Joan Chambers

	Technology adoption in health care delivery has already surpassed anything we’ve done in the drug development industry. In health care, mobile technology and mobile engagement allow patients to interact with their caregivers, health care delivery, and pharmacists. In the drug development industry, however, we have not kept pace with how people use mobile phones, smartphones, and iPads to engage with their daily lives.
	
	In the millennial generation, roughly 30 to 40 percent do not have a primary care physician. Instead, these millennials access their health care delivery through ambulatory clinics or engage with health care providers via mobile devices. Even people in their 60s or 70s often use mobile technology for health care delivery needs such as chronic disease management and medication alerts. Beyond health care, the daily routines of individuals across all age groups include the use of technology.

	Building upon the usage of technology in health care delivery, integrating technology into clinical research as a care option will be a game changer in achieving greater participation in clinical research and decreasing the overall time for trial completion.
	
	

	Between 2013 and 2017, Alphabet, Apple, and Microsoft collectively applied for more than 300 U.S. health care patents, signaling an increased technology presence in the health care space.

 In an effort to tackle the status quo, Amazon, Berkshire Hathaway, and JPMorgan Chase are collaborating to simplify health care and drastically reduce costs.
	
	These tech giants have also influenced the health care landscape among payers and providers. In a proposed $69 billion deal, one of the largest in U.S. health care, drugstore chain CVS is acquiring Aetna, the largest health insurer. Other deals have recently been announced, such as Cigna’s acquisition of Express Scripts and Albertsons’ acquisition of Rite Aid. These consolidations can reshape health care relationships and capabilities, profoundly affecting patient participation and experiences. Even Lyft and Uber have entered the health care space, leveraging their ride-hailing services for patient transportation and prescription pickup.

	Once the big tech players get into this space and own that relationship with the patient as a consumer, it will be difficult for pharma and biotech to come back. Patients will be less inclined to participate in trials because the barriers to participate take them so far out of their normal routine for their health care delivery.

	The biotech and pharma companies have an opportunity right now to own that patient engagement, either through mobile technology or technology engagement such as Bluetooth and wearables. The people who know drug development best and understand the intricacies of bringing drugs to market are still the health care and science professionals within the CRO space, pharma, and biotech. All that depth and understanding are necessary to be able to apply the technologies appropriately to gain the most efficiency and opportunity, compress trial timelines, develop greater patient engagement, minimize the barrier to entry, collect more data in real time, and ensure patient safety. Technology by itself won’t solve all the problems. The industry needs that skill set and knowledge base.

	“Virtual trials” can be a misnomer. They are not replacing every physician visit with technology or a virtual visit. Rather, enough data exists to understand the total patient journey, in terms of how patients are being treated for their disease in the real world, how we use that data and our understanding of the patients’ pathway to treatment, and how to optimize the clinical protocol. The value here is on minimizing the patient burden to participate in research.

	If there are 10 or 12 visits in an average clinical trial, then through wearable devices, Bluetooth technology and mobile platforms, potentially half of those visits could be conducted in a virtual model, with the data pushed directly to the provider. The use of virtual visits can enhance safety while reducing the burden on both patients and trial sites. Thus, more real-time data reaches the physician in a more effective and efficient manner. Patients can more easily participate in trials, as they do not need to go to the clinic and step out of their daily routines on multiple occasions. Rather than entirely replacing that connection between the physician and the patient, we’re augmenting it so that no one makes visits for what can be done and collected in a virtual environment. The trial is still safe, effective, and well managed.

	There may even be trials in a 100 percent virtual environment, either through telepresence visits with Teladoc or virtual visits via smartphone, with the incorporation of Bluetooth-enabled devices. If we can collect vital statistics from a patient via their own device, hundreds of medical-grade devices approved by the FDA can push the data directly into a mobile platform that can then be shared with a health care provider.
	
	The drug development industry is starting to move forward. Several companies have already indicated that their goal is to move to an almost entirely virtual clinical trial model. Pfizer was on the forefront of that almost a decade ago. Now, Novartis is partnering with Science 37 for 10 virtual trials over the next three years, to move forward with a more virtual, “site-less” model. Virtual participation can improve the diversity of trial participation and, therefore, broaden the collection of real-world evidence in clinical research. Once these companies demonstrate the benefits, the dominoes will fall quickly for the rest of the industry.

Meeting stakeholder needs in clinical research

	The reality is that patients have choices whether to participate in research. There may be five, six or seven drugs currently in clinical trials for some indications, particularly for chronic diseases, so patients also have an option as to which trial to participate in. One of the biggest challenges is recognizing that patients who participate in trials are actually consumers first.

	If you look at the 21st Century Cures Act and similar regulations, government agencies are encouraging pharmaceutical and biotech companies to leverage these technologies to enhance the ability for patients to participate in trials. We still must ensure that the data we collect is robust, auditable and clean, and that it tells the appropriate story to regulators that justifies or supports the mechanism of action of the drug and the impact on the disease state.
	
	Technology is not going to solve everything. However, with a new molecular entity currently averaging more than $2 billion and 10-plus years,

 we need some sustainable solutions. By leveraging technology to make clinical trial participation less burdensome for all stakeholders-including patients, physicians, sites, and caregivers-we can decrease overall timelines and costs, getting new therapies to market faster.

, Executive Vice President and Chief Scientific Officer, PRA Health Sciences, and member of the Advisory Committee of the 

Bridging Clinical Research & Clinical Health Care Collaborative

, Senior Copywriter, both with SCORR Marketing and the 


	1. When the Human Body Is the Biggest Data Platform, Who Will Capture Value? 

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	2. Tufts CSDD Assessment of Cost to Develop and Win Marketing Approval for a New Drug Now Published. 

http://csdd.tufts.edu/news/complete_story/tufts_csdd_rd_cost_study_now_published

Articles

Building upon the usage of technology in health care delivery, integrating technology into clinical research as a care option will be a game changer in achieving greater participation in clinical research and decreasing the overall time for trial completion.

Leveraging Technology to Bridge Clinical Trial Processes and Real-World Health Care

	According to the National Academy of Medicine, a Learning Health System is one in which science, informatics, and care culture are aligned to generate new knowledge as an ongoing natural byproduct of the care experience. The system seamlessly refines and delivers best practices for continuous improvement in health and health care.

	Simply put, a Learning Health System represents a cultural commitment to learn and improve as a result of every single experience of every participant, so that our health system gets better and decisions get better. It moves us to a paradigm in which every decision affecting health is informed by actionable knowledge of what works best.

	As such, Learning Health Systems involve multiple cycles of continuous learning. These cycles involve:

	1. Taking what happens in the doctor’s office and outside health experience and turning that into data so we can learn from it (performance to data/P2D).

	2. Transforming the data into knowledge (D2K) through analytics.

	3. Mobilizing knowledge in tailored and actionable forms to inform decisions and be implemented into actions in a timely manner (knowledge to performance/K2P).

	Patients, in collaboration with their clinicians, can make important health decisions not just based on a couple of clinical trials or their physician’s experience with a few patients, but based on the experience of every other patient like them and what worked and what did not.

	Despite the huge investment in clinical research, patients, caregivers, and clinicians often feel they do not have the information they need. To take one example of an effort to address these challenges, the Patient-Centered Outcomes Research Institute (PCORI) funds comparative clinical effectiveness research that gives patients and caregivers the ability to make better-informed health decisions, with a focus on sharing results with the public.

	PCORI funds the development of both clinical data research networks (CDRNs) and patient-powered research networks (PPRNs). CDRNs perform data sharing and patient-centered clinical research, coordinating capabilities across organizations and other CDRNs. The University of Michigan Medical School is part of one CDRN, the Patient-Centered Network of Learning Health Systems (LHSNet). The institutions that are part of LHSNet have built relationships with patients and communities, academic medical centers, universities, health care centers and payers. LHSNet generates patient-centered knowledge and disseminates it widely to continuously optimize care for the 10 million people served by the network. This data sharing is also leveraged to focus on longitudinal study of certain diseases.

	PPRNs are driven by collaboration among patients, registries, nonprofits, and patient advocacy organizations, often around a single disease such as vasculitis or COPD. The networks aim to transform clinical research by directly engaging patients who have particular diseases, as well as investigators, care providers, and health systems, to conduct patient-centered research. Often, patients consent to share their health information and can be directly involved in research design.

	There are numerous other examples, including the Million Veteran Program and the All of Us Research Program, that focus on recruiting people who want to share their experiences to improve the future of health care.

	At its core, patient empowerment is about putting power in the hands of patients, who are the ones who ultimately have the most skin in the game, to improve their health and the health of a loved one and the health of the others in the system as a whole.

	For patients, there is this amazing enthusiasm, desire and also frustration of not being treated with respect, of using “patient” as a third-person word without the recognition that every single one of us will be or has been a patient or caregiver.

	Many patients have a strong desire to get access to their data and to the literacy to understand-and to be able to do great things with it to improve their own health and the health of others. The fact is, their data is their life experience, and that can be painful. Their experience comes from having lived through it, which makes them an expert on what they’ve been through. Patients want to feel valued for their expertise and experience and also respected for what they’ve been through.

Advancing clinical research through Learning Health Systems

	Not only can Learning Health Systems advance clinical research, but they also work to get that research into practice. The approach can dramatically improve how we learn from real experiences. If only 3 percent of patients are participating in clinical trials, even that participation is taking a fraction of patients’ experience. Imagine if we were learning from nearly 100 percent of patients who want to be a part of this, how much more quickly we could learn lessons and apply them.

	Learning Health Systems are about linking real people’s health care experiences and their overall experiences that stretch beyond health care. The system is about empowering research and learning from each piece of it, and then translating what’s learned from the researchers beyond journals and papers into practice and into people’s lives-where it can improve health and save lives, millions or billions at a time.

, Program Officer for Learning Health System Initiatives at the University of Michigan Medical School Department of Learning Health Sciences and member of the Advisory Committee of the 

, Senior Copywriter, both with SCORR Marketing and 

The use of Learning Health Systems in order to advance clinical research.

Applying Learning Health Systems to Advance Clinical Research and Health Care

	Though the comprehensiveness of electronic health records varies globally, EHRs contain a wealth of longitudinal real-world data-including demographics, clinical data, pharmacy and billing claims, and other patient information-to create a multifaceted picture of health, care-seeking behaviors and pharmaceutical consumption across broad populations. By leveraging EHR data, the industry can transform how it conducts clinical research and delivers health care in the future.

Identify qualified patients for clinical research

	Prescreening individuals according to specific demographic and medical data can expedite the patient recruitment process in clinical trials. 

, President of Advarra, articulates EHR’s wide-ranging potential: “The ability to mine information in EHRs will allow us to identify potential patients, expose them to the opportunity of participating in research, and then connect them with physicians they may be familiar with, including their own physician.” EHRs can help identify, reach, and serve a broader patient population, to benefit the patient and further research.
	
	

	Changing the current mindset to advance health care requires a bridge from EHR data into clinical trials, according to 

, solution executive at IBM Watson Health. Without the integration of data from electronic records, he says, the disparate data will not be as robust and complete. For example, in a clinical trial, patients may inadvertently fail to report information such as an adverse event. By unlocking pharmacy and claims data as well as other information from electronic records, however, clinical researchers can help ensure patient safety and identify whether treatments result in improved health outcomes.
	
	

Overcoming Challenges to Using EHR Prospectively for Clinical Research Studies

, Scientific Innovation Officer at Elligo Health Research, discusses how the use of EHRs resulted in significantly faster drug-related adverse event reporting-from 35 minutes to less than one minute. In addition, using EHRs to auto-populate electronic case report forms, as opposed to manual data entry, resulted in time savings of 37 percent for data capture. The potential for EHR to improve efficiencies in clinical trial conduct is vast, and these recent studies have made strides in quantifying the ROI. 

	The data in electronic health records overlaps with the types of data collected for clinical research. This provides opportunities for data sharing and reuse without reentry or transcription, thus supporting open science and learning health systems. Building better bridges between research and health care offers limitless possibilities for facilitating research and improving health care delivery.
	
	

, founder and CEO of monARC Bionetworks, speaks to the possibilities: “The sheer tsunami of health care data available from medical records and the growing use of mobile and digital sensor technologies to collect health data, combined with rising online patient engagement in health care and research, present an unprecedented opportunity to modernize clinical trials through greater collaboration with patients and their clinical care systems.”

	To unlock, access, and leverage the multitude of data from EHRs requires harmonization of data standards and data models. TransCelerate’s Clinical Data Standards Initiative, in collaboration with the standards development organization, CDISC, as well as C-Path, NCI-EVS and FDA as part of CFAST, aims to develop industrywide data standards to support the exchange and submission of clinical research data. The implementation of these standards will enable data aggregation, cross-study analysis and end-to-end data flow, as well as facilitate analysis from multiple disparate data sources. Consistent data collection in clinical trials will ultimately lead to more efficient research with higher-quality data.
	
	Regulatory guidance on using EHR and applying artificial intelligence to enhance patient recruitment are also key issues to explore to advance the state of clinical research. Through collaboration between multiple stakeholders-including pharma, biotech, CROs, health care organizations, advocacy groups, and regulatory agencies-we can ultimately develop solutions to the industry’s most critical questions.

By leveraging EHR data, the industry can transform how it conducts clinical research and delivers health care in the future.

Joan Chambers

Articles

Leveraging Technology to Bridge Clinical Trial Processes and Real-World Health Care

Applying Learning Health Systems to Advance Clinical Research and Health Care

How EHRs Facilitate Clinical Research