The Cost of a Failed Clinical Data Strategy and How to Avoid It

clinical data analysisDrug and device development is a grueling process with long timelines and excruciating costs. Throughout the trial process, Sponsors often face obstacles that delay timelines and inevitably increase costs. Even more frustrating, the odds of success are stacked against Sponsors – approximately 90% of drugs that reach clinical development never make it to regulatory approval and marketization.

Drug and device trials can fall of track for many scientific reasons, however many Sponsors associate trial delays with slow patient recruitment (more than 80% of trials fail to enroll on time). But, many studies go haywire for reasons that Sponsors can control with better planning and due diligence when it comes to choosing the right vendors. When problems arise, Sponsors often look to different vendors in an effort to “rescue the study”.

Sponsors often face these common challenges in data collection and reporting that lead to costly delays including:

  • Poor trial design and inconsistent with endpoints
  • Inconsistencies in trial data and failure to detect erroneous or fraudulent data
  • Failure to understand regulatory requirements and feedback
  • Dispersed data that can lead to inaccurate analyses or poor data quality
  • Vendor problems with staff and project team turnover

While a “rescue study” might be necessary to save a Sponsor’s clinical program, these studies pile on thousands or even millions of dollars of additional costs for the Sponsor. According to a market study by IMS Health, a single sponsor running 100 clinical trials a year spends $26 million annually to “overcome avoidable protocol design flaws and patient recruitment difficulties”. Even scaling that figure for smaller pharma and biotech companies results in inexcusable costs and can be avoided. Sponsors considering a rescue study have to account for tasks such as new database build, data migration and import, new CRF/eCRF design, new SOPs and of course a new project team.

How can Sponsors plan effectively in the trial design and clinical data strategy phase?

1. Invest in data quality from the beginning

Many Sponsors fail to define a global clinical data strategy from the onset which includes plans for the entire phase of development and post-market. Clinical data is a Sponsor’s greatest asset, and therefore they should invest in a clinical data team with the proper experience and know-how for efficient database build and management as well as query management.

2. Involve a biostatistician from the beginning and keep a consultant statistician on your team throughout the development cycle

The best time to involve a biostatistician in a trial is from the very beginning in order to understand the study design and make suggestions on hypothesis testing and analysis. The statistician plays a vital role in protocol development and design, data management, monitoring and reporting. Keeping a consultant statistician on your team throughout the study will help alleviate problems that arise with trial design and data analysis as well as reporting to regulatory feedback. Statisticians can apply trial design methods – such as adaptive trial design – that can make significant changes in the study that reduce timelines including early study termination if necessary. Most importantly, statisticians can support in DSMB and regulatory meetings and help make sense of clinical data.

3. Centralizing clinical data with a specialized vendor

When data is dispersed across vendors, Sponsors often face problems with data traceability, cross-product analysis, query management and data inaccuracies. Centralizing clinical data services – including biostatistics, data management and medical writing – saves time by creating a global library of databases, shorter learning curves between CRO and Sponsor and easy access to study metrics. Quality is greatly improved through standardization, familiarity with customer processes, formats and templates and communication.

4. Strategic Functional Service Model to address staff augmentation and turnover

The FSP model faciliates a scalable, expert team of resources for a particular function and results in improved quality, eradication of change orders, reduced training and greater efficiency. Using FSP, Sponsors can save on recruitment fees, training costs, and HR management time. The CRO is responsible for producing the required resources and ensuring continuity of trained resources. In this case, the Sponsor can be guaranteed that they will have the same resources dedicated to a project that understand both the CROs requirements and the Sponsor’s requirements.

5. Risk-Based Metrics from data experts to enable Risk-Based Monitoring

Risk-Based Monitoring combines on-site monitoring along with centralized remote monitoring by coordinating centers. Based on risk assessments about how the clinical information is captured and protocol designed, risk-based monitoring activities can be proactively supported by the usage of reporting tools. One important component of RBM is the metrics that enable source data verification and triggering alerts when sites have inconsistent data patterns of problems. Centralizing your data with a specialized team of data managers and statisticians allows for accurate and timely metrics about site performance.

Take our Survey “Addressing Clinical Data Strategy”

survey-button

The Cost of a Failed Clinical Data Strategy and How to Avoid It

clinical data analysisDrug and device development is a grueling process with long timelines and excruciating costs. Throughout the trial process, Sponsors often face obstacles that delay timelines and inevitably increase costs. Even more frustrating, the odds of success are stacked against Sponsors – approximately 90% of drugs that reach clinical development never make it to regulatory approval and marketization.

Drug and device trials can fall of track for many scientific reasons, however many Sponsors associate trial delays with slow patient recruitment (more than 80% of trials fail to enroll on time). But, many studies go haywire for reasons that Sponsors can control with better planning and due diligence when it comes to choosing the right vendors. When problems arise, Sponsors often look to different vendors in an effort to “rescue the study”.

Sponsors often face these common challenges in data collection and reporting that lead to costly delays including:

  • Poor trial design and inconsistent with endpoints
  • Inconsistencies in trial data and failure to detect erroneous or fraudulent data
  • Failure to understand regulatory requirements and feedback
  • Dispersed data that can lead to inaccurate analyses or poor data quality
  • Vendor problems with staff and project team turnover

While a “rescue study” might be necessary to save a Sponsor’s clinical program, these studies pile on thousands or even millions of dollars of additional costs for the Sponsor. According to a market study by IMS Health, a single sponsor running 100 clinical trials a year spends $26 million annually to “overcome avoidable protocol design flaws and patient recruitment difficulties”. Even scaling that figure for smaller pharma and biotech companies results in inexcusable costs and can be avoided. Sponsors considering a rescue study have to account for tasks such as new database build, data migration and import, new CRF/eCRF design, new SOPs and of course a new project team.

How can Sponsors plan effectively in the trial design and clinical data strategy phase?

1. Invest in data quality from the beginning

Many Sponsors fail to define a global clinical data strategy from the onset which includes plans for the entire phase of development and post-market. Clinical data is a Sponsor’s greatest asset, and therefore they should invest in a clinical data team with the proper experience and know-how for efficient database build and management as well as query management.

2. Involve a biostatistician from the beginning and keep a consultant statistician on your team throughout the development cycle

The best time to involve a biostatistician in a trial is from the very beginning in order to understand the study design and make suggestions on hypothesis testing and analysis. The statistician plays a vital role in protocol development and design, data management, monitoring and reporting. Keeping a consultant statistician on your team throughout the study will help alleviate problems that arise with trial design and data analysis as well as reporting to regulatory feedback. Statisticians can apply trial design methods – such as adaptive trial design – that can make significant changes in the study that reduce timelines including early study termination if necessary. Most importantly, statisticians can support in DSMB and regulatory meetings and help make sense of clinical data.

3. Centralizing clinical data with a specialized vendor

When data is dispersed across vendors, Sponsors often face problems with data traceability, cross-product analysis, query management and data inaccuracies. Centralizing clinical data services – including biostatistics, data management and medical writing – saves time by creating a global library of databases, shorter learning curves between CRO and Sponsor and easy access to study metrics. Quality is greatly improved through standardization, familiarity with customer processes, formats and templates and communication.

4. Strategic Functional Service Model to address staff augmentation and turnover

The FSP model faciliates a scalable, expert team of resources for a particular function and results in improved quality, eradication of change orders, reduced training and greater efficiency. Using FSP, Sponsors can save on recruitment fees, training costs, and HR management time. The CRO is responsible for producing the required resources and ensuring continuity of trained resources. In this case, the Sponsor can be guaranteed that they will have the same resources dedicated to a project that understand both the CROs requirements and the Sponsor’s requirements.

5. Risk-Based Metrics from data experts to enable Risk-Based Monitoring

Risk-Based Monitoring combines on-site monitoring along with centralized remote monitoring by coordinating centers. Based on risk assessments about how the clinical information is captured and protocol designed, risk-based monitoring activities can be proactively supported by the usage of reporting tools. One important component of RBM is the metrics that enable source data verification and triggering alerts when sites have inconsistent data patterns of problems. Centralizing your data with a specialized team of data managers and statisticians allows for accurate and timely metrics about site performance.

Take our Survey “Addressing Clinical Data Strategy”

survey-button

The Cost of a Failed Clinical Data Strategy and How to Avoid It

clinical data analysisDrug and device development is a grueling process with long timelines and excruciating costs. Throughout the trial process, Sponsors often face obstacles that delay timelines and inevitably increase costs. Even more frustrating, the odds of success are stacked against Sponsors – approximately 90% of drugs that reach clinical development never make it to regulatory approval and marketization.

Drug and device trials can fall of track for many scientific reasons, however many Sponsors associate trial delays with slow patient recruitment (more than 80% of trials fail to enroll on time). But, many studies go haywire for reasons that Sponsors can control with better planning and due diligence when it comes to choosing the right vendors. When problems arise, Sponsors often look to different vendors in an effort to “rescue the study”.

Sponsors often face these common challenges in data collection and reporting that lead to costly delays including:

  • Poor trial design and inconsistent with endpoints
  • Inconsistencies in trial data and failure to detect erroneous or fraudulent data
  • Failure to understand regulatory requirements and feedback
  • Dispersed data that can lead to inaccurate analyses or poor data quality
  • Vendor problems with staff and project team turnover

While a “rescue study” might be necessary to save a Sponsor’s clinical program, these studies pile on thousands or even millions of dollars of additional costs for the Sponsor. According to a market study by IMS Health, a single sponsor running 100 clinical trials a year spends $26 million annually to “overcome avoidable protocol design flaws and patient recruitment difficulties”. Even scaling that figure for smaller pharma and biotech companies results in inexcusable costs and can be avoided. Sponsors considering a rescue study have to account for tasks such as new database build, data migration and import, new CRF/eCRF design, new SOPs and of course a new project team.

How can Sponsors plan effectively in the trial design and clinical data strategy phase?

1. Invest in data quality from the beginning

Many Sponsors fail to define a global clinical data strategy from the onset which includes plans for the entire phase of development and post-market. Clinical data is a Sponsor’s greatest asset, and therefore they should invest in a clinical data team with the proper experience and know-how for efficient database build and management as well as query management.

2. Involve a biostatistician from the beginning and keep a consultant statistician on your team throughout the development cycle

The best time to involve a biostatistician in a trial is from the very beginning in order to understand the study design and make suggestions on hypothesis testing and analysis. The statistician plays a vital role in protocol development and design, data management, monitoring and reporting. Keeping a consultant statistician on your team throughout the study will help alleviate problems that arise with trial design and data analysis as well as reporting to regulatory feedback. Statisticians can apply trial design methods – such as adaptive trial design – that can make significant changes in the study that reduce timelines including early study termination if necessary. Most importantly, statisticians can support in DSMB and regulatory meetings and help make sense of clinical data.

3. Centralizing clinical data with a specialized vendor

When data is dispersed across vendors, Sponsors often face problems with data traceability, cross-product analysis, query management and data inaccuracies. Centralizing clinical data services – including biostatistics, data management and medical writing – saves time by creating a global library of databases, shorter learning curves between CRO and Sponsor and easy access to study metrics. Quality is greatly improved through standardization, familiarity with customer processes, formats and templates and communication.

4. Strategic Functional Service Model to address staff augmentation and turnover

The FSP model faciliates a scalable, expert team of resources for a particular function and results in improved quality, eradication of change orders, reduced training and greater efficiency. Using FSP, Sponsors can save on recruitment fees, training costs, and HR management time. The CRO is responsible for producing the required resources and ensuring continuity of trained resources. In this case, the Sponsor can be guaranteed that they will have the same resources dedicated to a project that understand both the CROs requirements and the Sponsor’s requirements.

5. Risk-Based Metrics from data experts to enable Risk-Based Monitoring

Risk-Based Monitoring combines on-site monitoring along with centralized remote monitoring by coordinating centers. Based on risk assessments about how the clinical information is captured and protocol designed, risk-based monitoring activities can be proactively supported by the usage of reporting tools. One important component of RBM is the metrics that enable source data verification and triggering alerts when sites have inconsistent data patterns of problems. Centralizing your data with a specialized team of data managers and statisticians allows for accurate and timely metrics about site performance.

Take our Survey “Addressing Clinical Data Strategy”

survey-button

The Cost of a Failed Clinical Data Strategy and How to Avoid It

clinical data analysisDrug and device development is a grueling process with long timelines and excruciating costs. Throughout the trial process, Sponsors often face obstacles that delay timelines and inevitably increase costs. Even more frustrating, the odds of success are stacked against Sponsors – approximately 90% of drugs that reach clinical development never make it to regulatory approval and marketization.

Drug and device trials can fall of track for many scientific reasons, however many Sponsors associate trial delays with slow patient recruitment (more than 80% of trials fail to enroll on time). But, many studies go haywire for reasons that Sponsors can control with better planning and due diligence when it comes to choosing the right vendors. When problems arise, Sponsors often look to different vendors in an effort to “rescue the study”.

Sponsors often face these common challenges in data collection and reporting that lead to costly delays including:

  • Poor trial design and inconsistent with endpoints
  • Inconsistencies in trial data and failure to detect erroneous or fraudulent data
  • Failure to understand regulatory requirements and feedback
  • Dispersed data that can lead to inaccurate analyses or poor data quality
  • Vendor problems with staff and project team turnover

While a “rescue study” might be necessary to save a Sponsor’s clinical program, these studies pile on thousands or even millions of dollars of additional costs for the Sponsor. According to a market study by IMS Health, a single sponsor running 100 clinical trials a year spends $26 million annually to “overcome avoidable protocol design flaws and patient recruitment difficulties”. Even scaling that figure for smaller pharma and biotech companies results in inexcusable costs and can be avoided. Sponsors considering a rescue study have to account for tasks such as new database build, data migration and import, new CRF/eCRF design, new SOPs and of course a new project team.

How can Sponsors plan effectively in the trial design and clinical data strategy phase?

1. Invest in data quality from the beginning

Many Sponsors fail to define a global clinical data strategy from the onset which includes plans for the entire phase of development and post-market. Clinical data is a Sponsor’s greatest asset, and therefore they should invest in a clinical data team with the proper experience and know-how for efficient database build and management as well as query management.

2. Involve a biostatistician from the beginning and keep a consultant statistician on your team throughout the development cycle

The best time to involve a biostatistician in a trial is from the very beginning in order to understand the study design and make suggestions on hypothesis testing and analysis. The statistician plays a vital role in protocol development and design, data management, monitoring and reporting. Keeping a consultant statistician on your team throughout the study will help alleviate problems that arise with trial design and data analysis as well as reporting to regulatory feedback. Statisticians can apply trial design methods – such as adaptive trial design – that can make significant changes in the study that reduce timelines including early study termination if necessary. Most importantly, statisticians can support in DSMB and regulatory meetings and help make sense of clinical data.

3. Centralizing clinical data with a specialized vendor

When data is dispersed across vendors, Sponsors often face problems with data traceability, cross-product analysis, query management and data inaccuracies. Centralizing clinical data services – including biostatistics, data management and medical writing – saves time by creating a global library of databases, shorter learning curves between CRO and Sponsor and easy access to study metrics. Quality is greatly improved through standardization, familiarity with customer processes, formats and templates and communication.

4. Strategic Functional Service Model to address staff augmentation and turnover

The FSP model faciliates a scalable, expert team of resources for a particular function and results in improved quality, eradication of change orders, reduced training and greater efficiency. Using FSP, Sponsors can save on recruitment fees, training costs, and HR management time. The CRO is responsible for producing the required resources and ensuring continuity of trained resources. In this case, the Sponsor can be guaranteed that they will have the same resources dedicated to a project that understand both the CROs requirements and the Sponsor’s requirements.

5. Risk-Based Metrics from data experts to enable Risk-Based Monitoring

Risk-Based Monitoring combines on-site monitoring along with centralized remote monitoring by coordinating centers. Based on risk assessments about how the clinical information is captured and protocol designed, risk-based monitoring activities can be proactively supported by the usage of reporting tools. One important component of RBM is the metrics that enable source data verification and triggering alerts when sites have inconsistent data patterns of problems. Centralizing your data with a specialized team of data managers and statisticians allows for accurate and timely metrics about site performance.

Take our Survey “Addressing Clinical Data Strategy”

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