4 Ways Technology Can Optimize Clinical Trial Workflows

4 Ways Technology Can Optimize Clinical Trial Workflows

In 2003, the cost to fully develop an FDA approved drug was $803 million. Now, however, that price has skyrocketed up to 2.6 billion and there have been no signs of this rate slowing down!

Unfortunately, while the price to develop drugs have increased, the rate of clinical trial success has decreased by about 12% in this span.

Therefore, this results in ever-increasing pressure to increase efficiency and reduce costs of clinical trials, which can be a major catch-22.

Site directors and managers are fighting an uphill battle to minimize complexity, ensure compliance, and streamline clinical trial processes.

On the other hand, there’s still a practical, regulatory, and ethical obligation to ensure data accuracy and scientific validity.

Clinical trial workflows – or the series of repeatable tasks required to finish a trial – are essential for effectiveness, reliability, and efficiency.

Women using advanced technology for organizing data.

Automation and workflow technologies help improve workflows…

…but they also may be challenging to implement. What you need to think is, will this all be worth it? The answer is yes.

After all, the majority of pharma companies don’t have in-house teams of software developers ready to take on the challenge of designing workflows which actually keep costs down and reduce complexity.

There are also stringent privacy and regulatory expectations that can impact pharma trials’ priorities.

Still, if they can be merged with existing systems, automated workflows eliminate repetitive, and manually intensive processes.

This simplifies data gathering and analysis, improves communications and productivity levels, and facilitates accurate tracking and reporting on process steps and completion dates.

In order to achieve these benefits, pharma companies will need to break through some of the above barriers sooner than later!

Team members in a meeting using advanced technology.

Here Are 4 Ways Technology Can Optimize Clinical Trial Workflows

Trials generate enormous amounts of data. This information is key to identifying operational bottlenecks and generating insights into how current processes could improve.

But to make use of it, pharma companies need to be able to see it, analyze it and put it into action.

Despite the emergence of digital technology in pharma, many companies still lean heavily on paper documentation or traditional tools such as manually created spreadsheets to manage information and patient records.

There are plenty of problems with this traditional approach, including:

  • Not fast enough.
  • It’s historical. (i.e. you can only use it to examine data from the past, or that has already been recorded and stored)
  • It’s prone to user error, inaccuracies, and data loss.
  • It’s harder to share with all stakeholders – you’ll need to configure access to online databases, ensure version control, or deal with paper copies. (none of which are ideal)

Software that can automate record-keeping processes and keep track of systematic workflows doesn’t just save time short term but they also make it easier to make good business decisions that affect the entire pharma life cycle.

To be more specific, here are 4 areas in which it’s possible to use digital emerging technology to cut costs, reduce information solos, and take advantage of automation to make clinical trial workflows more effective.

Device for reaching out to physicians for pharma sales reps.

1. Systematizing Trial Startup and Site Selection

Site selection and study startup are among the slowest and least efficient phases of clinical trial management.

Country selection, site selection, budgeting and contracting, regulatory constraints, and finding enrolling participants all take significant effort and time.

Automation can support study startup planning by outlining systematic tasks in order of urgency. Workflows can be designed based on country-specific regulations as well as individual sites, roles, and activities.

Technology can also be used to recruit patients. For example, one study found that a workflow could be designed to flag potentially eligible patients from routine health information system data in a hospital setting.

To name a few more examples:

  • Process automation can create an automatically updated virtual calendar where upcoming documentation needs to streamline trial startup procedures.
  • Databases can help automatically identify investigators with previous sponsor relationships and identify whether additional documentation of finances, licensing, and other disclosures are up-to-date.
  • Analytics and CTMS platforms can also assemble and visualize data from multiple sites at once, providing organizers and sponsors with accurate, real-time information on site performance.

A study found that inefficiencies often arise from the difficulty of measuring and predicting site performance early on during a trial, software that can identify low-performing sites can also help prioritize investigator time.

Allowing investigators to shut down unproductive sites early, or recommend monitors to visit high-risk sites over others, could save hundreds of thousands of dollars in wasted time and energy.

Physician going through data for making decisions.

2. Reducing Repetitive Tasks and Eliminating Bottlenecks

Clinical trials involve lots of workers, many of whom are highly-skilled, MD or Ph.D. – level researchers. Their time is expensive, and when it is primarily spent conducting the same tasks repeatedly, it ends up being wasted.

Common tasks of theirs include creating contracts, processing adverse event notifications and follow-ups, recording patient information, or drafting protocols.

Clinical trial site staff and investigators also often spend significant time inputting data into CRO systems with vastly differing systems for reporting AEs/SAEs and other data.

Although not all of these tasks can be automated, many of them can.

One immediate benefit of optimizing workflows with technology is through standardizing digital tasks, and automating some of the data captures. For example, scheduling patient repeat visits automatically or automatically populating patient data into the online record.

Workflow automation can also generate standardized contracts drafts to replace having to manually rewrite them for each trial. Other tools can compare patient records with previous entries to identify missing data points and potential errors in real-time.

While there’s an initial hurdle to get over when it comes to implementing a solution to do this, automating these tasks saves both effort and cost. When done well, they also reduce compliance errors and eliminate unnecessary delays.

Team of sales reps in a meeting using advanced analytics.

3. Improving Visibility and Business Decision-Making

Clinical trials are, first and foremost, designed to produce information.

To support this goal cost-effectively, all operational processes must be designed for optimal workflow and efficiency, so that:

  • Trials proceed on schedule.
  • All staff roles are defined and well-understood.
  • Important projects and tasks don’t get forgotten.
  • Resources are prioritized effectively and directed at the correct tasks.
  • Process inefficiencies are identified and eliminated.
  • Bottlenecks are removed.

In order for sponsors to achieve these goals, managers need tools to see how trials are progressing and analyze this information in real-time.

Armed with good information, they can address problems as soon as they emerge and allocate limited resources effectively. This requires deep analysis of performance across multiple areas and roles in a trial, from regulatory compliance to site selection, patient recruitment, and daily data collection activities.

Unlike previous traditional tools, which only facilitate analysis after-the-fact, pharma analytics software allows forecasting and immediate visibility of all trial processes. A single workflow program can accomplish this goal.

For example, by segregating and analyzing raw data under a single platform, our pharma data analytics solution lays out everything in a clear and concise way to allow your team to more efficiently do their job.

Using a technological tool to align your daily work with the most important objectives in the study leads ultimately to more efficient work, better enrollment, higher retention, and higher compliance rates – and in the end, that results in faster and more cost-efficient clinical trials.

Artificial Intelligence being used for actual business insight.

4. Regulatory Compliance & Study Validity

Approximately 35% of clinical research costs are spent on compliance.

Meeting regulatory constraints on the first try, rather than after trial and error, significantly lowers this cost and can shorten a trial’s timeline.

Data-driven strategies using analytics and other tools can help improve quality outcomes by eliminating compliance issues.

Data standardization – created through designing effective workflows – is also key to ensuring the reliability of the overall trial, particularly when trials go global.

You are much better off in a Medicare or financial audit when you design workflows that collect data along the way and then organize that data logically whenever the workflow is finished.

When paperwork gets lost or forgotten on someone’s desk, or there are errors in recording it, audit inspections can be delayed, leading to further headaches.

In contrast, when your data are organized and reported within a single software-based source, the auditing process is faster and far less painful for all involved. An advanced pharma CTMS software solution will keep track of anything from financial records through consent from the documentation.

Physician using tablet device.

Automation Removes Bottlenecks and Streamlines Workflows

The potential of digitizing and automating common pharma tasks is still in its infancy.

Pharma companies are often reluctant to change processes, given the challenges of adopting new technology to old regulations and strict compliance guidelines.

Still, in order to compete and counteract the skyrocketing price of developing new medications, reducing inefficiency and looking for ways to streamline clinical trial operations is unavoidable.

With the tools already out there, it’s already possible to:

  • No longer enter data and assign tasks associated with running a clinical trial manually or traditionally.
  • Identify and reduce the current bottlenecks relevant to your organization.
  • Create standardized workflows designed to make start-ups easier, eliminate delays, and implement study protocols faster.
  • Identify cost- and time-saving opportunities.
  • Improve visibility and streamline collaboration between team members.
  • Keep data gathering auditable and compliant with current regulations.

Also, if you’d like to learn more about our CTMS solution or our analytics and data management solution, contact us below for free!

4 Challenges With Managing Clinical Trials & How Technology Can Help

The skyrocketing costs of clinical research are likely the first issue that comes to mind when it comes to barriers to pharma companies’ R&D efforts.

In 2014, the Tufts Center for the Study of Drug Development found that clinical testing costs as much as $2.6 billion per drug; the cost of drug development has increased by 400% in less than two decades.

However, ongoing research challenges are affecting far more than pharma companies’ bottom lines. To name just one high-profile example:

Pfizer recently realized that patients taking one of their arthritis drugs might have reduced risk of developing Alzheimer’s. While that seems like positive news, the company ultimately opted out of testing the correlation. This was due to the risks, difficulties, and cost of R&D not being worth the potential upside.

This case reveals a growing reality within the pharma industry – clinical trials are an essential step towards bringing new drugs to market and driving value, but they are facing increasingly pressing challenges, not only including costs but also:

  • Time: Also, the average testing process takes up to 14 years, so drugs may have only a couple of years on the market before they face generic competition.
  • Complexity: Increasing trial complexity influence both the cost and quality of the research. Testing drugs sometimes requires hundreds of sites, complex protocols, and the involvement of hundreds of highly qualified professionals.
  • Risk Management: Standardizing clinical trial processes to comply with regulations requires extensive planning and IT sophistication.

In situations like the one, Pfizer faced, everyone loses – the patients, who miss out on potentially life-saving treatments, the insurers, who have to pay more for drugs that cost more to produce, and the pharma companies, who have shrinking windows for patented drugs and who face R&D costs spiraling out of control.

Unpacking the specific barriers facing clinical trials – and how to overcome them using the most innovative solutions available – is key to meeting efficiency goals and continue to add value.

4 Challenges With Managing Clinical Trials & How Technology Can Help

Top Challenges Affecting Clinical Trials & How to Solve Them With Pharma Technology

1. Regulatory Barriers and Approval Delays

Given how tightly regulated the pharma industry is, meeting compliance obligations is unsurprisingly among the top challenges getting in the way of timely and cost-effective clinical trial completion.

Especially as trials move globally, they become increasingly constrained by their own complexity. The need to coordinate between multiple sites, partners, and vendors are becoming exceedingly challenging.

In a survey including pharma executives by ICON and pharma intelligence, 43 percent of respondents named regulatory approval delays as the most common challenge.

Even steps as fundamental as version control on consent form documentation can turn into major deviations from protocol – a regulatory disaster – if data isn’t correctly stored and organized.

In fact, more than one-third of clinical research spending goes to keeping trials compliant.

Organizing information using a CTMS software keeps track of all information from the beginning, standardizing your record-keeping and who is authorized to do what, and when.

Analytics tools not only keep you protected in an audit but also make delays less likely, as well as streamlining the entire approval process.

An effective CTMS software will keep track of anything from Sunshine Act reporting through consent form documentation, and make it easier to define investigator and support staff roles at a site-level.

These tools also centralize site activation mechanisms, making it possible to instantly share important records with stakeholders.

Once a trial is underway, record-keeping systems also help keep track of scheduled dates for ethics/IRB submissions and approvals, helping to keep study timelines on track.

Clinical trails

2. Site Selection & Recruitment

About 2 million patients participate in clinical trials every year, but to meet U.S. recruitment goals, 6 million patients would be needed. This reality causes delays or budget issues in as many as 90% of trials.

Recruiting and retaining enough participants to complete a trial is among the biggest sources of delays and trial failures.

Site selection is a critical first step to patient recruitment, and some of the most important parameters for site selection are patient access, infrastructure, and suitability for the given treatment type.

However, according to research done at Tufts, the number of PIs available to conduct research has consistently declined over the past several years.

This makes it more challenging – and more important – that pharma companies have the tools to identify available investigators who have the highest enrollment potential.

Artificial Intelligence or AI can draw operational data from previous trials to predict site performance in the future. Eventually, it may even be able to predict retention, trial success, and whether a drug will result in positive outcomes.

Today, however, using the right software makes it possible to re-use information from a site across multiple trials, reducing the time it takes to select and then initiate a site.

When the same patient population becomes known, these tools can also support increased engagement and better relationships over time.

Clinical Trials

3. Clinical Trial Site Management

Clinical trials have been growing increasingly complex for years.

As the complexity, geographic diversity, and rate of change in trials increases, it becomes more difficult to make decisions and identify potential issues in real-time.

Roles and responsibilities among staff members evolve quickly, and lack of visibility into data, as well as dealing with disparate data sources, makes it touch to respond quickly.

About two-thirds of clinical trial coordinators say they use manually compiled spreadsheets to make business decisions.

This leads to slower problem resolution and an inability to identify underperforming sites (leads to more delays).

Using a CTMS, you can easily generate reports on study progress, financial metrics, staff hours, enrollment goals, protocol deviations, and adverse events.

This software enables centralized monitoring, real-time reporting, rather than shuffling papers and trying to compare sites after the fact or in cumbersome ways.

Clinical Trials

4. Data Management

When trials are underway, ensuring that sites are well-monitored, and data is being accurately captured, is one of the most important priorities of trial management.

Ensuring patient perseverance and completion of the clinical trial protocol requires active data analysis and monitoring to track compliance, including monitoring of endpoint data, deviations, and any adverse events.

Doing this manually, as many pharma companies still are, leads to difficulty updating information quickly and aggregating data from multiple sources and across different systems platforms.

Lab results, imaging, and health records are difficult to integrate quickly, especially with site directors relying on manual spreadsheet methods.

Software for clinical data management has the advantage of instantly centralizing the information, making it accessible by key personnel quickly.

The right solution can integrate across disparate data sources in near real-time, enabling proactive response to SAEs/AEs and seamless monitoring of protocol compliance.

Data managers can also automate result reporting, making it easy to look for trends in patient responses sooner.

clinical trials

Traditional Methods of Clinical Trial Management Aren’t Working Anymore

In the past, clinical trial activities such as…

  • Patient Recruitment
  • Site Selection
  • Intervention Delivery
  • Compliance and Record-keeping
  • Data Collection
  • Etc.

…were all completed using paper-based, traditional methods.

Even though online tools have been available for record-keeping for over two decades, clinical trials have been slow to adopt them.

Today, less than 10 percent of clinical research professionals report having access to the software tools that enable automation of these initiatives.

This should be too much of a surprise given the long lifecycle of drug development being eclipsed by the evolution of digital tech and that pharma is such a regulated industry.

However, given how pressing the challenges currently facing clinical trial management are becoming, using modern tech solutions is the best – and possibly the only productive way to improve diverse areas of research, such as:

  • Overall study quality and validation
  • Risk-management protocol and risk-based monitoring
  • Centralizing of study data and monitoring
  • Site selection and management
  • Site Selection
  • Patient Recruitment and retention
  • CRO oversight
  • Time management

Tools like Artificial Intelligence, Data Analytics, and CTMS software all reduce the risk of extra cost and delays. Data analysis enabled by these technologies can also reduce overall expenditures and improve the efficiency of future studies.

Clinical trials require a balancing act of speed and delivery against the quality of data and processes to deliver the safest product. Often, the right software makes the difference in this balancing act.

If you’re interested in our CTMS solution for your clinical trials, contact us below for free and let’s chat about it!

Solutions For Improving Data Quality & Avoiding Delays From a Clinical Trial Site Manager

Laptop with clinical trials data

In all clinical trials, one of my ultimate goals is to obtain accurate, clean data as quickly and efficiently as possible – all while minimizing overall trial costs.  Although the trial data results are the end goal, I never want to sacrifice subject safety to get it. 

Subject safety is the reason we follow the International Conference on Harmonization (ICH) and Good Clinical Practice (GCP).  Institutional Review Boards (IRBs) are in place as a means of ensuring we follow ICH/GCP throughout the life of a clinical trial. 

To remove bias, third-party vendors monitor and verify clinical trial data.  It is this vendor, often a Clinical Research Organization (CRO), that is responsible for sending out Site Managers (SMs) to perform monitoring visits at all sites chosen to participate in the trial.  During these visits, SMs review source data for accuracy and completeness. 

SMs ensure that site staff have been compliant with the protocol, verify Principal Investigator trial oversight, perform drug accountability, verify documented site training and can work with the site staff to reconcile any discrepancies noted.  At the completion of a visit, the SM leaves the site as ‘audit-ready’ as possible.

As SMs have many responsibilities, it is easy to see that there are many ways in which trial data delays can occur.  As a former Lead SM and now a Clinical Operations Lead, I have learned that one of the most basic ways to lose time in a clinical trial is by having the monitoring visits occur out of the scheduling window. 

What is the Problem?

We can only rely on clinical trial data entered after a SM has verified it.  Therefore, it is crucial to have monitoring visits occur according to the timing schedule found in the Clinical Monitoring Plan (CMP) / Clinical Operations Plan (COP).  When these visits do not occur within the scheduling window of the CMP/COP, it leads to untimely source document verification (SDV). 

Untimely monitoring visits can create a multitude of problems during clinical trials.  In my experience, a delay in SDV has a negative chain effect.  Other clinical departments (i.e. Safety, etc.) are unable to perform their review until after the SM has performed SDV.

This prolongs the time it takes for overall trial data reconciliation.  The Data Management department may also spend an endless amount of time querying unverified/unclean data unnecessarily.  This is not just a poor use of time but can be a very costly endeavor for pharmaceutical/sponsor companies. 

During the SDV process, SMs often find unreported Adverse Events (AEs) and/or Serious Adverse Events (SAEs).  SAEs require reporting to the sponsor company and the IRB within specific timeframes.  As mentioned earlier, subject safety is my highest priority during any clinical trial. 

Therefore, prompt assessment and documentation of AEs and SAEs is a must.  If monitoring visits are not occurring according to the CMP/COP, I cannot ensure this.  Any delay in SDV can also lead to protocol deviations going unnoticed and possibly repeated for subsequent subjects at multiple subject visits. 

What is the Remedy?

In our very technologically savvy world, there is any number of calendar date generating applications and websites one can choose.  I have used the following website when I do not want to be relegated to the use of a ‘date wheel’:  https://timeanddate.com.

There is even an associated phone application for iOS called ‘Time & Date Calculator’.  Both the website and phone app require me to enter the date of the initial visit and then the number of weeks/days/months required in the interval.

Once I enter that information it will calculate when the next visit should occur.  If I need to create something more tangible for my SM team, I input a trial-specific formula into an Excel spreadsheet. 

This enables anyone on the clinical study team to generate the same information as the above-mentioned website, which is helpful when SMs need to forecast future monitoring visits. 

Whichever method is chosen, I know that I am creating a check and balance system that can minimize the timing of trial data available for further analyses.  CROs can use these measures to ensure that their employees are following the CMP/COP and to hold trial sites to their contractually agreed upon availability. 

Likewise, pharmaceutical/sponsor companies can use these methods to verify that a CRO is adhering to their contractual obligations for overall trial monitoring.  Most importantly, though, by finding a method that works best – it will aid in getting clean trial data submitted in a timely fashion.

If you would like to learn about our Clinical Trial Management System tool and how our solution can help solve problems such as this one, click below!