCTs offer immense opportunities to expedite clinical trials with increased compliance, however, the use of technologies goes beyond just patient recruitment, and digitizing health records.
Understanding the digital technologies that have transformed the efficiencies across the clinical trials landscape is vital. These advancements include;
Artificial Intelligence/Machine Learning (AI/ML) for Data Insight
Zettabytes of data can be generated in complex clinical trials and the data comes in various formats from simple lab values to multiplex pathology images to gene sequence, and protein data. Processing this data to extract insight is challenging but, can be made possible by leveraging Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL). They speed up the processing time and can unearth problems from historical data, leading to cost savings. Data arising from wearable devices in a continuous streaming manner combined with extraneous parameters, as well as Real World Evidence (RWE), can be analyzed in real-time using AI/Ml/DL algorithms at a rate that is not possible by human involvement.
Moreover, AI/ML/DL can deal with both structured and unstructured data, including image analysis of value for the clinical trials study teams. Digital pathology has been on the rise with the help of AI/ML/DL applications to process complex images in order to gain insights into drug efficacy or resistance mechanism that helps in clinical development. Finally, AI can be used effectively to automate pharmacovigilance and assist with safety reporting of adverse events.
One area that is gaining importance is data mining to identify the golden nuggets to derive a meaningful insight, and disseminate it to the end users. These include; providers (need for drug safety), Key Opinion Leaders (interested in the mechanism of the action of the drugs/devices), Patient Advocacy groups (disease symptoms/side effects), and Medical Information groups (medical affairs interested in clinical trial outcomes). Data mining of structured, and unstructured data, for dissemination, can be accomplished by capitalizing on AI and ML, as well as Natural Language Processing (NLP).
Mobile, and Connected Devices, and Interoperability for Data Collection
The shift to digital clinical trials in which the trial participant’s data is accessed through remote patient monitoring (RPM), was accelerated during the COVID-19 pandemic. According to data published in Forbes Technology report in 2022, it is indicated that 100% of pharma and CRO sponsors stated that Virtual trials are an integral part of their portfolio, and 89% of the same group would run clinical trials at participants’ homes.
This shift in DCT is enabled by the electronic data capture (EDC) through connected/wearable devices, and leveraging medical Internet of Things (mIoT) along with a robust interoperability standards. Benefits derived from mIoT enabled DCTs include; larger pool of participants not restricted by geo-spatial limitations, increased diversity, overcoming limitations of travel to trial sites, better participant retention, continuous collection of data with real-time monitoring, reduced human errors, and seamless trials. The overall outcome is the ability to bring a product faster to market at less cost.
Blockchain for Improving Efficiencies across Supply Chain
Medication delivery for remote clinical trials necessitates that there is a robust clinical supply chain. Blockchain technology that enables sharing of information through a distributed network leading to end-to-end visibility. This in turn reduces wastage and improves clinical trial efficiency. This blockchain technology can assist with the process of ordering, tracking, and delivering drugs and/or devices to a patient at a remote location in a virtual clinical trial. The ultimate advantage is the coordination across the entire supply chain network so that the right drug or device is delivered to the right site, and patient at the right time. Moreover, it overcomes issues related to counterfeiting.
Cloud Infrastructure for Data Management
End-to-end data collection, storage, integration, analysis, and sharing (CSIAS), while protecting privacy, and ensuring data security is a critical element in digital clinical trials. This in turn is enabled through the advancements in cloud computing. High-Performance Computing (HPC) is essential to handle complex, and a large volume of data arising from clinical trials, and needs to be a robust, reliable, and scalable infrastructure. Leveraging the Cloud enables pharma, medical device, and CROs with the critical need to handle digital clinical trial data to achieve surpassing performance, control, and governance while delivering scale, elasticity, and cost savings. Cloud technology is designed to secure, and protect sensitive patient and patient-derived sensitive data.
Even though everything might look rosy for Digital Clinical Trials due to the adoption of advanced technologies, the road ahead is not smooth. Key challenges are the practicality between the proposed technology and successful adoption for digital clinical trials. Challenges that need to be given due consideration, include;
Patient Data Privacy & Protection
GlobalData’s surveys conducted in 2019, and 2020 indicated that respondents attributed issues with digital privacy, and data security, to be the key concerns associated with digital transformation. Growth of the virtual clinical trials places increased importance on data security, privacy, compliance, and regulations. Assurance pertaining to safe, ethical, and effective data collection needs to be provided in leveraging wearable devices, and smartphone applications, along with obtaining consent, and data ownership. GCP guidelines provide the framework for data integrity, data protection, GAAMP5 validation for computer systems, and audit trails.
Recruitment and retention of patients
Patient recruitment, and retention is a critical challenge in clinical trials. The COVID-19 pandemic only added to these woes. Moreover, the introduction of technologies such as eDiaries, wearable and connected devices into Digital trials, has added another dimension of complexity. The quality of data generated through the use of these technologies, can also be impacted by the degree of computer literacy of the clinical trial participants, and the organizers. This calls for careful monitoring of the data collection, along with the placement of mitigation strategies. Then comes the aspects of the study's complexity, adequate feedback provided, and lack of granularity within the therapeutic areas, site visits, inadequate patient communities, and advocacy groups. All of the above factors, delays recruitment of patients, prolongs studies, and thereby hinder bringing the therapy to market on time and at cost.
Data integrity is a critical element in digital trials, and necessitates the use of regulatory approved systems, along with the necessary audit trials (such as electronic medical records, patient reports, and lab results). The broad spectrum of data can arise from EHRs, clinical records, demographics, patient-reported outcomes, nutrition, physical activities, digital biomarkers, connected devices, wearables, and more. All along the way standardization, verification, and validation using GAAMP5, GLP, GCP, CFR Part 11 compliance, IQ, OQ, PQ, e-Signatures to name a few are critical to ensure integrity. The lack of these standards would throw a wet blanket over the digital trial outcomes.
Healthcare data generated during clinical trials vary greatly from one clinical trial to another part due to the source of the data (patient care, lab results, clinical research, insurance, billing, etc.,) and partly due to different standards used to collect these data by service providers and sponsors. In addition to these data standardization issues, every clinical trial study deals with unstructured data (e.g. paper notes) and faces challenges in translation these unstructured records into a digital format. Data gathered from each patient needs to be uploaded, properly digitized and interpreted which might need the assistance of skilled curators. Artificial Intelligence can come to the aid during curation, but needs human oversight. FDA in collaboration with other standardization organizations such as CDISC and HL-7 guides the use of healthcare data during interventional or non-interventional clinical trials (Real World Evidence – RWD). These standards need to be constantly updated as we generate more and more healthcare data from each patient using technologies and platforms. Regulatory agencies necessitate the specification of assumptions, method validation, and assurance of data quality.
Patients, funders and sponsors, trial sites, CROs, pharma, medical device providers, research institutions and universities, patient advocacy groups, non-profit working groups, hospitals, and regulatory bodies, are many of the players that need to buy into the technological advancements, guidelines, and recommendations that influence the clinical trials. The US Clinical Trial Transformation Initiative (CTTI) published recommendations on the use of mobile technologies, and apps for data collection in clinical trials in 2018. Lack of synchronization and coordination among these myriads of stakeholders would lead to challenges pertaining to the adoption of digital technologies in clinical trials that would negatively impact participant identification, recruitment, retention, attainment of consent, consistent data collection, and adequate follow-up. Moreover, inadequate representation from ethnicities, elderly patients, and geographies could lead to under-representation in the trial and skewing the clinical trial outcomes. The last fact is the lack of real-life settings.
Global, national, and state-level regulatory agencies promulgate laws that have a big say in influencing access to clinical trials, patient enrollment, diversity, retention, and trial outcomes. But the lack of clear guidance for virtual clinical trials is an impediment. This in turn impacts the measure of digital outcomes, data, and the total guarantee of patient safety. For example, in regards to the use of telemedicine in virtual clinical trials, state-level regulations need to be taken into consideration when subjects have to cross stateliness. State regulations focusing on patient privacy may overlap with HIPAA to create an additional layer regarding the complexity of regulations. The 21st Century Cures Act in the US added value to FDAs support for Digital Health and digital clinical trials. But in EU the specific guidance is a bit less. The addition of the General Data Protection Regulation (GDPR) in EU and China’s New Personal Information Protection Law (PIPL) has added another level of complexity. Many countries outside the US tend to follow the EU guidance. Moreover, COVID 19 pandemic introduced another layer of complexity in regards to regulatory approval EUA – Emergency Use Authorization.
As digital clinical trials evolve, the future looks bright with advancements in digital technologies to capitalize on the data generated to derive a meaningful insight, and with rapid adoption by various stakeholders. We see that not only the decentralized clinical trials are on the rise but the virtual clinical trials are also gaining momentum. Virtual humans is one such outlook that provides the flexibility to conduct infinite trials for medical devices before implanting them in vivo. This has value for heart valves, pacemakers, stents and for imaging modalities – X-rays, MRIs, and CT Scans, with the ability to create 3D models with the virtual representation of the human body. The effectiveness of the devices can be accelerated by running simulations on a HPC cluster residing in a cloud infrastructure (example Oracle Gen 2 Cloud). As data grows rapidly, there will be a need for higher compute power that can accelerate data analysis by multiple magnitudes. Quantum computing machines could be of value for advanced clinical research. Virtual Reality (VR) is another outlook that has been employed in pain management clinical trials. This involves a self-administered in-home VR therapy program with software to manage patient recruitment, eConsent, participant engagement, and collecting patient-reported outcomes. This program supports clinical workflows, including randomized schemas, research communication, principal investigator oversight, coordination of VR headsets, and trial kit distribution.
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