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Today, only 5% of the US population participates in clinical research. With the rise of new software tools that make research faster, cheaper, and more accessible and with a forward-looking FDA digital health team, the time is ripe for a clinical trial paradigm shift.
Healthcare companies that support clinical trials have been famously slow to adopt technological innovations. Many research sites still use physical protocol binders, paper diaries and decade-old software.
That tide is starting to turn as more companies across the clinical trial value-chain incorporate software into their product offering. A recent study found that听, and 97% plan to use these tools in the next 5 years.
The goal of this post is (1) to highlight听new software tools听that support clinical research across the value chain, and (2) provide perspective for two emerging innovations:听virtual trials听and the rise of听digital biomarkers.
Virtual or 鈥渟iteless鈥� trials are conducted outside of the site or clinic鈥娾�斺�奱nd in the participant鈥檚 home. Digital biomarkers, as听, are consumer-generated digital tools that collect behavioral and physiological data (e.g., clinically-validated wearables and sensors).
Sponsors conducting virtual trials often reference four benefits:
(1)听Cost. Virtual trials can听.
(2)听Recruitment. They can increase听recruitment rates and diversity听by making it more convenient to participate in trials.
(3)听Data. Using digital tools (e.g., digital surveys and sensors), a Sponsor has many more touch-points with the participant during the trial. For example, if a participant comes into a site a few times a month, the Sponsor can collect ~50 hours of data on the participant. However, if data can be collected passively at home, nearly 4000 hours of data can be collected鈥娾�斺�奱 75x increase. Furthermore, the data collected from a participant鈥檚 natural environment are more 鈥渞eal-world鈥� than site-collected data.
(4)听Clinical-applicability. As we all know, more data doesn鈥檛 always mean better data鈥娾�斺�妎r improved outcomes. Nevertheless, in the past few years new algorithms and approaches are assisting researchers to make sense of and use this data and apply the results clinically. For instance,听听补苍诲听听take thousands of heart-rate measurements at home and can predict abnormal heart conditions like atrial fibrillation with 97% accuracy.
Of course, with any new technology there are solvable challenges (e.g., data quality, ownership, security). With the rise of computing power, and the听FDA鈥檚 revised stance on digital tools, this software-enabled tide is rising. We are poised for a paradigm shift in clinical research.
Methodology
The clinical trial value chain is filled with alphabet soup鈥娾�斺��,,,eCOA,. Even seemingly benign phrases like 鈥減atient engagement鈥� have strong鈥娾�斺�奲ut varied鈥娾�斺�奱ssociations within segments of the industry (e.g., 鈥減atient engagement鈥� may mean 鈥渦ser experiences during trial administration鈥� or could describe a 鈥渂est practice when designing the study protocol鈥�).
To keep the landscape open to newcomers, we limited jargon and focused on product functionality. This approach was useful for other reasons, too: many companies are developing products and services that expand beyond an industry-standard acronym.
To keep the graphic simple, we put a company鈥檚 logo in it鈥檚 鈥減rimary鈥� product, recognizing that many companies (e.g., Medidata and others) offer products that span across categories.
The focus of this piece is听蝉辞蹿迟飞补谤别-濒别诲听companies supporting clinical research with human participants.听Therefore, we excluded multiple contract research organizations (CROs) because many provide services rather than software tools. With the focus on human trials, we also excluded cloud-based laboratories like听.
The data was collected using publicly available sources鈥娾�斺�奵ompany websites, Crunchbase, TheConferenceForum.org, and through interviews.
Of course, this landscape is a snapshot in time, and with the rapid innovations in technology, this map will constantly change.
Have an update? Leave your notes in the comments.
Software-Enabled Company听Overview
Protocol Design 补苍诲听Review
Protocol design and review is one of the most important stages of the clinical trial. Improved protocol design means less changes throughout the trial, lowering costs and helping good therapies come to market faster.
When a good drug or device fails its trial because of bad design, it is not only a huge economic loss, but also a social one: good trial design is important to maximize patient engagement and minimize drop-out rates.
Biopharma and device manufacturers are facing additional pressure to make trials more patient-centered and ensure that results that are produced during the trial can hold up after the therapy comes to market. Yale professor Dr. Joseph Ross and his colleagues reported that听1 in 3 FDA drug approvals have safety issues after coming to market. Good design can minimize these issues while getting more therapies to market faster.
While there are many great companies and contract research organizations (CROs) that specialize in protocol design and review鈥娾�斺�妋ost are consulting services and without software/data products. However, there are a few that are actively using new technology advancements.听Transparency Life Sciences 补苍诲听听are building platforms that crowdsource protocols for clinical trials.
has an online database to detect protocol violations and minimize duplicate enrollments in clinical trials.听听also has a real-time tool to analyze protocols.
听has launched digital health study templates for clinical research.听听has survey and feedback tools to collect data from participants to inform the study design process.
There are a few non-profits and consortiums supporting this category, too. The听听is a Public-Private Partnership that published guidelines earlier this year for the use of听mobile technology in clinical trials鈥娾�斺�妛ith a focus on novel endpoint design.
听calls for 鈥渁ll past and present clinical trials to be registered and their full methods and summary results reported鈥濃�娾�斺�奱 beneficial registry to counterbalance the bias of only reporting positive results. Negative results, while not as 鈥渋nteresting鈥� to publish, are results鈥娾�斺�奱nd can greatly affect future research so we don鈥檛 repeat past failures.
Site Selection 补苍诲听Start-Up
The two most popular online tools for site selection are听听owned by QuintilesIMS 补苍诲听听owned by WIRB.听听also has a tool to analyze protocols and find the right sites and patient populations.
Regarding site launch and training,听goBalto听is building anend-to-end study startup platform that speeds clinical trials through site selection, feasibility, and activation. The team is shifting the time to set up a site from months to weeks or days.听听is also building training and connection tools to speed up site launch.
听specializes in online investigator training which can 鈥渄eliver your training in as little as 5-business days. Less than a week to get training up and running.鈥澨�Covance鈥檚听Xcellerate Trial Design听product uses two proprietary data assets鈥娾�斺��(a) investigator performance data derived from 鈥淐ovance鈥檚 central laboratory operations that spans >45% of all clinical trials globally鈥� and (b) 鈥渄e-identified longitudinal diagnostic data from LabCorp which spans some 100M lives.鈥�
For site start up, there are also a number of eConsent companies which assist sites by digitizing the informed consent process.听Mytrus, one of the leading eConsent companies, was purchased by听Medidata听earlier this year. A number of other companies have eConsent products, including听DrugDev鈥檚听SecureConsent,听FIRECREST, 补苍诲听CRF Health.
Patient Recruitment
Patient recruitment could be a separate deep-dive with all the new software-led approaches. There are many different approaches to finding better ways to recruit patients; technology advances (e.g., natural language processing, AI, online training) is part of the solution, but not the silver bullet.
听raised $2M earlier this year to match cancer patients to clinical trials using an algorithm to understand unstructured natural language within听and matching it with a patient鈥檚 medical record.
听is also applying artificial intelligence and natural language processing to medical records to find patients.
听has developed a software platform to streamline the process of participating in clinical trials.
听is a stealth-mode technology company that鈥檚 building a treatment access platform for cancer patients.
听is a patient network that also operates a real-time research platform. Other technology-led patient recruitment platforms include听,听 ,听 ,听 ,听,听,听 ,听,听 Langland,听,听 Comprehend Clinical,听补苍诲听 .
Some ventures are working on connecting with participants after the clinical trial wraps up.听听is building a patient community beyond the clinical trial.
Trial Administration
Once the site is set up and patients have been recruited and onboarded, the trial begins. This section was the most challenging one to group into categories because many pieces of software can span across functions.
Operational Data Management
This category handles the site-level and operational information (e.g., clinical trial management systems, site monitoring, risk-based monitoring, and payment automation). Many companies offer products that have multiple features. We鈥檒l share a few highlights.
Clinical trial management systems (CTMS) have been in the industry for a long time. A few of the classics are听Oracle鈥檚 Siebel听CTMS Cloud Service,听Parexel鈥檚听Perceptive MyTrials,听叠颈辞肠濒颈苍颈肠补鈥檚, 补苍诲听Medidata听CTMS.
Some start-ups are taking a new approach to operations management. Founded in 2014,听听recently raised $1.7M to move clinical research off paper and into the cloud. Also founded in 2014,听听is building a clinical trial management platform that focuses on investigator site engagement and protocol compliance. Launched in 2015,听听is building a similar software system to replace paper-based data collection. Released in 2016, Trial by Fire Solution鈥檚听 platform is an 鈥渙n-demand鈥� Clinical Trial Management System (CTMS).
There are also a number of start-ups that are assisting in the operations around clinical research.听听is building a modular patient relationship management platform focused on people living with chronic diseases.听听is a risk-based monitoring (RBM) systems for clinical trial monitoring.听叠颈辞肠濒颈苍颈肠补鈥檚听ClinPay听补苍诲听听are automating clinical trial payments and budget forecasting.
Drug and Supply Logistics
Most companies that provide drugs and supplies to clinical trial sites don鈥檛 use a lot of technology; however, there are a few exceptions.
听is a start-up that integrates with electronic data capture systems and uses clinical trial data to inform automated logistics workflows. They also supply kits that can be customized by site, patient, or study timepoint.
If a Sponsor is collecting information using mobile or connected technologies鈥娾�斺�奾ow do those devices get to the participant?听听supplies sites with a number of connected devices including Apple iPad/iPhone products. Multiple eCOA and ePRO vendors, like听CRF Health, will also supply sites with smart devices. Some of the digital biomarker companies, like听, will also handle their own sensor logistics. This category is still in early days, but it will grow as virtual trials and digital endpoints take off.
Continuing with the clinical trials alphabet soup听, there are a number of companies that support clinical trial randomization and the associated drug supply management process. As an听, many acronyms are often associated with these processes: Randomization and Trial Supply Management (RTSM), Interactive Voice Response (IVR), Interactive Web Response (IWR), Interactive Mobile Response (IMR), Interactive x Response (IxR), or even Interactive Response Technology (IRT).
Acronyms aside, there are a few companies doing some interesting work with software to modernize these activities. Launched in 2015,听听built a platform using natural language processing (NLP) among other tools to reduce the time it takes to get a drug to a participant. Launched in 2010,听Endpoint Clinical听features a system that has real-time reports and is configurable to a study鈥檚 supply chain. Launched in 2007,听听has a platform that works across multiple smart devices and integrates with multiple third parties (e.g., other data capture systems and outcome platforms).听ICON,听Almac,听Bracket, 补苍诲听Medidata听also have solutions for randomization and trial supply management.
Patient-Level Integration
This category was also a challenge鈥娾�斺�妕here aren鈥檛 clean lines around patient engagement and collecting/storing/analyzing patient information. We split it out into two categories to better highlight the rise in digital biomarkers.
Patient and Outcome Data Management
This category includes electronic data capture (EDC) systems and other platforms that will store patient-level data. It also includes digital tools that collect eCOAs (Electronic Clinical Outcomes Assessment) and ePROs (electronic Patient Reported Outcome)/PROM (Patient Reported Outcome Measures) data. Many companies have created products that span across the patient and outcomes data layer.
There are a number of big EDCs that have been in the industry for a long time:听, Oracle,听, 补苍诲听eClinicalSolutions. Some companies, like听, have been modernizing the tools for SaaS in global life sciences, expanding out its cloud-based platform.
Aside from the big players, there has been a rise in software tools to capture patient outcomes.听CRF Health听is one of the leaders in eCOA and ePRO assessments.听听is one of the leading providers of eCOA, rater training, and trial supply management solutions for biopharma sponsors鈥娾�斺�妛ith a focus on CNS therapies.听 is also building an eCOA platforms.听听is building a 鈥渘ext-generation鈥� patient data capture platform with many tools designed for clinical research. The International Consortium for Health Outcomes Measurement (ICHOM) has published a number of companies that have web and mobile-based reporting systems for outcome measurements on the听ICHOM TechHub.
Outcomes are also influenced by med adherence technologies, and there are a number of new tools that are designed to improve adherence.听听is an advanced medication adherence solution powered by artificial intelligence, which visually confirms medication ingestion on any smartphone. Dan Gebremedhin and Kara Werner from Flare Capital recently conducted听. These types of technologies are in many ways more similar to digital biomarkers than to the big patient data capture databases.
Digital Biomarker Collection
As听, digital biomarkers are consumer-generated digital tools that collect behavioral and physiological data. These tools can be used to diagnose and/or treat patients remotely.
This list is far from exhaustive, and there is a lot of innovation that is happening in digital biomarkers that we鈥檒l share in future posts. For now, a simple way to think about this category is (a) the听sensors and tools that collect the data听and (b) the听systems that integrate that data.
听There are hundreds of teams working on developing digital biomarkers. A few of the most prominent are:
Google鈥檚听听has recently launched听, a collaboration of Duke University and Stanford University that will enroll 10,000 healthy people for the study. The study will likely use survey data along with sensor data from the听, a sensor-packed smartwatch Verily launched in April.
Actigraph听is one of the oldest companies in the digital biomarker industry. Founded 15 years ago, Actigraph provides medical-grade wearable activity and sleep monitoring solutions for the global research community. Another company developing digital biomarkers is听, which has developed a FDA-cleared single-lead EKG for $99.听听is a remote care service provider that has created customized 鈥渒its鈥� that include 4g tablets with wireless vitals monitors.
There are companies that are developing platforms to integrate the sensor data.听听is a technology platform that provides 鈥渁ccess to a world of mobile health and in-home devices, fitness equipment, clinical sensors, activity wearables, smart bands and wellness applications.鈥澨齣s similarly building a 鈥渞eal-time health data network, powering more than 10,000 applications in 40 countries.鈥� Apple has been heavily investing in 听over the past two years, developing customized apps and products for a range of conditions.听听is a 鈥渘on-exclusive, open, and interoperable鈥� platform that has partnered with over 鈥�400 collaborators including medical device manufacturers, health service providers, app developers, and more.鈥�
On the evaluation front,听听is building a solution to help companies quantify their digital outcomes, focusing on research with connected devices.
The FDA has recently made a number of forward-thinking changes that will speed up the development of digital biomarkers. The FDA鈥檚 Center for Devices and Radiological Health has spun out a听to look at more at these digital tools. Last summer, the FDA released new guidelines for听听and this past summer, it has released a听鈥淧reCert鈥� program听which will certify companies rather than products, allowing developers to continue to iterate on the software after FDA clearance.
CTTI, recognizing the advances鈥娾�斺�奱s mentioned earlier鈥娾�斺�妑eleased a set of听guidelines for how to use these mobile technologies to develop novel endpoints. These advances, along with the increased R&D in the sensors, are priming the industry for many new tools鈥娾�斺�奱 paradigm shift for research.
Remote-Virtual Trials
One of the biggest shifts that鈥檚 happening in clinical research is the rise of virtual or 鈥渟iteless鈥� trials. These trials hold the promise of being cheaper, accessing a wider population and more opportunities to capture real-world data from participants.
Biopharma and device Sponsors are under pressure to reduce costs, improve patient engagement, and simplify the trial administration process. With this shift, many Sponsors have reduced their partnerships with contract research organizations (CROs)鈥娾�斺�奵utting down on the number of CROs used in a trial, taking the CRO responsibilities in-house, and/or work with virtual trial providers.
听is one of the most unique companies in this category. First off, they are a听non-profit听research organization, which 鈥渟eeks to develop predictors of disease and accelerate health research through the creation of open systems, incentives, and standards.鈥� Sage is the mastermind behind Apple鈥檚 ResearchKit, and they鈥檝e put out a number of virtual trial apps including听, for Parkinson鈥檚 disease.
Going 鈥渇ully-virtual鈥� can be an operational challenge for biopharma. For example, if the protocol requires a participant to get regular chemo, having the infusions at home could be a risk (e.g., patient has anaphylactic shock and no medical support to treat it). As a result, many biopharma companies are taking a听鈥渄irect-to-patient鈥� approach听when possible and may have some parts of the trial remain in a clinic while shifting more touch points to the home (e.g., more virtual).
There are a few business models that are starting to emerge. First are companies that are building a听鈥淧latform-as-a-Service.鈥澨�,听launched in 2013, is building a leading cloud-platform product that is designed for siteless trials and has a number of tools ready to deploy direct to patient. This model is a technology play, building products that are highly configurable and deployed across iOS, Android, and the web.听Parallel6, which was recently acquired by PRA Health, is also building a software-based platform that Sponsors then license for their trials.听听is building a cloud-based digital patient recruitment and engagement platform, currently focusing on 鈥渟iteless鈥� trials.
Aces Health, launched last year, is one of the more recent players in the end-to-end remote clinical trials management systems, featuring a platform 鈥渁utomatically collecting data on demand from over 15,000 eHealth sources.鈥澨�, a startup still in stealth mode, started as a dev shop with extensive clinical trial experience. Public information on this venture is limited, but on their site they claim to build customized apps that enable biopharma, CROs, and researchers to conduct remote patient research. Perhaps this may lead to a platform one day, too.听听is the newest venture, launched in October last year. The team is building a 鈥淒igital Research Platform鈥� for remote patient trials.
, perhaps the best known virtual trial venture, has raised $67M in the past two years to support siteless trials. In contrast to the pure-platform technologies plays, Science 37 is more similar to a 鈥渄igital CRO鈥�, although the company does not use the term 鈥淐RO鈥� in public materials鈥娾�斺�奺mphasizing its technology roots.
Science 37 is taking a more full-service model than the 鈥淧latform as a Service鈥� companies and hiring over a hundred employees (), many of whom are supporting the remote trial operations. Science 37 offers recruitment and other full value-chain services. In contrast, the pure tech 鈥淧latform as a Service鈥� plays have smaller teams (Medable is听) and don鈥檛 hire coordinators or nurses.
QuintilesIMS听launched a听听group that is doing many interesting things at the intersection of software and digital tools. For instance, the team launched a 鈥減ragmatic trial鈥� which collected remote data from patients. This听. Nice savings, while collecting more real-world data.
, which serves Merck, Biogen, Janssen, Sanofi Genzyme, UT, and TEVA, has completed three virtual studies where they鈥檝e directly recruited patients into their portal and followed the participants for one year in a completely autonomous and automated manner. Their electronic portal incorporates web, mobile, and wireless device applications.
, backed by GE Ventures, was first listed in a digital biomarker section because it has a different approach. Gleamed from publicly available documents, rather than focusing on 鈥渢raditional鈥� clinical trials like Science 37, Evidation Health seeks to partner with start-ups and digital device companies to design and execute research to validate digital products. The company鈥檚 vision is to 鈥渜uantify outcomes in the digital era, using real life data from connected patients.鈥�
Last but not least, we also included e-consent platform听Mytrus, which was听purchased by Medidata earlier this year. Myrus is one of the old-guard in this category, assisting听.
With the rise of improved software tools and sensors, it is becoming easier for Sponsors to launch remote, virtual research. Clinical trials are poised for a paradigm shift as software scales research faster than ever.
What鈥檚 next?
There are hundreds of teams working on algorithms and sensors to collect clinically-useful digital biomarkers. We鈥檙e working on a separate post to highlight these. Stay tuned.
Source Data
Want to dig into more detail? Check out our听听for more information at a company-level.
Thanks to听,听,听,听, Richard D, and many others for contributing to this piece.