Rick Morrison

	Even the most casual observer cannot help but notice the array of technological solutions bringing disruptive change to the clinical trials process. From a growing body of literature to webinars to multi-day conferences, the word is out that technology is key to a world focused on making measurable improvements such as speeding study start-up, streamlining transmission of clinical trial data, and overhauling how studies are monitored. And it’s no longer about individual point solutions to seemingly intractable problems, but rather, it’s about the sharing of real-time data they capture to enable strategic decisions by collaborators on the status of a study as it actually unfolds. This is a dramatic change from traditional paper-based methods that have been at the root of the industry’s slow and costly methods of conducting global clinical research whereby evaluation of data quality relied upon onsite monitoring or near database lock, sometimes years after the data were first collected. These older approaches have, in no small part, contributed to the ever growing timeframe for clinical development, which is an estimated 6.8 years, up from six years in the 1999 to 2001 timeframe, a 13% increase.

	This article offers a glimpse into some of the expansive solutions taking hold in today’s market and why the industry is finally ready for change. Only a decade ago, the clinical trials sector was embarking on implementing electronic data capture (EDC) on a large scale

, and since that time, there has been lots of lip service about additional technologies that are poised to make a difference. Some of them include cloud-based methodologies, namely the electronic trial master file (eTMF); electronic source documentation, commonly known as eSource; and risk-based monitoring (RBM). Further, data generated from these and other systems, such as EDC and clinical trial management systems, are aggregated, brought into the cloud, and supported by a virtual on-demand data warehouse. This approach will eventually benefit from standards that do not yet exist for aggregating data into a clinical data warehouse.  

	As described in a recent FDA webinar, the biopharmaceutical industry has been slow to uptake electronic solutions that could revolutionize clinical trials

, but some sponsors, contract research organizations (CROs), and investigative sites believe the industry is nearing a tipping point. As evidence, a recent study of the eClinical solutions market, including cloud-based solutions, projects a compound annual growth rate of 13.8% from 2014 to 2020, reaching an estimated $6.52 billion, up from the 2014 projection of $3 billion.

 It seems the industry is ready to embrace solutions that many see as drivers of change.

In 2012, the Institute of Medicine (IOM) released 

Envisioning a Transformed Clinical Trials Enterprise in the United States: Establishing an Agenda for 2020

a report summarizing a two-day workshop of 150 leaders of the clinical trials sector. Representatives of biomedical research, regulatory, pharmaceutical companies, academia, and other niches came together to discuss the growing recognition that the clinical trials enterprise faces intense challenges that impede the conduct of clinical research. According to the report, the situation has evolved to the point that the industry has limited ability to generate much needed evidence, so a complete transformation is in order (see sidebar). The IOM report discusses further that the need to build an infrastructure to support a transformed clinical trial enterprise should be a core theme. 

	And that’s where today’s technological advances fit in. The report takes a broad-based view of the overhaul, identifying a wide range of factors, including the need for improved data collection, management and analysis, data standards, and improved communication of results among stakeholders.  Today’s cloud-based technologies are designed to enable these sought-after improvements.

The advent of cloud-based capability could not come at a better time. It coincides with an all-out push from the FDA to adopt technology, as evidenced by the release of two guidances and one draft guidance on this subject (see sidebar). In August 2013, FDA released a guidance encouraging use of RBM where appropriate.

 This publication was quickly followed by the September 2013 guidance promoting use of eSource data.

 And in February 2014, the agency put forth a draft guidance providing for electronic regulatory submissions using standardized study data.

	Ed Seguine, CEO of Clinical Ink, a provider of eSource solutions, comments, “What’s unique about these three guidances in quick succession is their tone. They use terms such as ‘promote’ and ‘encourage.’ They are wanting to make it absolutely clear that FDA wants to see use of innovative solutions, so there is no regulatory excuse not to implement them.”   

	Before the string of FDA guidances, the European Medicines Agency (EMA) stated its position on the use of electronic collection of source data in a 2010 Reflection Paper

, which aligns with 12 user requirements of source data established by the Clinical Data Interchange Standards Consortium (CDISC). These requirements describe a group of high-level principles, which, according to the Reflection Paper, should be internationally applicable. 

	The EMA also released a Reflection Paper in 2013 on risk-based quality management

, a few months after the FDA guidance on RBM. Its purpose is to encourage and facilitate the development of a risk-based approach to quality management of clinical trials. The document discusses risk review as it relates to monitoring, and makes frequent reference to central monitoring, stating that electronic tools can support risk management efforts and decision-making. 

This drive toward electronic solutions coupled with regulatory encouragement is destined to impact stakeholders faced with managing growing pipeline activity. Research indicates a rise in the number of drug candidates in global development, namely 646 Phase III drugs in 2012, up from 573 in 2010 and 547 in 2008. Similarly, Phase II drugs exceeded 2,100 in 2012, up from 1,812 two years earlier, a 17% increase (see figure).

 Paralleling this trend is the massive increase in research and development spending, which according to the Pharmaceutical Research and Manufacturers of America (PhRMA), jumped to an estimated $51.1 billion in 2013 among its members, up from $34.5 billion in 2003

, an increase of 48% (not adjusted for inflation). 

	With this growing cadre of drugs under development, there is a need for cloud-based capability to streamline clinical trial activity. As explained by Jennifer Goldsmith, Vice President of Veeva Vault at Veeva Systems, a cloud-based provider of eTMF solutions, “Cloud-based technology has matured to a point where it can be used in a highly regulated industry. When we started, there were tremendous questions around maturity of the cloud and ability to integrate with in-house systems, but there has been a 180-degree turnaround. Those who would never consider a cloud environment a few years ago are now mandating it.”

	With the cloud gaining acceptance, so, too, are the technologies it supports, such as eTMF, eSource, RBM and next-generation clinical analytic interfaces built on virtual, on-demand data warehouses. A brief review of each of these technologies highlights why they are essential to supporting forward-moving clinical trials.

	The eTMF refers to the electronic version of the essential documentation needed to conduct a clinical trial and evaluate the quality of the data produced. Initially, when the TMF went electronic, it was generally maintained on an in-house client server, and functioned mostly as an electronic file cabinet whereby paper documents were scanned and archived, but were essentially static. Over time, this format has matured to a cloud-based solution housing massive amounts of interactive data that can be used for strategic planning of an ongoing trial. In particular, the eTMF offers greater visibility of data among stakeholders, documents are always audit ready, and there is functionality as a business planning tool, without having to maintain the IT infrastructure in-house.

	Recently, Veeva Systems released results of a large eTMF survey of 252 TMF owners.

  The survey collected data on the various types of eTMF systems used by the respondents, i.e., a local file share system (26%); a cloud file share (18%); a content management system (30%); or a full eTMF application (13%), which provides functionality specific to TMF documents and process-driven content management.  Results showed that the more advanced eTMF systems, namely content management systems and eTMF applications, delivered more benefits and higher TMF quality.

 The top drivers motivating eTMF adoption were cost savings (56%), speeding study start-up (55%), improving monitoring (49%), and increasing inspection readiness (45%).

	In interpreting these results, Goldsmith comments, “Requirements around the world for inspection readiness have become more stringent. Before, documents that were archived were acceptable. Today, we are seeing more in-process auditing and greater interest in remote auditing. There has also been a dramatic shift over the past 10 years in the amount of collaboration that goes on in a clinical trial. CROs, for example, are not only providers, they are actually strategic partners. For that reason, the ability to share the information housed in the eTMF among partners has become more important.” 

	Another solution, eSource, is gaining momentum, especially since the September 2013 release of the FDA guidance on the subject, which encourages its use.

 As stated in the guidance, eSource is defined as data initially recorded in electronic format. Data obtained at a study visit can be entered directly into an electronic case report form (eCRF), a process that has the advantage of reducing errors by eliminating the step of first writing on paper and then transcribing (see sidebar). 

	eSource addresses one of the major issues of EDC: the need to transcribe source documents into CRFs.  With eSource, clinical information flows directly into the study’s clinical trial database in real time or near real time, allowing for earlier visibility and a faster start to data analysis. Given this capability, one could argue that the CRF, a conduit for data collection, could actually be eliminated. Moreover, for the sponsor or CRO anxious to see clinical trial data, the issue of waiting several weeks for monitoring visits to review data captured by EDC is removed with eSource, and is replaced by real-time review of data, which is entered during a subject’s visit.

	Capabilities offered by eSource are a natural lead-in to RBM. The concept behind RBM is to focus sponsor oversight activities on preventing or mitigating risks to data quality and to processes critical to human subject protection and trial integrity.

 Traditionally, companies have conducted 100% source data verification (SDV) via on-site monitoring, a notoriously labor-intensive practice. But the need to continue this practice has been called into question, especially since it is not mandated by FDA or EMA.  Moreover, there is a growing awareness that 100% SDV does not automatically result in better clinical data quality.

	Between the regulatory encouragement for RBM and the robust volume of literature touting its value, RBM is a hot, if complex, topic. Much of the discussion focuses on the hefty costs associated with 100% SDV. Medidata puts the cost of onsite monitoring for a large clinical trial at 28.7% of the study budget, clearly the largest study expense.

 Project management costs are also substantial, at 26.47%, but other tasks as a percentage of the total budget, such as patient recruitment, data clean-up, data entry, and site close-out are in the single digits.     

	In moving to RBM, monitors can better spend their time reviewing critical study-related issues, protocol compliance, and patient safety. As described by Hunter Walker, Chief Technology Officer of Atlantic Research Group, “Despite the widely held belief that RBM is a money saving technique, it’s really about data quality. With RBM, monitors will still visit the sites, but instead of reviewing data transcription from source to eCRF, they can devote more time to process and compliance issues.”

	RBM uses targeted approaches to remote or cloud-based monitoring of subsets of the clinical trial data, and can take the form of partial SDV and statistical risk-based algorithms based on fixed risks tied to the protocol. TransCelerate BioPharma, a non-profit focused on innovation in R&D, has provided further clarification into RBM through its position paper on the subject.

 It defines five steps, starting with risk assessment, and ending with monitoring execution (see chart).  As part of this effort, TransCelerate makes frequent reference to use of technology for central or off-site monitoring to make the desired efficiency gains without impacting patient safety. The intent is to reserve onsite monitoring to further support site process, patient safety, and data quality.

	The new cloud-based analytics technologies are meant to improve the collection and transmission of clinical trial data from disparate sources.  To make meaningful insights from the data, stakeholders need to be able to generate 

 reports and develop operational metrics that determine if milestones and timelines are being met, if there are safety signals related to the investigational product, and how sites are performing relative to others.

	With a single interface, it is possible to collect study-related trial data housed in multiple systems from multiple vendors, such as EDC, interactive voice response systems (IVRS), and clinical trial management systems, and use it to answer key questions. With the help of a self-service visualization-based data discovery environment, stakeholders can visualize up-to-the-minute study trends, such as enrollment rates, timely entry of data, degree of data quality, abnormal lab values, etc. Without these reports, stakeholders have limited ability to determine the status of an ongoing trial.  

	Anecdotal claims from Comprehend Systems, a provider of a cloud-based interface, suggest that use of this technology may lead to a 30% decrease in site monitoring visits by utilizing visualizations of key performance indicators such as recruitment pace and drop-out rates. Again, anecdotally, there have been 50% reductions in database lock time, and 3-4 days per month per trial saved in clinical data review time as a result of having actionable data available in a unified reporting interface.

	Traditionally, the major way of analyzing volumes of data has been by accessing a user-controlled data warehouse, a methodology that is slow, costly, and inflexible and requires constant re-programming and re-validation as questions change. As part of that effort, stakeholders have been faced with the significant challenge of integrating clinical, operational, and safety data from different sources in different formats. Bringing those data together into one location where they can be linked together for analysis has been rendered all the more difficult as there is no standard way of collecting those data. Because of these issues, companies that embark on building out a warehouse can spend years developing it, so using a provider may be a viable option. 

	With the advent of a hosted cloud-based non-standard clinical data warehouse, which is essentially how the interface operates, it is possible to ask the necessary questions without having to invest the resources needed to maintain it in-house. Validation is still needed, but programming is handled by the provider’s application. In addition, steps such as infrastructure analysis; extract, transform, and load; and performance tuning can be managed by the provider. This effort will be further facilitated once the industry develops standards for aggregating data in a data warehouse.

	With the implementation of the described cloud-based technologies, a change in the current business model is required. This model was developed decades ago, in response to a time when clinical trials were very different from today’s global multi-site approach.

 Even the significant introduction of EDC, which brought huge strides in terms of edit checks, a better query process, and faster viewing of clinical trial data, was still rooted in the traditional business model with legacy approaches to monitoring and validation. By comparison, other data-heavy industries have changed their underlying business models, and research suggests a similar change is in order in the clinical trials sector.

	Not surprisingly, the industry is in various stages of adoption, reflecting different sizes of companies and levels of sophistication among stakeholders. David Scott, President and CEO of Palm Beach Research Center in West Palm Beach, Florida, comments that use of technology is on the upswing, but notes that his site does not use eSource documents. “We have paper source documents, and by not making that transition, that is one huge amount of responsibility we don’t have to take on. At this point, we think of cloud-based solutions as best suited to business documents, not study documents.” 

	Regarding RBM, he explains that only a few of Palm Beach’s sponsors are using the technology, but more are trying to make that transition. Similarly, Laura Whitaker, Neurosciences Research Coordinator at Hoag Memorial Hospital in Newport Beach, California, comments that only one study is 100% RBM, and in that case, she speaks with the monitor by phone. 

	An industry veteran, Whitaker appreciates and welcomes the changes offered by technology, but feels that, at least to some degree, the human touch is getting lost. She says her site is starting to notice that streamlined processes and technologies are shortening the research phase by getting the data collated and meeting contracted timelines, “but we are losing the human element with RBM. The monitor can see the clinical trial data remotely, but they aren’t seeing documentation of the informed consent process or the actual signature of the investigator on various documents. Also, they aren’t seeing any notations, such as why the patient was out of window or why certain factors were not reportable to an IRB,” she explains.  Other comments appear in the sidebar at right. 

	As regulators, sponsors, CROs, sites, and other stakeholders come together to bring greater efficiencies to the beleaguered clinical trials industry, technology and process change have been highlighted as key. The days of paper-bound methodologies are diminishing as cloud-based solutions are stepping in, but there is a range of adoption of these new solutions from modest to full-blown.

	How technology adoption changes the business model will be a closely watched subject as the need to rein in costs, streamline operations, and adhere to regulatory guidelines steers the clinical trials industry toward more timely development of safe and effective therapies that benefit patients across the globe.

Rick Morrison is CEO of Comprehend Systems.

Getz KA. Evolving Challenges and Opportunities for Clinical Trials Conference presentation, Clinical Trials Ontario, Feb. 2014 (data: JA DiMasi). 

Kramer JM, Schulman KA. Transforming the economics of clinical trials. Institute of Medicine. 2012. Available at: 

http://www.iom.edu/~/media/Files/Perspectives-Files/2012/Discussion-Papers/HSP-Drugs-Transforming-the-Economics.pdf

Final Guidance on Electronic Source Data in Clinical Investigations: Promoting eSource Data Capture.  FDA Webinar, January 29, 2014. Available at: 

http://www.fda.gov/Training/GuidanceWebinars/ucm382198.htm?source=govdelivery&utm_medium=email&utm_source=govdelivery

E-Clinical Solution Software Market is expected to reach USD 6,515.3 million in 2020. Transparency Market Research. July 3, 2014.        Available at: 

http://www.transparencymarketresearch.com/pressrelease/e-clinical-solution-software-market.htm

Weisfeld N, English RA, Claiborne AB. Envisioning a transformed clinical trials enterprise in the United States: Establishing an agenda for 2020. Institute of Medicine. 2012. Available at: 

http://www.iom.edu/reports/2012/envisioning-a-transformed-clinical-trials-enterprise-in-the-united-states.aspx

Guidance for Industry: Oversight of clinical investigations - A risk-based approach to monitoring. Food and Drug Administration. August 2013. Available at: 

http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM269919.pdf

Guidance for Industry: Electronic source data in clinical investigations. Food and Drug Administration. September 2013.Available at: 

http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM328691.pdf

Draft Guidance for Industry: Providing regulatory submissions in electronic format - Standardized study data. Food and Drug Administration. February 2014. Available at: 

http://www.fda.gov/downloads/Drugs/Guidances/UCM292334.pdf

Reflection Paper on expectations for electronic source data and data transcribed to electronic data collection tools in clinical trials. European Medicines Agency. June 2010. Available at: 

http://www.ema.europa.eu/docs/en_GB/document_library/Regulatory_and_procedural_guideline/2010/08/WC500095754.pdf

Reflection paper on risk based quality management in clinical trials. European Medicines Agency. November 2013. Available at: 

file:///C:/Users/Customer/Downloads/EMA%20Reflection%20paper%20risk%20based%20QM%20in%20CT_2013%20(4).pdf

CenterWatch Drugs in Clinical Trials Database, 2014.

Pharmaceutical Research and Manufacturers of America, 2014 Biopharmaceutical Research Industry Profile. Washington, DC, April 2014. Available at: 

Neuer A. Great expectations for the eTMF.  Clinical Informatics News. March 12, 2014. Available at: 

http://www.clinicalinformaticsnews.com/eCliniqua_article.aspx?id=136178&terms=Neuer

Executive Summary: Veeva 2014 Paperless TMF Survey: An industry benchmark. Veeva Systems. 2014. Available at: 

Neuer A. Veeva survey highlights variation in eTMF solutions. Clinical Informatics News.   August 2014.  Available at: 

http://www.clinicalinformaticsnews.com/cln/2014/8/13/veeva-survey-highlights-variation-eTMF-solutions.html

Neuer A. Power Source. International Clinical Trials. August 2014; pp 54 – 58.

Koreith K. The high cost and questionable impact of 100% SDV. CenterWatch Monthly 2011;18(2). 

Medidata 11/2013 Fact Sheet. Medidata CRO Contractor: Fair Payment for CRO Services. Available at: 

Position Paper: Risk-based monitoring methodology. TransCelerate BioPharma. 2013. Available at: 

http://www.transceleratebiopharmainc.com/wp-content/uploads/2013/09/Risk-Based-Monitoring-Methodology-Position-Paper.pdf

Articles

How the use of eSource, eTMF, and other cloud-based solutions are changing clinical trials

Technology’s Role in Clinical Trials

The emergence of EDC systems to collect trial data electronically at their source has significantly advanced clinical trial research over the past decade. While this shift towards web-based collection and management shows improvements in achieving cleaner data and more efficient processes, there is still a lot of room for improvement. The next great advancement in clinical trials will require revamping the currently onerous process. In the coming year, we expect to see sponsors focused on making better use of their data investments that are now electronically available through EDC and other systems.

	Designed specifically to replace error prone and ineffective practices of paper and eCRF collection methods, EDC systems were merely digitizing an archaic process. Other than reducing paper-based systems, not much has changed. Sponsors haven’t received better visibility into their entire clinical portfolio, faster study startup, or better data availability. Additionally, with so many different types of commoditized EDC systems available, communication across the varying systems is greatly delayed.  Data collection during a trial is necessary but it is no longer sufficient.

	The industry continues to look to incorporate Electronic Health Records (EHRs) in the clinical trial realm to supplement the constraints of EDCs.

	EHRs are now widely adopted by hospitals and clinical trials look to reuse the data for more real-world evidence. EHRs can help supplement clinical trials with a more complete picture of a patient, for example by providing a more thorough medical history. EHRs also have the potential to provide clinical researchers with the data of millions of patients to researchers, which can enable a more thorough or helpful understanding.

	The large quantity EHR data can also be a valuable mechanism for protocol design and patient recruitment. Analysis can be launched against the volumes of EHR data to identify patients who meet study criteria. Detailed patient health records help to reduce errors by identifying safety concerns prior to patient enrollment.

	The evident use case of EHRs for recruitment has already attracted pioneers such as the Mayo Clinic, Penn Medicine, and Giesinger Health, who have all seen increases in patient identification, enrollment and referrals. Additionally, the established ECR4CR program demonstrates effective use of international EHR data while protecting patient privacy. The program has successfully accessed clinical data from more than five million patients, expanding patient information on a global scale. As EHRs continue to deliver greater volumes of data, it is critical to incorporate processes for enhanced interpretation.
	 

	In the year ahead, we expect analytics platforms to play a key role in unlocking the potential of EHR data, particularly cloud-based systems that can bring all relevant data together in one place.

	Cloud based tools facilitate real-time access to data, supporting Sponsors and CROs in running queries as often as necessary. Because there remains an array of EDC systems and the widespread adoption of EHR systems is still distant, utilizing these tools will leverage the increasing volume of available data to ensure better patient safety and bring new treatments to market sooner.

In the coming year, we expect to see sponsors focused on making better use of their data investments that are now electronically available through EDC and other systems.

2015 and Beyond: What’s Next for Clinical Data Management and Investments

 Comprehend CEO Rick Morrison to shares his thoughts on 2015 predictions for clinical R&D.

Beyond innovation, smaller sponsors will bring more drugs to market

 – Gone are the days when big pharma were the sole drivers of innovation and blockbuster drugs. But the days of big pharmas buying smaller biotechs to enhance their pipelines are also dwindling. More and more of these smaller and mid-sized sponsors will stay lean and nimble and focused on what they do best – innovative R&D based on better, safer, faster trials – by leveraging top specialized CROs, technology vendors and sales and marketing organizations. M&A will continue, but the stakes will be higher as these small and mid-size pharmas gain steam.

 – The CRO market is due for a significant shake up. More and more sponsors need and are demanding access to their data along the course of their trials, and the CROs that are able to evolve with the times will be the ones who will win. The repackaging or retooling of existing services won’t cut it as drug and device developers are looking for outsourcing partners that support new ways of bring treatment to market. As a result, today's market leaders are at risk of falling to competitors who are more specialized and open to new approaches to clinical development.

Clinical data collection becomes commoditized 

– When it comes to EDC being viewed as a static repository, we are basically already there. Adding EDC into the mix 10-12 years ago only digitized an already broken process. In the year ahead, we’ll see more sponsors focused on reinventing clinical development, which means investment in better analytics and access to data to enable key approaches like risk-based monitoring, adaptive trials, cross-study insights and identifying potential threats to data/trial integrity.

Comprehend CEO Rick Morrison shares his thoughts on 2015 predictions for clinical R&D.

2015 Predictions for Clinical R&D

For the past few decades, contract research organizations (CROs) have successfully fulfilled a ‘body-shop’ role in clinical development, supporting trials with manpower, deployment resources and a core competency of knowledge around how to execute studies. As trends like risk-based monitoring are adapted on a larger scale with the goal of reducing trial costs, trial execution will continue to become more efficient – resulting in a slash to CRO budgets and demand. With less budget and reduced need for traditional CRO value, the existing number of CROs will compete for the same amount of work. When the market hits this saturation point, CROs will need to prepare for a complete change in their role within the industry– a change that must be embraced by the existing business structure to avoid cannibalization.

Data and technology will undoubtedly change the trial landscape – trends that CROs must capitalize on in order to reinvent their differentiating factors and hone in on areas of expertise. Right now, the industry is waiting for a CRO to take this leap and revamp how they contribute to the trial process, but the risk of deviating from standard course is holding most back. CROs must embrace this change to revolutionize the existing business structure and seize the opportunity to increase market share by being a thought leader in this new technology-driven era of trials. The core values of CROs will remain the same – therapeutic area expertise, trial implementation, recruitment, etc. – but margins will change. By building a CROs expertise on top of new technologies and data tools, the trial process will become much more scalable and efficient with each player - EDC vendors, sponsors, etc. – doing what they do best. 

Here are four core things that CROs need to do to stay relevant in a changing industry:

Drive change in the CRO business to increase market share

Embrace the role of data and advanced technology in trials

Capitalize on value-added service options to differentiate, including therapeutic areas, trial implementation, IT solution engineering and consulting services

Collaborate with sponsors to take over IT functionality, easing the burdens of sponsor cost cuts and outsourcing scenarios

For the past few decades, contract research organizations have successfully fulfilled a 'body-shop' role in clinical development...

Beyond the Body Shop: How CROs Can Stay Relevant in a Saturated Market

Cloud computing is changing enterprise across all industries, and the recent success of Veeva’s IPO is further evidence that the life science industry is no exception.

Ten years ago, pharmaceutical companies and medical device makers were not comfortable putting their data in the cloud. There was an (unfounded) fear that cloud companies were not as secure as onsite deployments. Cloud EDC vendors like Medidata were just forming and paving the way to convince sponsors that actually data was safer in the cloud.

Fast forward to today, and the industry is completely different. Medidata is a $3.1 billion company, publicly trading on Nasdaq since 2009. Veeva, now public since October 16, is hovering around $4.5 billion. I founded Comprehend to provide cloud analytics and collaboration across different data collection systems, but there are also dozens of other cloud technology vendors, like Medrio, that’s created a simple yet powerful EDC - and we will continue to see more. 

Veeva’s successful IPO is proof that cloud options are serious alternatives to onsite deployments that were most popular two decades ago. Here are the primary reasons every life sciences company should consider cloud, if they haven’t already:

Lower ongoing cost – Cloud vendors have several cost advantages over an in-house deployment. Cloud vendors can take advantage of massive economies of scale, meaning that they can pool certain resources across all of their customers in ways that individual sponsors cannot. For example, a cloud vendor can hire a single system administrator that can maintain a dozen or more individual systems, whereas a sponsor would only be able to use that system administrator for themselves. The cloud vendor can spread the cost across several of their customers, ultimately offering a cheaper option overall.
  

No capital expense – When a sponsor buys an onsite system, they need to provision hardware and internal resources to setup and maintain the computing infrastructure, not to mention that onsite software typically costs a lot of money upfront. With cloud technology, there often is no capital expense up front, so sponsors can simply start subscribing and pay a monthly or quarterly operational expense.
  

Pay only for what you use – Not only is cloud much cheaper to start with, but it’s more capital efficient. Sponsors pay only for what they use. If they start using more, they pay more. If they start using less, they pay less. 
  

More secure – Cloud vendors have much more experience with computing infrastructure than sponsors due to the nature of the number of different sponsors that they serve. Similar to efficient pricing plans, vendors can take advantage of economies of scale in regards to security as well. Because cloud vendors work with more systems and data, they can afford (and become) security experts much more easily than sponsors.
  

Focus – It’s important for every company to focus on their core competency, which is why more and more sponsors are outsourcing trial implementation to CROs. The same can be said about technology. Let vendors focus on running, maintaining and securing technology infrastructure so life sciences companies can focus on their core competencies. 
  

Scalable – Cloud vendors are used to executing much larger deployments, and several simultaneously. They already have the infrastructure in place to scale as necessary, so it’s much easier for them to do than the sponsor internally.
  

Quick deployment – Cloud systems can be up and running much quicker than onsite deployments due to less of a need for elaborate provisioning, planning, training, etc. Cloud vendors have brought their systems online many times before, whereas when a sponsor implements an onsite deployment, it’s usually their first time and takes months or years. Cloud deployments can often be up in running in days or weeks.

These are some high level benefits of cloud for life science companies. The most important point is that it’s happening, as Medidata and Veeva are proving. We are still in the very early days of cloud adoption in life sciences, with the biggest value savings still ahead of us. 
  
If they haven’t already, every life sciences executive managing clinical operations should consider fully embracing the cloud.

Cloud computing is changing enterprise across all industries, and the recent success of Veeva's IPO is further evidence that the life science industry is no exception.

Veeva's IPO: Life Sciences Increases its Commitment to the Cloud

 – What has always worked in the past will not necessarily work in the future (in fact, it most certainly will not). In the year ahead, proliferation and adoption of powerful technology to not only make processes more efficient, but also provide clarity into what’s actually happening across a sponsor’s portfolio of trials. It will enable sponsors to expect more from their CROs, and force all companies to modernize.  This hasn’t been possible in the past, but now that EDC systems are commonplace, along with the power of the cloud, will enable companies to really take advantage of their data in ways previously impossible. 
  
I’ve talked to several sponsors who are dropping partner CROs that they’ve worked with for years, because the old-fashioned CROs are unwilling to do things differently. For example, the sponsors want access to interim data, and the CROs are unwilling to do it because “this is the way we’ve always done it”. The sponsors, in response, are simply finding new CROs to work with. 

In 2013, CROs will learn to adapt to the new requirements of their sponsors, or they will be forced to go out of business (or at least, downsize).

2. Trials will (finally) become more dynamic

 – We’re already starting to see new processes that allow for better reactions throughout a trial, like risk-based monitoring, centralized analysis, adaptive trials, and more specifically-targeted treatment for patients – but this will take off in the year ahead. Companies are vigorously pursuing adaptive clinical trials, and this trend will continue.
  
  The FDA is continuing to work with various sponsors to refine risk-based approaches to monitoring. This will continue to evolve. They’re also exploring new ways to run and structure adaptive clinical trials, and this trend will continue en force.
  
In 2013, companies will continue to push the boundaries of adaptive clinical trials and risk-based monitoring, and successfully begin using these techniques to run more efficiently, and cheaper, than traditional methods.

3. Sponsors will take on more risk in R&D

 – Sponsors need to start targeting blockbuster drugs that will cure diseases ailing millions of people. Over the past few years, we’ve seen large pharma shy away from this, due to regulatory or litigation fears. However, the technology support infrastructure is in place to allow them to confidently pursue more common indications.
  
In 2013, several large companies, who have been focusing primarily on orphan drugs, will announce that they’re pursuing research and/or starting trials on potential blockbuster drugs.

– The massive buildup in the number of eClinical systems will continue, as companies continue to add additional data collection systems into the mix and new vendors spring up. The industry would love to start consolidating, but this will never be possible. Instead, they will start relying on technology that connects these systems instead of creating new silos.
  
In 2013, several new mergers will result in completely incompatible data collection systems. Several companies will realize that their sizable investments in data warehouses were wasted. Several companies will start using new, modern technology (shameless plug: like Comprehend), that will help them integrate their systems.

 – Now more than ever, pharmas are facing increased pressures from generics, regulator bodies and lawsuits. The long term impact will be that companies that can adjust and create scalable and agile businesses will succeed, those that cannot will disappear. Sponsors that embrace risk-based monitoring and adaptive clinical trials will be able to drastically cut costs, those that don’t will go out of business. CROs that embrace opening data and analytics to their customers will get new business, those that have done “what they’ve always done” will disappear. 
  
In 2013, there will continue to be large cutbacks at companies that aren’t modernizing.