Srini Dagalur

	Managing clinical trials in today’s highly regulated and increasingly global life sciences marketplace can be extremely challenging. It requires an integrated, end-to-end approach that concurrently provides visibility into trial costs and regulatory risks and adheres to schedule. Yet, clinical trial management can be hampered by organizational boundaries, siloed information, disparate systems, and non-standardized processes, resulting in an unsettling case of “You don’t know what you don’t know.” It is important, therefore, that clinical operations executives at life sciences companies address clinical trial management issues proactively and thoroughly to enable successful product development.  

	For several years, increasing numbers of life sciences organizations have implemented a Clinical Trial Management System (CTMS) that can provide insights gleaned from the system’s data to gain early and increased visibility into problems, progress and possibilities. Many organizations have a constant need to expand CTMS capabilities, integrate clinical operations data across multiple systems, and update clinical trial processes – all in order to adapt to changing regulatory requirements and clinical trial practices. This is the dilemma facing clinical operations executives when selecting a CTMS solution to manage clinical trials – go with an existing approach/solution or explore alternative options.

	CTMS definition, challenges and benefits

	A typical CTMS defines and manages all of the activities that span the lengthy and rigorous clinical trial process (Figure 1).

	A CTMS can reassure clinical operations executives that “you know what you should know.” It transcends organizational boundaries, improves interoperability, and addresses evolving regulatory standards. It maintains and manages clinical trial planning, preparation, performance, and reporting, with an emphasis on keeping up-to-date contact information for trial participants and tracking deadlines and milestones (e.g., for securing regulatory approval, distributing drug supplies, or issuing progress reports). Typically, a CTMS provides data to a business intelligence (BI) system, which acts as a digital dashboard for clinical trial managers.
	
	A life sciences organization exploring the selection of a CTMS should anticipate the solution to provide the following core capabilities:

			Clinical program/project management - Enables oversight of related clinical trials per therapeutic area based on a set of specific clinical project activities (i.e., tracking actual vs. target). Includes the ability to track progress at specific trial and program levels.

			Trial and site planning - Facilitates investigator and site identification and recruitment, including key trial milestone tracking such as target site/enrollment metrics for each study country.

			Site and subject management - Provides tracking ability for site monitoring, subject enrollment relative to plan, and Case Report Form (CRF)/ Electronic Case Report Form (eCRF) completion status. Includes management of site visits/trip reports.

			Study management - Tracks key information such as CRF collection, Clinical Research Associate (CRA) monitoring frequency, protocol visit frequency, and adherence to protocol regiments. Includes support for study documentation and tracking tasks.

			Investigator management - Allows the trial sponsor to manage relationships with investigators, based on visibility into the status study data and related status with CROs and/or investigator sites. Also tracks approvals by Institutional Review Boards (IRB) and Independent Ethics Committees IEC(s).

			Study financials and investigator grants and payment management - Supports financial management including tracking study costs, reimbursing investigators, and paying claims related to study activities. Includes grant payment management and management of financial disclosure.

			Clinical supply management including supply tracking - Manages clinical supplies.

			Clinical trial performance and reporting - Provides reporting/dashboards to communicate trial performance against targets, as well as other operational reports.

	In addition, many current CTMS vendors are offering solutions with advanced capabilities for managing clinical trials that are beyond the scope of traditional CTMS solutions. Among these are:

			Protocol and study documentation management - Enables review/management and authoring of essential study documents. Also includes approval of clinical trial documentation and tracking its status throughout its lifecycle.

			CRF and eCRF development - Provides the ability to view and track the creation of CRF/eCRF forms including their status.

			Tracking electronic data capture (EDC) components and summary details - Tracks the status of data collected in these forms which, in turn, informs the tracking of key clinical trial milestones (e.g., Last Patient Visit (LPV).

			Financial system integration - Integrates SAP financial systems with pre-existing SAP workflows/business rules for payments, including invoicing approvals.

			Clinical supply management: storage and shipment - Extends clinical supply management to include oversight and management of clinical supply logistics for components such as inventory locations, lots, and shipment details.

			Clinical data archiving/warehousing and management - Provides enhanced data management and archiving for future reference

			Data analysis and query resolution - Supports the evaluation of trial-generated clinical data and resolution of any discrepancies or inconsistencies found in clinical data.

			Clinical learning and training - Integrates learning management to track and manage internal and external staff learning requirements relative to the clinical trial process.

	As with any evolving process or technology, implementing a CTMS could result in challenges, such as:

			Data access issues, as data resides in multiple locations or there may be gaps in data collection (i.e., trial process-specific data might not be captured)

			Lack of mature data management capabilities to store current and historical data to aid data analysis

			The inability to respond to potential protocol amendments in a timely manner

			Poor quality and reliability of clinical operations data due to significant lag times between data entry and reporting, and inconsistencies in reference data among various source systems feeding the CTMS.

	However, the benefits of using a CTMS can be substantial and outweigh such challenges. Potential benefits include:

			Improved clinical operations decision making resulting from more efficient trial planning/tracking milestones via executive management dashboards and metrics reporting

			Increased trial investigator selection rates and performance tracking management

			Help managing clinical trial costs/payments and clinical drug supplies tracking

			Enhanced relationship management across the clinical trial process (CRO, investigator and sponsor)

			Accurate financial reporting with enhanced ability to manage operations of individual studies and the entire set of clinical programs

			Improved data quality through the use of consistent vocabularies, including dictionaries, to avoid confusion and ambiguity of clinical trial data meaning.

	Life sciences companies have several options for implementing CTMS solutions:
	1) Implement an on-premises CTMS from a vendor (e.g., Medidata, Oracle);
	2) Enter into a Software-as-a-Service (SaaS) arrangement with a CTMS Vendor;
	3) Use a Contract Research Organization (CRO) owned- and managed-system; or
	4) Develop a bespoke CTMS solution (a standards-based, open architecture system with interoperable service-based integration with other systems).

	Currently, the CTMS market is fragmented and lacks comprehensive, vendor-supplied solutions. While options 1-3 already are being undertaken by various life sciences organizations, we are starting to see the emergence of option 4, bespoke CTMS solutions (e.g., Force.com from Salesforce; Allegro CTMS@Site) replacing entire CTMS traditional software or building a suite of solutions where traditional CTMS solutions don’t meet needs. In addition, we anticipate that the following trends will likely play a key role in an organization’s approach to CTMS selection:
	
	

 Life sciences organizations will need to understand new developments and approaches such as Adaptive Clinical Trial Design; the implications of managing/executing orphan drug trials; the impact of meeting emerging market needs resulting in global clinical trials; and expansion challenges across countries spanning different IRBs/ERBs.

Leveraging industry and technology innovations can aid a company’s decision-making when selecting a CTMS implementation approach. These innovations may include CDISC data/information models that have accounted for industry standardization of processes and nomenclature; new platforms (Force.com, Oracle PaaS) to develop CTMS capabilities that aim to keep trial operating costs low while driving more efficiency; and technology-specific enterprise solutions such as business intelligence suites (reporting and analytics), semantic applications, and collaboration/portal suites.

. Many organizations are using multiple CROs to manage clinical trials. This strategy calls for tighter collaboration among the trial sponsor and CROs and a comprehensive CTMS solution that can align clinical trial processes and integrate eClinical toolset components.

	When selecting a CTMS solution, life sciences companies should assess their current and future-state needs, review CTMS capabilities, trends, and challenges, consider the various CTMS solution options, and weigh potential benefits against their clinical operations objectives. Following a CTMS Assessment Framework (Figure 2) can aid the selection process.


	** : Bespoke Solutions based on extending CRM solutions OR Platform (PaaS)

	The myriad scientific, regulatory, and marketplace changes taking place in clinical trial management are creating a pressing need for innovative solutions that can span and integrate multiple, geographically dispersed trial partners and sites. While traditional software vendors provide CTMS capabilities via on-premises software and/or cloud-based Software as a Service (SaaS) solutions, the possibility of functional and information gaps can be a concern – especially in today’s dynamic life sciences environment. The emergence of PaaS provides an opportunity to reduce these gaps and build a set of CTMS capabilities on a robust, flexible platform that is custom-designed to meet a company’s current and future clinical trial management needs.

	
	
	Srini Dagalur, PhD, is a Specialist Leader, Life Sciences for Deloitte Consulting LLP. 

Articles

The dilemma facing clinical operations executives when selecting a CTMS solution to manage clinical trials is to go with an existing approach/solution or explore alternative options.

CTMS: What You Should Know

There have been significant changes in the way clinical trials are executed today—with a move towards eClinical where technology-based solutions are being widely used to drive automation and overall efficiency into the clinical trial end-to-end process. The majority of these current approaches are more siloed around systems such as CTMS, EDC/CDMS, IVR and submissions management (i.e., trial master file, CSR, etc.). There still exists certain phases such as study design and study build within the clinical trial process that can have a significant impact based on reduction in overall time for getting trials ready for study execution across the clinical sites. 

This article provides a framework called clinical trial design automation that helps establish a recommended approach to manage the study design and study build phase of the overall clinical trial process. The approach includes process and technology to aid in speeding up critical elements of a clinical trial lifecycle—elements covered are from study design (protocol design) to study build. This article highlights how this recommended approach will drive efficiencies by reducing overall timelines for building eCRF-based clinical trials including the drive towards reusing protocol elements and eCRF page elements using standards-based libraries. The conceptual architecture provided describes the components of the architecture and the process upon which this recommended approach for clinical trial design is founded on. Most of the components necessary for the proposed approach can be configured based on pre-existing solutions in the marketplace, while the core component termed clinical design interchange doesn't exist and will need to be designed and built. The use of industry data standards and CDISC-based messaging format for storing and communicating is proposed. The key mechanism in the proposed approach is the creation and maintenance of study components which are constantly being built in a clinical library resulting in reusable components that enables flexibility and adaptability to changing needs/regulatory requirements and support for global clinical trial execution. 

This recommended approach has significant value for key clinical trial stakeholders—sponsors, CROs, and eClinical vendors, each with the potential for driving efficiencies in the study design and study build phases of clinical trials resulting in the overall cost reduction of clinical trial execution while enabling flexibility to meet new regulations and clinical trial trends. 

Life science organizations are facing challenges with escalating costs emanating from increased operational complexities and ever-changing regulatory requirements within the United States and across the globe. In many cases, primary increases in costs for bringing products to market are around planning and execution of clinical trials. Further, the clinical trial market place is experiencing the following key trends as a result of increased cost of drug development, reduced probability of drug success, and failure to meet trial deadlines due to trial operational complexities. 					

Maturity of CRO's, emergence of boutique CROs, and other support organizations.

  complete drug development faster than the drug companies themselves, without sacrificing data quality. Boutique CROs are focusing on specific therapeutic areas and provide expertise such as protocol design, patient/investigator recruitment, etc. 

Globalization impact has increased clinical trials being conducted outside of United States and Europe.

 It has been driven by reduction in costs, increased patient recruitment across varying demographics, and less bureaucracy.

 Eighty-nine percent of all drug candidates from the initiation of Phase I through FDA approval fail in the clinic. Adaptive trials offer the potential to enable more levels of doses to be studied using maximum tolerated dosage over a select patient population.

  Adaptive trials improves the decision making in the identification of drugs with reduced probability of success.

  by identifying patients that meet clinical protocol criteria. Clinical data captured via these methods are helping answer questions about the safety, effectiveness, and costs of new treatments.

The proposed approach is based on building clinical studies centered on the following steps: 					

Developing study/protocol based on individual protocol components that are stored in a reusable CDISC-based repository.

Designing individual eCRF page elements that are stored in a eCRF library.

Leveraging study maps which define eCRF pages based on linking eCRF page elements to study/protocol components.

Building entire eClinical studies based on study maps.

The intent of the proposed approach is to enable the reduction in cycle times based on process improvements including reuse of clinical trial design content (study design and study build) while providing for a flexible framework that adapts to meet clinical protocol needs (Figure 1). 

Each of the key components of proposed solution architecture is described in detail below: 

 This component is based on document management solutions that provide structured authoring,

  wherein complex documents are broken down into smaller components and then assembled together via document maps to create final published documents in multiple formats. In the case of clinical trial protocols, it is based on decomposing clinical trial protocols (includes protocol amendments) into components and building protocol components independently and then assembling these components into protocol documents using pre-defined protocol document maps. All these components are stored in a document store called the protocol repository that serves as the primary content storage mechanism for managing protocol components. The protocol repository is based on the protocol representation model (PRM)—a CDISC standard that supports the planning and design of a clinical trial protocol including protocol amendments. Further, the submission data tabulation model (SDTM)—trial design model (TDM) datasets are used as a source of elements for PRM. 			

As this approach to protocol authoring takes effect, the protocol repository becomes richer in content and further drives speed of authoring protocols.  This approach results in reduced overall time to approve studies/protocols based on: 			

Minimizing document hold-ups with different authoring groups. 

Using a component library that brings speed to content creation by reusing elements and also developing standard components that do not change across protocols.

Enhancing support for regional/local/country specific protocol changes by targeting specific protocol components that are impacted due to regional regulatory needs, which also speeds up overall approval times compared to traditional approaches. 

The implementation of this part of the proposed architecture can be based on configuration of pre-existing structured/component authoring solutions that meets this proposed approach.

  manages the design and build of the eCRF pages including the underlying clinical database that support these eCRF pages, all during the study build phase. This architecture component provides this feature and also includes the eCRF design tool that enables the layout and creation of eCRF pages. The study definition interchange provides a standard-based CDISC integration layer that describes the protocol structure defined during the study design via a map. This map links pre-existing elements across protocol and eCRF page elements. During the study build phase (i.e., eCRF build) the EDC platform processes the map information to link each of all protocol component elements to its corresponding eCRF page elements based on these maps. The eCRF pages are then generated including the database to store eCRF results. Within this component as eCRF pages are generated, for those protocol components for which eCRF page elements do not still exist in the eCRF library, new eCRF pages including maps will be created and maintained.  

This is the core component of the proposed architecture and functions as the connectivity layer between protocol authoring (study design) and eCRF build (study build). The study definition interchange component manages all mapping and any transformations that are necessary between protocol elements and eCRF page elements. It provides integration services that are based on CDISC standards linking protocol authoring platform to the EDC platform. The rules, transformations, and maps linking study/protocols to eCRF pages are also stored within this component.  Maintaining all these elements requires a simple user-interface to create, update, and manage components throughout the lifecycle. On the study design (protocol authoring) side, all elements in the protocol repository are exposed in the form of PRM elements within the study definition interchange layer in order to be transformed into specific eCRF page elements based on pre-existing protocol maps and transformation rules. On the study build (eCRF page creation) side, the study definition interchange component takes each protocol component exposed as PRM components and maps it to eCRF page elements based on clinical data acquisition standards harmonization (CDASH) standard, a subset of CDISC.   

Since the study definition Interchange component of the proposed solution architecture has to be designed and built, below are some key design considerations for this component: 					

Store all study definition metadata in this component.

Leverage dictionaries and CDISC standards to provide interoperability between clinical systems across study design and build (e.g., WHO Drug, PRM/SDTM/TDM/ODM/CDASH, etc.).

Align on standards naming/metadata across all areas (global, therapeutic area, study, etc.).

Maintain version control, data traceability, and audit trails for regulatory compliance.

Leverage an ETL engine that supports transformation and store maps for study metadata across standard libraries. 

The study definition interchange is a new component that does not exist in the market and will need to be developed or extended based on some pre-existing solutions.  

For the clinical trial design automation approach to be effective it is integral for the maintenance of both the standard libraries—protocol and eCRF—both of which manage and store protocol components across all clinical trials (Figure 3).  

Key groups for proposed process are described in detail below: 					

The governance committee is responsible for managing and approving overall content within study standard libraries: protocol and eCRF. They also approve QSD (quality system documents) that describe the process and policies to help manage study standard libraries.

The standard libraries librarian helps manage, track and get documentation ready to governance committees for approval. Based on approval status help notify users of standard libraries in terms of components that are ready to be published and made available for clinical studies within the organization.

The component proposer group is primary authors of components that exist in the standard libraries. This group is responsible for preparing documentation on new components including updates to pre-existing library components. Works with the librarian group in getting documentation ready for approvals via the governance committee.

These three groups in concert with the proposed process help maintain the study standard libraries and enable the proposed approach in driving efficiencies into study design and study build process. 

Benefits of clinical trial design automation

 The benefits for the proposed clinical trial design automation approach are as follows:

Structured protocol authoring drives: quality, efficiency,search, and collaborations.

Standards based development enables upstream anddownstream integrations.

Ensures compliance with SOPs and regulations.

Study design—clinical data capture build (eCRF):

Standardized protocol and eCRF libraries improve reusability,visibility, and maintenance.

Industry standards (CDISC) based metadata and datacapture.

Enhances management of eCRF while enabling enhanceddata collection methods.

Streamlined clinical development process, harmony betweenclinical operation and data management.

Facilitates easier management of documents based on documentrepository with version controlled check-in checkoutcapability, approval workflow, and electronic signatures.

Improved productivity (notifications and task management)and compliance.

Data is exchanged electronically using the CDISC-basedXML engine instead of documents.

A single authoritative source of truth is maintained andconsumed by the protocol documents and trial specificeCRF pages.

Enabling data mining/analytics around clinical trial design.

Incorporating CDISC-based libraries to store study components for study design and building eCRF pages.

Srini Dagalur

Articles

CTMS: What You Should Know

Clinical Trial Design Automation