臨床試験ソフトウェアがどのように研究の効率化に役立つか

Research organizations are faced with the pressures of study deadlines and a need to stay compliant with regulatory standards. Often, they run multiple clinical trials simultaneously. They’ve got to be efficient.

They need to be able to see and manage their clinical trials effectively so they can identify process inefficiencies. They need full transparency of the process from start to finish so they can report on this come submission time. And most importantly, they need to collect the required data quickly and accurately.

This is why more and more organizations are engaging the help of clinical trial software companies offering cloud-based solutions. Many types of clinical trial software are used by clinical research organizations (CROs), biotechnology, and pharmaceutical companies to facilitate clinical trials from conception to submission. This specialized software can help you run clinical trials more efficiently and help you to get clinical products to the market faster.

• Protocol management
• CRF design
• Metadata management
• Collection and analysis of data
• Data validation and conformance
• Data exchange (the standardization of vendor collected data)
• Submission of compliant clinical study data to regulatory authorities

The pharmaceutical industry has been slow to try new approaches and emerging software solutions. They’ve been focused on getting clinical products to market, despite process inefficiencies.

Traditionally, spreadsheets have been used to record and manage the various aspects of clinical trials, including data collection, study protocol and specifications. But these traditional ‘manual’ solutions carry a considerable risk of errors, incomplete data collection, and process bottlenecks. As a result, efficiency, compliance, and patient care are often compromised.

The industry now recognizes that to stay ahead of competitors and overcome tight timescales, cloud-based clinical trial software solutions are key for faster, more efficient clinical trials. The FDA encourages the use of cloud-based solutions to streamline the clinical trial process.

There are many different types of software provided by clinical trial software companies, for different stages in the clinical trial process.

1. Clinical Trial Management systems (CTMS)

2. Electronic Data Capture systems (EDC)

3. Clinical Metadata Repositories (CMDR)

4. Clinical Data Management systems (CDMS)

Below, we explore these solutions in more detail.

A clinical trial management system is an integrated cloud-based software platform that’s used for the end-to-end management of clinical trials.

A clinical trial management system is used to:

• Plan, track, and analyze clinical trials
• Find and manage participating patients
• Track participants’ involvement in clinical trials
• Manage finances

This type of software can help you improve the quality of your clinical products, reduce the time it takes to get a product to market, and ensure compliance with industry standards and regulations.

Clinical trial management systems are often used in conjunction with other clinical trial software that specializes in a specific area, such as EDCs.

An EDC is an electronic system used to gather patient data during clinical trials. EDCs typically have a user interface for users to enter data into electronic forms. A validation function will check forms have been filled in accurately, and a reporting tool lets users analyze the data collected.

EDCs have been around since the 1990s and are improving all the time. Modern EDCs let you target specific patient profiles or study phases. Examples of modern features include cloud data storage, role-based permissions, CRF designers, clinical data analytics, interactive dashboards, and electronic health record integration.

A CMDR is a centralized location for you to store, manage and find all your study metadata, such as forms, standards and datasets, in one place. A bit like a library, or a single source of truth.

Metadata can be stored in various stages of development. It can be updated, approved, and kept as organizational standards. This gives you easy access to approved metadata you can reuse again and again. This means less time spent creating and approving metadata with every study.

Examples of standardized metadata include case report forms (CRFs), terminologies, datasets, and mappings.

The key drivers for using a clinical metadata repository are:

• 規制準拠
• High data quality
• Process efficiency
• Reuse
• Save time and resources
• Get to submission faster

And many of these benefits come as a direct result of automation.

Automated processes and clinical metadata repositories go hand in hand. You’ll find that if you implement a CMDR, you’ll also be able to automate traditionally manual processes.

A clinical metadata repository stores all your organizational standards in one place. This means your content is easily accessible and ready to use across all your studies. A good CMDR also enables auto-generation of study artifacts such as EDC, SDTM, and ADaM specifications.

Automation simplifies processes for clinical studies, from study setup through to submission. It helps to accelerate studies and to reduce human error by removing manual processes. It also makes it easier for companies to comply with regulatory standards because submissions can be easily built to a compliant specification and data quality will be high.

By using a CMDR or other clinical trial automation software, you’ll be able to:

• Get clinical trials done faster
• See improved data quality and consistency
• Analyze data more quickly and effectively
• Reduce overall costs of the study

The aim of a CDMS is to collect, clean and manage clinical trial data to ensure it aligns with regulatory standards. Using a CDMS, you can ensure that your data is complete, high-quality, and free of errors and inconsistencies. How does it work?

As with CMDRs, these benefits come as a direct result of automation.

A clinical data management system with automated data validation allows you to automatically compare your datasets against regulatory criteria and highlight any issues you’ll need to fix in advance. The right software can even let you validate as you go – so you won’t have to wait until all data is collected to identify problems. This gives you complete confidence that your data conforms with regulatory requirements before you submit.

• Validate against regulatory requirements – have confidence that your datasets conform before submitting to mitigate the risk of non-conformance. Look for platforms to help you comply with CDISC standards, controlled terminology, and resources like MedDRA and WHODrug.
• Make and track changes between validation rounds – with the right platform, you won’t need to wait for all data to be collected before validating. Instead, automatically validate, correct quality issues, and repeat while the study is ongoing.
• Ensure internal standards comply – along with regulatory standards, your data may need to comply with internal organizational standards. Use a data validation platform that accommodates custom standards and validates those against regulatory standards such as CDISC.
• No need for expert knowledge – a validation platform helps you easily identify issues and patterns in your data without the need for an in-depth understanding of how it all works.
• Stakeholder collaboration – Sponsors, partners, and vendors access one platform and single source of truth to collaborate and ensure data conformance.

Every research organization knows the pain of retrospectively standardizing data that’s been collected outside of an EDC system. In fact, over 70% of clinical data now originates from ‘external vendors.’

A comprehensive clinical data management system offers the ability to collect and standardize non-EDC data.

• Easily design and store study specifications in one place – a data exchange tool helps you create specifications stored in one central location, accessible by vendors, so you know they’re collecting data in alignment with your current spec.
• Leave behind spreadsheets and emails – with a capable data exchange platform, you’ll design and store your specs in one cloud-based platform, so you won’t need to keep spreadsheets up to date or have lengthy email conversations with vendors to ensure they’re collecting the data you need.
• Validate third-party data to ensure it meets your requirements – with the right platform, you’ll check collected data against your predefined specification to ensure it complies.