Tanya is Vice President of data strategies and solutions at Bioforum. She has vast experience across the industry through her current role at Bioforum, as well as the 14 years she spent with IQVIA (legacy Quintiles). Throughout her career, Tanya has worked with multinational pharmaceutical companies as well as small-to-mid size biotech and startups. She has led various data management operations and programs, heading numerous innovation teams and spearheading the development of strategies for customized data delivery solutions, focusing on timely, quality data.

A certified clinical data manager (CCDM, SCDM), Tanya holds a M.Med.Sc in Hematology and Cell Biology from University of the Free State in South Africa. She also has a project management professional certification (PMP, PMI).

Tanya du Plessis, Brand Insights Contributor, VP, Data Strategies & Solutions, Bioforum the Data Masters

For years now, there’s been lots of discussion about electronic source (eSource) and its potential to transform clinical trial processes. The shift from an environment in which what is currently considered “source data” – essentially a combination of paper and electronic data recorded at the point of generation – to a future state in which data is only initially recorded in electronic format is already increasing efficiencies in clinical trials, enabling faster access to research data and more rapid decision making.

While eSource is here to stay, its adoption in clinical trials has been fragmented and slow, particularly among resource-constrained emerging biotech and biopharma startups. Understandably, among them, concerns include a range of different potential challenges, including those related to regulatory compliance, technology barriers and costs of change management. These concerns, however, should be considered in the context of the success of early adopters and growing interest and support from the FDA.

Innovative new technologies and increasing access to them are enabling exciting opportunities to collect higher quality data more quickly than ever before. These technologies have enhanced speed, efficiency and data quality for clinical trial sponsors and their CRO partners, eliminating the burdens of paper-based data management. And now, eSource is bringing these benefits to the site level.

Still, implementing and scaling eSource is a daunting challenge. It can, however, be managed with the right strategy and framework, even by smaller companies with limited budgets and less experience. What’s important is to understand the process of moving to a more electronic process in data capture does not need to be an “all-or-nothing” approach.

Below are questions that frequently come up in our discussions with startups and emerging biotechs. We hope the responses provided will be helpful in guiding discussions on eSource and how to navigate its adoption.

Source documentation, according to the FDA, is the initial documentation of data within a clinical study.For example, source data may include initial blood pressure, height, weight and temperature recordings. Throughout the clinical trial process, integrity is then maintained by using an audit trail to track any changes or modifications that may occur to these recordings.

eSource is the digitization of this process. Instead of recording source data manually and then later transferring this data to an online data base, eSource captures data electronically from the start, directly into an CDMS (clinical data management system). With eSource, all source data must be electronic and must be followed with a detailed electronic audit trail.

What is the difference between eSource and eCOA (and ePRO)?

Simply put, eCOA (electronic Clinical Outcome Assessment) is a type of eSource, a method of capturing data electronically in clinical trials, and ePRO (electronic Patient Recorded Outcomes) is a type of eCOA. ePROs and other forms of ECOA use handheld devices, tablets and the web to enable patients, clinicians and caregivers to directly report outcomes, resulting in more granular endpoint data.

Beyond those focused on clinical trial sites, what benefits does eSource offer?

eSource has huge cost and time-saving implications for clinical trial stakeholders across the industry and sponsors of all sizes. For starters, using eSource results in greatly reducing the need for paper storage, source data verification (SDV) and travel among clinical trial site monitors. Utilizing eSource also lends itself to improving data integrity by allowing direct data flow from the source to the sponsor’s system, with minimal or no human intervention. Furthermore, by enabling real-time remote data sharing, eSource facilitates collaboration among trial stakeholders and across geographic barriers.

It depends on how clinical trial sites capture study data. Electronic data capture (EDC) is used when sites capture data on paper source forms and then transcribe the data into a database. eSource is used when the site’s paper process is replaced by electronic capture of patient data. For example, when data is entered directly into a tablet and paper is not used to capture information.

If a company decides to only capture source data electronically, directly into a database, then, yes, eSource can replace EDC. However, if only few components of source data are captured electronically (for example, only patient feedback forms) and the majority of patient visit data are still captured on paper (and then transcribed into a database), a company can still use an EDC database and integrate the electronic source data into the EDC database. 

Similarly, if the majority of data will be directly entered, electronically, into an eSource database, but one or two components may need to be manually transcribed (for example, a specific evaluation score or laboratory result), then an eSource database can be used. Those specific transcribed forms can be labelled “transcribed forms” andmanaged as such by the clinical team.

What are the pros and cons of adopting eSource?

Experience has shown us that the advantages of using eSource include high-quality data with less queries and no entry delays, and real-time access to insights that enable more informed decision making. However, experience has also shown us that the change management process can be challenging, especially because of how deeply embedded paper processes are in most companies’ SOPs. Proper planning and monitoring of eSource adoption is critical, particularly for site documentation management and clinical monitoring teams. It’s important to ensure necessary changes are being made and, for example, remote monitoring is taking place and source document verification (SDV) is reduced where possible.

While change management is often associated with increased costs, the transition to eSource can be done cost effectively. Forming partnerships with the right service providers, who can provide training on eSource data capture and the associated change management processes is also a key factor to enabling success.

What’s the best way to get started with eSource?

We highly recommend identifying service providers with the right experience, who can be true partners and support you in developing a strategy that fits your needs and through the change management process. We have also found that learning more about different eSource technology platforms is helpful. Requesting demos from various service providers is a good way to do that and also get a feel for which eSource solution will meet your organization or study’s needs. Lastly, when adopting eSource in your clinical study, ensure data management is included in study design discussions, by the protocol formation phase. Doing so will help enable time and cost efficiencies, and contribute greatly to optimizing study design quality.

Acceleration of eSource adoption is a critical step in modernizing the conduct of clinical trials. Realizing this vision – one in which all source data, acquired through any context, whether via a healthcare professional, patient or caregiver, are completely electronic, high in quality, and meet the standards of regulators worldwide – is a significant effort. It will involve alignment and dedication from all industry stakeholders, including patients, clinical trial participants, sites, technology vendors, standards organizations, regulators, payers, and sponsors, whether from large multinationals or small companies. That’s why raising questions and creating a dialogue on the topic is so critical.

What else would you like to know about eSource? We’re eager to continue this discussion, incorporating as many perspectives as possible, so please feel free to send questions or thoughts to 

Bioforum the Data Masters is a data-focused Contract Research Organization (CRO), supporting clients in the utilization of their clinical data and guaranteeing its integrity and accuracy. Our goal is to consistently improve and innovate data processes to allow for the most efficient data submissions for our clients across the life sciences industry and the patients they serve.

Articles

Ready for eSource? Considering Options Beyond EDC

In our last blog, we discussed how to avoid and reduce the impact of momentum-breaking clinical trial amendments. One of the key ways to mitigate this risk is choosing the right electronic data capture (EDC) system to collect and manage your clinical trial data. The challenging part about this seemingly simple task is that it can quickly become very overwhelming. Sponsors will often express frustration, saying things along the lines of “the process started out well, but, now that I have spoken to a few service providers, everything is starting to blur.” With so many EDC providers offering a range of solutions, how can startups or small biotechs ensure they select the right tools with the capabilities to fit both existing and future needs? How do you begin to sort through all the choices and find the right EDC platform or solution?

As with any investment, you need to do some homework before making a decision. I sat down with Richard Young, Vice President, Vault CDMS Strategy at Veeva Systems, to discuss what that entails when it comes to shopping around for an EDC and how sponsors within smaller organizations can ensure they are set up for long-term success.

Below are some questions that often come up in our conversations with clients about the EDC-selection process and our thoughts on how sponsors can best address them.

What questions should sponsors ask as they evaluate EDC solutions?

It’s important to begin by asking what functionality is necessary. This may seem obvious, but this critical step often gets missed. It’s very easy to be lured in by the bells and whistles many systems offer, but do they address your company’s needs for specific studies? Identify these needs and then analyze and prioritize them. Doing so will help you narrow down and simplify the criteria on which to base your decision and how to potentially adjust your budget. The next subject to tackle is whether the EDC integrates with other systems in your technology portfolio and how the EDC vendor’s pricing fits in with your budget.

Absolutely. Once you have this information in hand and set key priorities, there are several other questions that should also be kept top of mind. For example: Is the system easy to use? Does the system fully support compliance with CFR Part 11? How long will it take to implement the system? What kind of training and support services does the vendor offer?

A solution that is easy to use, with an intuitive design, will simplify complexity. During demos, be sure to inquire about a straightforward way to set up a protocol, accurately enter data and efficiently manage queries. It’s also critical to get ahead of potential compliance issues by making sure the system fully supports CFR Part 11.

What about a service provider or vendor’s experience? Is that a critical factor?

Experience is always an important factor. We encourage our clients to take vendor stability into consideration. What you want to know is that the service provider is going to be there for you in the long run by investing in its technology, adding and enhancing capabilities to support innovation, scaling needs and long-term growth.

Asking about a vendor’s experience is essential. But it is equally important to recognize that, within the world of clinical trials, our current processes are broken and require new thinking and new technologies. As an industry, we have become experts in creating workarounds and patches using traditional EDCs that mimic paper. What’s happened is that these limited, old-fashioned tools now dominate our data collection strategies, creating distractions that waste time and money. A broad range of service providers and suppliers offer EDC, as it has become the “industry standard,” however the features and functions that separate “traditional” and “modern” EDCs are worlds apart. It’s important to find a technology partner that can offer fully integrated APIs for other systems, flexible and automated workflows, and productized functionality as opposed to external custom functionality. A modern EDC creates a unique, bespoke and tailored user experience for each stakeholder involved in clinical trial data collection and management.

In addition to experience, what are the top considerations an emerging company must consider when selecting a technology partner?

 It comes down to cost, efficacy, adaptability and level of “after-sale” support available. We encourage our clients to carefully consider the following:

 Great question. First, you need a technology that enables you to run the trial you wish to perform, not the trial that the technology will limit you to. The high cost of making changes in traditional EDCs has anchored our vision to one-dimensional studies for too long. Modern trials are multi-dimensional and fluid in execution.

Second, you need a partner who will genuinely invest in your success. Collaboration is the key to delivering trials successfully and that starts with true partners coming together, working together and, of course, problem solving together. For me, this starts with technology that provides greater agility and extends through a delivery team that is caring and responsive to the sponsor’s needs. Every vendor should be attentive during the sales cycle and read through recent customer case studies to get a better sense of customer needs.

What are the main causes of database-build delays? And how do sponsor and CRO cycle times compare for database build, data entry and database lock?

There are several factors that contribute to database delays, but typically we see three main causes: (1) building on unclear protocol specifications, (2) building on unclear database design specifications (if applicable); and (3) technical restraints within an EDC platform that require a lot of customizations (and thus additional manual programming or work-around solutions). The first two causes result in numerous back-and-forth discussions around designs of forms, edit checks and many drafts of the CRF/edit checks. While the third cause is more technical, it requires manual effort (and continuous problem solving), which can be a real source of frustration when everything else is in place to expedite a study build.

 This is a tricky question, as it really depends on when you start and stop the clock. From my perspective, the clock starts when you have a “good” draft protocol, which can be used in a meeting kicking off an engagement between sponsors and their service provider partners. For a traditional EDC study build, it typically takes sponsors 12-18 weeks and CROs 8-12 weeks. Both timelines are far too long.

Tufts Center of Drug Development in 2017-2019

, protocol changes are the primary cause of delay during database builds. The impact of these changes is amplified by other common causes, which are User Acceptance Testing (UAT) and limited design functionality. Securing consensus among stakeholders is difficult and time consuming. Therefore, it is critical to select an EDC with design tools that support collaborative decision making and real-time changes.

There are numerous differences that account for different cycle times among sponsors and CROs, but the most common factors that extend database lock times have to do with the growing volume of data coming from external sources.

What are the best ways to overcome clinical data management challenges including protocol changes, reporting and more?

 Ensuring you have libraries and standards to work from at study startup is a huge help, even if these need to be customized for specific protocols because they save considerable time. Of course, amendments are often unavoidable and therefore managing them must be considered when selecting an EDC. When it comes to amendments, some platforms are much more nimble than others.

 Put simply, select a flexible solution that embraces the need for change. Look for purpose-built capabilities to manage change, such as casebook versioning so investigator sites can adopt the latest version as soon as they receive IRB approval. Another example would be push-button deployments, such that any and all changes can be deployed in minutes, without migrations or downtime for sites.

Agile trial design is an important factor when planning clinical studies. How can companies address and build this into their data management processes successfully?

First and foremost, by selecting an EDC platform that allows for more agile trial design. Once that’s in place, sponsors must ensure that the teams working on the trial understand how agile design can be utilized to bring efficiency to the entire study process. This means understanding the end user’s experience as well as the data management cleaning, and quality-by-design concept that is required by regulatory authorities.

 An agile build process fosters better collaboration and decision-making within the study team. Rapid iterations help you achieve user acceptance up-front, early in the build, which reduces late-stage changes as well as findings during UAT. Your technology should provide reports with efficiency and effectiveness metrics. These then inform decisions on what works and what doesn’t, so you can course correct and move forward decisively.

Do you have any final advice for those going through the vendor selection process?

 Ask questions, a lot of questions. Ask to see and experience the features you need, and then ask the technology company (and their CRO partner) what else they can show you. Beyond that, dare to think fresh, dare to park the old methods and seek a better way. Technology is moving fast, faster than you may even imagine. Good technology can support your trial design and execution goals in ways that you may not yet have considered. We used to design trials and then ask how we can deliver them, but today, we can ask what technologies can do for us, and then look at how we can use these features to better our research.

 Approach your vendor selection process with structure and purpose. Make sure you know what you need from the system, what you would like and what would be the absolute best-case scenario to meet your needs, for all stakeholders—data mangers, clinical teams and, of course, the research sites. With this knowledge in hand, you can be more specific with service providers about what capabilities to show you during demos and avoid generic presentations. Following this approach will make it easier for you to do an apples-to-apples comparison and assess which EDC service provider offers the best fit and is the right choice for you.

In our next blog, we’ll talk about how to leverage standards to increase clinical trial efficiency and reduce costs. Companies may think they are too small to establish standards, or are feel overwhelmed by the thought of setting them up. However, there are easy ways to build standards into the process without incurring significant costs. Stay tuned for more on that!

 is vice president of data strategies and solutions at Bioforum the Data Masters. She has vast experience across the industry through her current role at Bioforum, as well as the 14 years she spent with IQVIA (legacy Quintiles). Throughout her career, Tanya has worked with multinational pharmaceutical companies as well as small-to-mid size biotechs and startups. She has led various data management operations and programs, heading numerous innovation teams and spearheading the development of strategies for customized data delivery solutions, focusing on timely, quality data. ​ 

A certified clinical data manager (CCDM, SCDM), Tanya holds a M.Med.Sc in Hematology and Cell Biology from the University of the Free State in South Africa. She also has a project management professional certification (PMP, PMI).

Welcome back to the Forum for EmergingBio's Outsourcing Decisions!

Overcoming the Paradox of Choice: Selecting EDC Capabilities to Fit Your Needs

The unplanned costs and delays associated with protocol amendments are a major source of frustration and concern, given their impact on trial budgets and timelines. And now, with the COVID-19 pandemic, dealing with study amendments has become even more challenging, as clinical trial sponsors and their research partners adapt processes and technologies to keep studies moving forward amid the pandemic in an environment where regulations continue to evolve.

The longer your study runs and the more complex it is, the more likely you are to have a mid-study protocol amendment. But even in a pandemic, it’s important to remember that there are preventive and proactive measures that can be taken to reduce the likelihood and impact of some amendments or, at the very least, minimize disruption and ensure the continued productivity of the study team. The more prepared we are for amendments, the more efficient we can be when implementing them and successful in terms of keeping the clinical trial on track.

It all starts with getting the right people around the table

Having a well-defined data strategy with built-in flexibility can curb the high impact of amendments. However, there is a misperception that aligning with a data strategy from study start is not important and it, therefore, gets deprioritized until data starts coming in. Needless to say, this is the common pitfall and trying to plan amendments at this point leads to a number of challenges which have time and cost implications.

The good news is that a flexible data strategy is actually something that can quite easily be achieved, particularly for startups and smaller companies that can avoid the bureaucracy that slows down larger organizations. Working together, in-house experts and trusted partners (covering internal knowledge gaps) should lay out the short and long-term data goals. In doing so, they can define a flexible data strategy that takes in account the risk areas related to data collection and management from the planning phase. For example, this integrated team can, early on, identify mitigations around these areas and supportive tools/applications that can be used to manage unanticipated changes relatively easily (and that are good for function and cost). The key is striking the right balance between following best practices and thinking outside of the box, all while staying within the agreed upon budgets.

A flexible data strategy should be able to accommodate anticipated amendments or changes (i.e., known risks) as well as unanticipated changes (i.e., unknown risks) with as little impact as possible. However, if the data strategy is retroactive and not embedded in the clinical program from the very start, it’s nearly impossible to avoid the chaos of substantive amendments that lead to significantly longer clinical trial cycle times and higher costs.

While no two organization or studies are the same and a template approach is never realistic or advisable, there are five major pillars of a data strategy and associated considerations for each that should be taken into account when you start writing a protocol for a clinical trial. This will enable the development of a data management strategy that is flexible in that it meets the specific, individual needs of both the clinical study and the sponsor’s short and long-term goals.

Remember, while working through these steps, do not limit your options based on in-house expertise or budget considerations. These are, of course, important, but the first step is to determine the best approach. From there, you can dive into the details of choosing the right partners to support your data strategy development and its management, and, in doing so, significantly reduce painful amendments or their impact.

It is also important to note that having budget constraints does not necessarily mean that a startup or small company has to give up on using the latest technology tools, standardization and/or consistency in clinical trial execution—a topic we will address in an upcoming blog, with a focus on how to:

Determine which services are essential and how to weigh the pros and cons when it comes to making budget decisions

Select the right tools/technologies (wading through the options)

Incorporate more standardization and consistency across all trials or study operations

Is there anything else you would like to hear about?

We’re open to evolving these discussion starters based on your input and would love to hear your thoughts, so please reach out and feel free to share ideas. Our goal is to create a forum for knowledge sharing that specifically addresses the needs of the small biotech and startup community.

Looking forward to continuing the small- and mid-size EmergingBio conversation!

 is vice president of data strategies and solutions at Bioforum the Data Masters. She has vast experience across the industry through her current role at Bioforum, as well as the 14 years she spent with IQVIA (legacy Quintiles). Throughout her career, Tanya has worked with multinational pharmaceutical companies as well as small-to-mid size biotechs and startups. She has led various data management operations and programs, heading numerous innovation teams and spearheading the development of strategies for customized data delivery solutions, focusing on timely, quality data. 

Welcome back to the Forum for EmergingBio's Outsourcing Decisions!  There is nothing quite like protocol amendments to put the brakes on a clinical trial’s momentum, which is why, in this blog, we are turning our attention to how to face this challenge head on.

Regret Comes Too Late: Getting Ahead of Protocol Amendments

	Welcome to the Forum for EmergingBio's Outsourcing Decisions!

	If you’re reading this post, chances are you work in clinical research and are well aware of the countless challenges that life sciences companies face today. Limited headcount and resources combined with increased pressure to contain costs, accelerate timelines and deliver novel, targeted therapies to market are not new challenges for our industry, but they are intensifying amid the COVID-19 crisis. As the biopharma industry traverses uncharted waters and doubles down on efforts to bring new therapies to market quickly, cost effectively and without affecting quality, the success of strategic partnerships and functional service provider models are more critical than ever before.

	But, how can small biotechs and startups successfully navigate the pathway toward finding an outsourcing partner, particularly in a pandemic? Does being “small” limit your options? How big a role should cost, therapeutic expertise and geographic location play when evaluating potential CRO partners? 

When the stakes are even higher from the get-go 

	The stakes are even higher for small biotechs to get CRO and vendor partnerships right from the outset than for Big Pharma as they simply cannot afford missteps. Avoiding mistakes can be especially difficult for emerging companies that do not have an abundance of in-house expertise and resources available, both for executing clinical trials and for risk management and contingency planning.  

	Unexpected “surprises” can be completely out of a company’s control, such as with how COVID-19 has affected certain trial operations. Current and planned clinical trials with traditional site-centric protocols suddenly cannot operate the way they were designed. Due to the social distancing and travel restrictions associated with the pandemic, for example, access to many clinical trial sites is limited for staff, principal investigators (PIs) and, most significantly, patients. Bigger companies have the advantage of being able to invest the time, resources and budgets into adjusting or rethinking their clinical trial design and data collection strategy to deal with these issues. Small biotechs and startups, however, simply do not have the infrastructure and expertise to mirror how big pharma is managing the crisis-all of which means a different approach is required for smaller companies.

Choosing the partner that’s right for you

	The core competencies CROs have built over the decades to service large pharma don’t always fit the fast-paced, entrepreneurial world of small biotechs and startups. Emerging companies need more flexibility and expertise on how to chart the fastest, most efficient course through clinical trials, mitigate any unnecessary risk of delays or failure, and increase the likelihood of launch-all just to survive long enough to have the chance to get their novel treatments into the hands of patients who need them most.

	If they don’t already outsource, emerging companies must first understand why they are going down this path in the first place and what they are trying to achieve-whether it’s clinical support to help with a study or regulatory work to drive data management. The key is to do your homework upfront. What may work for one small company may not work for another.

	And that’s where building relationships with the right partners who understand how emerging biotechs operate and appreciate the entrepreneurial culture of startups is crucial. CROs or service providers that support small biotechs must strike the right balance between following best practices and thinking outside of the box, while ensuring ongoing communication and to stay within the agreed upon budgets.

	All that said, the challenges that emerging companies face can also be seen as opportunities. They have fewer decisionmakers and are nimbler than larger companies weighed down by bureaucracy. Additionally, across the industry, there’s a perception that having budget constraints means that one has to give up standardization and consistency in clinical trial execution. While each trial has its own set of unique design aspects, the actual data strategy for each study does not have to be unique and there are numerous ways to bring this strategic thinking into a company’s processes and procedures, without incurring costs. And lastly, having a less rigid business environment creates the freedom to explore new ways of doing things, spurring innovation.

	The current environment we find ourselves in with COVID-19 illustrates this point; now, we all must rethink the way we’re conducting clinical trials. Indeed, the recent 

FDA Guidance on Conduct of Clinical Trials of Medical Products during COVID-19 Public Health Emergency

 entities conducting clinical trials, no matter the size or experience of the organization.

	Over the next few months, as we tackle the coronavirus outbreak and its fallout together as a community, we’ll be discussing all of these different challenges and opportunities in bimonthly blogs on 

		When to outsource and how to choose the right partners

		Identifying the right balance of oversight when working with a service provider and whether internal staffing investments are necessary

		How to incorporate more standardization and consistency across all trials or study operations

		Determining which services are essential and how to weigh the pros and cons when it comes to making budget decisions

What topics would you like to hear about?

	We’re open to evolving these discussion starters based on your input and would love to hear your thoughts, so please reach out and feel free to share ideas. Our goal is to create a forum for knowledge sharing that specifically addresses the needs of the small biotech and startup community.

	Looking forward to continuing the EmergingBio conversation soon!

	Tanya du Plessis	VP, Data Strategies and Solutions 	Bioforum the Data Masters	

As the biopharma industry traverses unchartered waters amid the COVID-19 crisis and doubles down on its efforts to bring new therapies to market faster, cheaper and without affecting quality, the success of strategic partnerships and functional service provider models will become more critical than ever before.

Tanya du Plessis, Brand Insights Contributor, VP, Data Strategies & Solutions, Bioforum the Data Masters

Articles

Ready for eSource? Considering Options Beyond EDC

Overcoming the Paradox of Choice: Selecting EDC Capabilities to Fit Your Needs

Regret Comes Too Late: Getting Ahead of Protocol Amendments

Bioforum, the Forum for EmergingBio's Outsourcing Decisions