Data. Data. Data. Pharma and CROs have more clinical study data at their fingertips than ever before, but many feel they are not yet using it in the best way. Which technologies and strategies are most effective for generating reliable data? What benefits is this actually driving? What challenges still need to be overcome? In a new series, we explore these questions with some of the experts working to answer them every day.
Here a range of ten clinical professionals from pharma, CROs and technology providers explore the most effective new technologies and innovative strategies being used to collect clinical data, and the benefits these are offering for both those running the trial and the patient.
Yvonne Chan, MD, PHD, FACEP, Director, Center for Digital Health, Associate Professor, Genetics and Genomic Sciences & Associate Professor, Emergency Medicine at Icahn School of Medicine at Mount Sinai
New technologies: 'At the Mount Sinai Center for Digital Health (CDH), we believe mobile technology as well as connected devices could enable valuable multi-dimensional, granular, real-world clinical data capture. In 2015, the CDH team led the pioneering application of Apple’s ResearchKit framework to enable a large scale prospective observational study of asthma, with over 10,000 research participants from 3 countries. The study helped demonstrate the power and utility of citizen science and that smartphones could the ubiquitous tool that brings clinical research to the masses.
We found that mobile platform may increase participant diversity by facilitating the inclusion of traditionally underrepresented and difficult to recruit populations, (e.g., those with disabling, severe disease, living outside academic center catchment areas, etc.) by removing some barriers that has historically crippled study enrollment and ongoing participation. Beyond the unprecedented scaling of recruitment (i.e. over 3 thousand participants enrolled in 3 days post study launch), the breadth and depth of data collected, such as surveys, devices, geolocation, air quality were also remarkable.'
The benefits: 'Smartphone-based technology and digital health (DH) technologies in general, could provide innovative, scalable solutions for clinical research aspirations that were logistically not feasible or cost-prohibitive in the past. Researchers and stakeholders running trials could benefit from the automation and standardization of certain mundane, time-consuming aspects of the process, while still retaining ‘human touch’ at carefully selected key touch points of the study. This “human in the loop” strategy has been shown to improve study retention and decrease costs.
Additionally, mobile health technology can provide the participant continual, near real-time feedback on status/progress, push notifications, reminders, and other useful engagement features. This capability is one important advantage of smartphones because it provides researchers with a way to interact with participants more regularly and frequently than previously possible. This capability can be fine-tuned and leveraged to become a powerful tool in behavioral modification.
Furthermore, DH allows clinicians and researchers to obtain a more holistic view of an individual or a population’s health. The traditional trial methodology of examining isolated variables/relationships in a near vacuum frequently doesn’t yielded the most useful, generalizable results, given the extraordinary messiness and complexity of human diseases and behaviors. The concurrent development of sophisticated analytical methods, including machine learning/AI, can help us make sense of the “big data” generated by the DH/Internet of Things/genomics era. The goal is to identify and predict important signals or patterns associated with disease or wellness for each individual so that we can offer personalized prevention and treatment strategies.'
Bruce Hellman, CEO/Co-Founder, uMotif
New technologies: 'We believe that clinical research is going through its moment of rapid digitisation, fuelled by the ubiquitous smartphone. This is similar to what’s happened in the shopping, banking and travel industries - where digital is a core part of business strategy.
We are seeing that patients who are engaged with their condition and engaged with their research project capture more data. To this end, any technology that puts patients at the centre of this shift will be the most effective. Enabling patients to use their own smart device (Bring Your Own Device) and its built-in user interfaces, sensors, and connections to other devices will have the biggest impact for clinical data capture. Importantly, this is because this technology will be most effective in offering patients a benefit themselves with the potential to empowering patients to manage their condition.’
The benefits: 'Firstly, looking from a patient’s perspective, tracking one’s condition over time has been shown to improve adherence to medication, deepen a patient’s understanding of their condition and interestingly improve their perception of quality of their clinical consultations.
The benefits don’t end there, when considering the use of BYOD data-tracking to support clinical research it allows for patient’s to be part of clinical trials with very low friction. Patients are using their own device which they are accustomed to, rather than taking time to travel to a research site or having to learn new technologies – all making research participation simpler for patients. Patients get the benefits of tracking and managing their conditions in return for providing their data for research, and by supporting clinical research, they are helping future patients with similar conditions.
We at uMotif receive reviews from patients and trial participants for our application. Patients enjoy tracking their data and record how they are. The consensus is: ‘This is helpful to you and it is helpful to me’ (quote from Parkinson’s patient taking part in the 100 for Parkinson’s study).
A patient-centric approach delivers benefits for sponsors and CROs, with more engaged patients, less likely to drop out, and recording more data – all of which can drive faster and more cost-effective research.'
Sheila Antonio, Sr. Director, Data Management of Precision for Medicine
New technologies:'Obtaining clinical trial data has evolved from the days of collecting information on a handwritten paper Case Report Form and subsequently double data entering the CRF data into a clinical data management system. Companies are looking towards more innovative ways to collect data as close to the source as possible.
Technology has allowed us to move away from the paper trail into the age of Electronic Data Capture. Further innovations now give us the capability of integrating various sources of data into the clinical database. Data sources include electronic health/medical records and a limitless number of specialized external data vendors.'
The benefits: 'As we look towards the future, real time data collection from a patient-level physiological, biochemical and biometric level becomes increasingly requested. Device wearables, such as fitness trackers, and handheld devices, such as tablets and smartphones, collect this type of data. Imagine developing a product or software app to collect real time clinical trial data using Bluetooth or similar technology to upload this data into the cloud.
The benefits of this data capture method would include no data entry time, accurate data directly from the patient, patient convenience and real time data syncing into the clinical database. This can reduce the amount of administrative time for clinical researchers and time is money. However, this does come with its challenges. There is discussion about 21CFR Part 11 compliance issues, HIPAA, subject compliance, technical failure, technical support, device variability and a number of other unknowns.'
Nick van Terheyden, MD (aka Dr Nick - @drnic1), Founder & CEO Incremental Healthcare
New technologies: 'Capturing clinically valid and reproducible data from the broadest cross section of humanity as frequently as possible will continue to expand understanding and could allow for a new methodology in clinical trials that relegates the concepts of Randomized Controlled Studies to the curiosa pile of history. With all data collection we will continue to draw ever more fascinating conclusions from what we might currently consider mundane data. Separating correlations from causality will continue to be required and a major focus as we develop new techniques to understand relationships and more importantly visualize the data and present it to the right people at the appropriate time in a form they can comprehend and take action based on the data
Ultimately it is not about the new techniques and channels for collecting data, but rather will be about capturing all the data and normalizing and tagging it to make it accurately machine readable that will have the biggest impact on clinical trials. Some of the most innovative methods of data capture are unimagined right now but will seem so obvious to us as we look back at the historical methods that will in hindsight seem so primitive.'
The benefits: 'Moving away from the traditional Randomized Controlled Studies to the use of all the data all the time, will benefit everyone as we transition from guesswork implied in traditional data collection methods that sampled infrequently and inconsistently, to continuous data collection across a wide range of clinical variables.
We must speed up the process of discovery and scientific validation of insights as we enter a new age of understanding of the workings of our world and biology. Importantly no data should be relegated to the rust heap of irrelevance, but rather complete publishing and democratization of access since we do not know were or by whom the insights will be developed. New insights, theories and models will be developed at an exponential pace sometimes even disproving established widely held scientific understanding and requiring rapid changes in treatment practices and protocols.
Rapid incremental improvements applied quickly and with rigorous scientific validation will be applied for the benefit of the patient who seeks the best and most effective possible care. But also for the scientists, clinical trial teams and clinicians who are all seeking the fastest and most economical path to the truth and understanding of disease as they race towards their desire to deliver the best care to patients.'
Sarah Iqbal, Head of Digital Life Sciences, Biotaware
New technologies: 'Depending on the clinical study design and protocol, there are various ways to collect clinical data in this digital age. Data such as patient questionnaires, eDiaries, case report forms, physiological data and digital biomarkers can be collected digitally using smart phones, tablets, wearable technology, medical grade devices and sensors. In addition, by using point-of-care testing devices, algorithms and cloud computing, innovative digital health solutions enable clinicians to perform tests in near-patient settings and receive answers in real-time.
Collecting data with these innovative technology is the way to move forward in clinical trials but is not necessarily the issue. Most, if not all of these technologies can collect data effectively if used correctly. Collecting data effectively depends on the choice of outcome measured. This is because different data has different requirements and priorities. Hence, usage of the innovative technology mentioned above needs to be placed at the right point in the clinical protocol to enable the right data to be collected.’
The benefits: 'Convenience - Patients can input data remotely using mHealth technology from the comfort of their own home. Clinicians can use smartphones and tablets to keep tabs on the scientific literature, track their experiments remotely and stay in contact with laboratory members. Investigators can have online access to lab results, improve patient satisfaction and provide more timely access to clinical results.
Data security - A digital data capture system is usually hosted online with data entry completed on either a mobile or web-based interface. Given the nature of the data collected in a digital ecosystem, software vendors make sure the data is protected and backed up. Each user account (i.e. investigator, study staff or patient) has designated permissions, so most actions can only be carried out by certain roles.
Data consistency and accuracy - Capturing data digitally improves data quality. There are options to add constraints or perimeters on a form that prevent inaccurate or illogical values from being entered. Using a computerised or a digital health system enables legible entries and automatic calculations for cleaner and accurate data.
Quicker access and query to data - Capturing data using digital technology such as smartphones, tablets, wearables, biosensors and clinical grade mobile devices can save a significant amount of time with real-time access to data and less time spent on query management. This also saves time at the end of a study allowing quicker availability of the data for analysis. While it can take substantial time to initially learn how to use a specific system, some are so intuitive that only a few hours of training is sufficient.
Organised and efficient - The use of a digital health data capture system increases efficiency of clinical trials due to its user-friendly design and navigation. Search options allow you to easily find and filter exactly what you need, and store everything in one location with greater visibility.
Cost-effectiveness - The cost of a digital health end-to-end solution varies depending on the complexity of the study. Adopting an end-to-end digital health ecosystem can seem like a large investment, but it should save money in the long run.'
Michelle Petersen (@shelleypetersen), Founder, Healthinnovations
'When asked about the future innovations of data capture in clinical trials, the majority of experts will say concentrating on the qualitative as opposed to the quantitative is key here. There are lots of technologies moving forward with a view to data collection in clinical trials and it’s moving quickly; since my last featured post for this community (Aug 17), my conceptual non-contact lab tag monitoring system has become a reality with Cornell University developing a non-invasive method for gathering blood pressure, heart rate, and breath rate using a cheap system of radio-frequency signals and microchip tags.
Pharma is already investing in several big data, or quantitative-based, technologies such as eSource - which involves electronic informed consent and direct data entry into tablet computers - and remote patient monitoring involving wearable or home-based medical devices transmitting patient data securely to enable real-time data capture and analytics.'
Anna Matranga, PhD, MBA, CA-AM, AMC Alliances & Consulting
'There are many articles in the press on the current and future benefits of data collection using digital/mobile technology in clinical trials and beyond. They describe how technology will enable the provision of real world data (via direct access to patients) to facilitate the reimbursement of drugs with a “proven therapeutic value”, to promote faster drug development and to lower drug development costs for the pharma industry. These technologies will “engage” patients via the usage of apps on their personal mobile phone providing relevant information on studies, therapies and diseases as well as enabling data collection for the clinical and/or post-marketing surveillance studies (“internal & open source data”). These articles demonstrate the potential for easier access to patient data (on health signs, mobility, day-to-day activities as well as safety & efficacy data from CTs) in the drug development process.
As part of this technology wave or deluge, there is an important need to develop (and acquire from other industries) the competencies in data science, informatics, business intelligence and alternative statistical approaches to manage this technology. The new business model for drug development necessitates the management of the mountains of data being collected. Over recent years the entry of new CIOs into the pharma industry has been visible and is key in providing the strategy for the acquisition/development of this “big data” competency to “evolutionise” the pharma business model.'
Dennis Salotti, Vice President of Operations, The Avoca Group
New technologies: 'Direct data extraction from EHRs represent the greatest opportunity to drive efficiency and positively influence quality in clinical research. Today, there are existing solutions that mine EHR data to locate patients for targeted recruitment and direct referral to investigators (physicians running clinical trials). As standards mature in this space – and the healthcare ecosystem increases adoption and standardization of electronic health records – the accessible patient populations will grow, and this opportunity will become more valuable. Standards to move EHR data into clinical research database systems are already emerging such as BRIDG from CDISC.'
The benefits: 'Sponsors and CROs stand to recognize the obvious benefits of more rapid identification of eligible patients and potential reductions to recruitment timelines. With 80% of trials missing their recruitment timeline objectives, this stands to address one of the most persistent challenges in clinical research. There is also, however, an opportunity to drive higher quality into trial protocols through proactive evaluation of the protocol entry criteria by examining the results of querying the proposed entry criteria against EHR data sets. In this capacity, EHR data sets empower smarter designs and influence clinical development plans—an opportunity of far greater consequence to moving to a more proactive, patient-centric approach to clinical trials.
For patients, coupled with concurrent efforts to empower patients with greater autonomy over their data, EHR mining offers a mechanism to bring greater access to clinical trials and in a way that may spare them from additional procedures should they choose to screen and enter an active clinical trial.'
Julianne Hull, CEO, WenStar Enterprises
New technologies: 'I think there are two key areas. The first one is what is happening regarding ‘wearables’ for patients. How can these new handy devices to measure patient information be used in clinical trials? How accurate are these devices? Can we use them to compare data between anonymised patients OR are they only valuable within individual patients? This really comes down to the quality of the wearable. Are wearables validated to provide data sufficiently accurate for use in clinical trials? Will they motivate patients to sign up for clinical trials if they get a free wearable they can keep afterwards?
The second one is use of Electronic Health Records (EHRs). This has been discussed for years and many many investigational sites still have paper health records even in 2018. It is slowly increasing in the West, but there are still no agreed data formats. Effectively using the EHRs to capture all data from a clinical trial in the health record and to transfer to a sponsor in parallel does seem to be some time away.'
The benefits: 'With wearables patient motivation is key. The availability of key data - eg blood oxygen, blood pressure, ECGs - at all times of the day in real time throughout the trial is a dream that should be achieved in the next 5 years. With monitoring of blood pressure all the time rather than at key time points, will patients need to go to so many visits at sites and will this be further motivating for their participating in the trial?
For EHRs if a sponsor was able to have access to anonymised electronic health records they could analyse if a site really does have the type and calibre of patients for their specific clinical trial.'
Raphaela Schnurbus, PhD, Clinical Solutions Director, OPIS
New technologies: 'Patient-centric, data driven technologies that allow for better study control and oversight, and ensure accessible, secure analysable data with minimal migration and/or manipulation have almost become norm. Everybody is trying to find solutions for data sharing and data integration from increasingly diverse sources, BUT data standardization is going to be the key for future success. CDISC and now, the “Align CRO” initiative make this very clear. And with this in place, it is going to become a question of who has the most data and not who uses the best algorithm.’
The benefits: 'The two worlds of the patients and those running trials are growing closer and there is mutual benefit when patients have opportunities to make their voices heard in trial design, which can benefit from real world patient data. I have even heard of “randomized registry trials” to give just one example.’
Explore other posts from our clinical data series here.