Explaining Business Scenarios for Trial Manager

Users can use this app to:

• Create program-specific demand objects as containers for demand items
• Delete and edit demand objects
• Add contacts and post comments relating to demand objects
• Change the planning horizon of a demand object
• Create demand items within a demand object
• Plan at demand item level with weekly or monthly time buckets
• Add contacts relating to demand items
• Push demand items to Supply Planning
• Deactivate demand items when users no longer wish to maintain demand for them in this app
• Assign demand items to a study

Users can utilize this application to effectively manage various aspects of clinical studies and streamline their planning processes with a comprehensive set of tools and features.

Firstly, the application allows users to create detailed studies. This functionality enables users to define and set up new clinical studies within the system, encompassing all necessary parameters and configurations to ensure accurate and organized trial management.

In addition to creating standard studies, users can also create lean studies that require no scenarios or forecasts and plan demand for them. This feature is particularly useful for studies that need to be fast-tracked or have straightforward requirements. By bypassing the need for detailed scenarios and forecasts, users can quickly set up and start planning demand for these lean studies.

Furthermore, users can link a study to the Clinical Trial Management System (CTMS) repository. This integration ensures that all relevant study data is synchronized and accessible within the CTMS, facilitating seamless data management and enhancing the overall coordination of the clinical trial.

The application also provides the capability to define site groups and placeholder site groups. Users can initially create placeholder site groups, which can later be replaced by one or more actual site groups as the study progresses. This feature helps in maintaining flexibility and accommodating changes in site allocations during the planning phase.

Users can create kit types, assign materials to them, and define blinding groups and label groups. This functionality allows for detailed configuration of the kits used in the study, ensuring that all materials are accounted for and that the necessary blinding and labeling requirements are met.

Additionally, the application enables users to request new materials for use in a study. This feature simplifies the process of acquiring necessary materials, ensuring that the study has all required resources available.

Users can also create scenarios as a basis for running simulations and comparing calculation results, including enrollment progress. By setting up various scenarios, users can explore different planning options, evaluate their impacts, and make informed decisions based on simulated outcomes.

The application supports the creation of randomization and treatment groups, as well as the definition of randomization group switches. This functionality ensures that the study design accommodates different treatment arms and allows for flexibility in randomization strategies.

Users can specify competitive enrollment for selected site groups within a randomization group. This feature allows for the management of enrollment rates across different site groups, ensuring balanced recruitment and optimal study progress.

The application also allows users to define treatments and assign kit types to them. This ensures that each treatment arm is properly aligned with the required materials, facilitating organized and efficient administration of treatments.

Furthermore, users can create treatment schedules and assign treatments to dispensing periods. This functionality ensures that treatments are administered according to a predefined schedule, promoting adherence to the study protocol and ensuring consistency.

The application supports the assignment of subject switches between treatment groups at the end of periods. This feature allows for the flexibility to move participants between different treatment arms as per the study's design and requirements.

Users can plan site seeding demands, replacement demands, and kit type switch demands. This detailed planning capability ensures that all aspects of study logistics are covered, from initial site supplies to ongoing replacement needs and kit transitions.

Additionally, users can view a network graph depicting a study's basic structure within a selected validity period. This visual representation provides a clear overview of the study's setup, helping users understand the relationships and flow between different components.

Lastly, users can review enrollment progress for a scenario's randomization groups. This feature allows for the monitoring and assessment of recruitment efforts, ensuring that enrollment targets are being met and identifying areas for potential improvement.

In summary, this application offers a comprehensive suite of features for creating and managing clinical studies. Users can establish studies, create lean studies, link to the CTMS repository, define site groups, configure kits, request materials, create and compare scenarios, manage randomization and treatment groups, specify competitive enrollment, define treatments and schedules, assign subject switches, plan demands, view network graphs, and review enrollment progress. These functionalities collectively enhance the efficiency, organization, and effectiveness of clinical trial planning and management.

The Study Master is a new dedicated object to hold all study-defining data and parameters for clinical demand planning. This includes:

• Study description
• Study status
• Sponsor
• Lead molecule
• Study type, phase, therapeutic area

The contacts represent key staff assigned to the trial supply chain of a study, for example:

• Trial manager
• Supply manager
• Other configurable entries

Site groups can represent individual countries, groups of countries, or regions inside a country. This is dependent on customer requirements.

• Select suitable list of site groups for a study
• Add further site groups to study at a later stage

The central depot is the manufacturing site for the clinical finished goods, whilst the distribution depot is the suppling depot for a certain site group.

Depots are assigned to a site group.

• Maintain lead times to be considered in the delivery process
• Regulatory status

Blinding groups are structures to hold different materials blinded together under one blinded description. Blinding groups are then used in the kit type design.

• Blinding group description
• Blinded description is the text for output in labels and documents
• Label information can be retrieved from the Molecule Based Description app, depending on the configuration setting (optional)

Kit types allow to combine blinding groups, label groups, site groups, and materials. Thereby, blinded or open label kit types can be defined for different country combinations to plan label content for clinical finished goods. 

Decide if the drug administration is at home or on site by the kit type. Deselect the serialized flag for open non-serialized studies.

• The kit type represents the clinical finished good, which is distributed to a country
• Blinding group for blinded studies only
• Label groups represent countries with same regulatory and country requirements

In case a material does not exist, the trial manager can trigger the material creation process from the study master.

• The system notifies the master data responsible person about a new material request.
• The requested material can already be used for the demand forecast calculation before it is created and approved in the material master.
• The trial manager is notified as soon as the material is approved. The material status changes from 'requested' to the finally created material.
• When a request is rejected or approved, the material assignment to the kit type is automatically updated.

Users can utilize this application to manage and synchronize updates from a Clinical Trial Management System (CTMS) repository, ensuring that their study data remains current and accurate.

Firstly, the application allows users to see a list of studies that have new, unprocessed updates available from the CTMS repository. This listing also includes the date on which the data was last updated within the CTMS. By providing this information, users can quickly identify which studies have recent changes that need to be reviewed and processed. This functionality helps in maintaining a comprehensive overview and ensuring that necessary updates do not go unnoticed.

Once users identify a study with available updates, they can select that study to view the differences between the CTMS data and the current study data. This comparison is available at various levels, including the study level, scenario level, and site group level. By examining these differences, users can gain a detailed understanding of how their current datasets differ from the latest information in the CTMS repository. This feature facilitates a thorough review process, ensuring that discrepancies are identified and evaluated.

To maintain data consistency and accuracy, the application offers multiple synchronization options. Users can choose to sync all differences for the entire study, ensuring that all updates from the CTMS repository are applied to the study data in one comprehensive action. Alternatively, users can opt to sync all differences for a specific section, such as a particular site group, focusing the synchronization efforts on specific areas of interest or need. For even more granularity, users can sync individual differences, allowing for selective updates based on specific data points that require adjustment.

In summary, this application provides robust tools for managing and synchronizing updates from a CTMS repository. Users can view a list of studies with new, unprocessed updates and see the date of the latest data update from the CTMS. They can then select a study to compare CTMS data with current study data across different levels, from the overall study to specific site groups. Finally, users have the flexibility to sync all differences for an entire study, specific sections, or individual differences based on their requirements. These features collectively enhance the accuracy and currency of study data, ensuring seamless integration and up-to-date information in clinical trial management.

Users can utilize this application to comprehensively manage and analyze various aspects of clinical trial planning and monitoring, ensuring accurate and efficient execution of study scenarios.

Firstly, the application allows users to calculate planned enrollment, visits, and demand for study scenarios. This functionality enables users to generate detailed projections of participant enrollment numbers, scheduled visits, and the required resources for each study scenario. These calculations form the basis for effective planning and resource allocation in clinical trials.

In addition to scenario-based calculations, users can plan enrollment for a site group manually. This feature provides flexibility for users to define specific enrollment targets for individual site groups, accommodating unique site characteristics and ensuring tailored planning for each location.

Users also have the capability to modify planned enrollment figures manually. This allows for adjustments to be made to initial projections based on updated information or changing study requirements, ensuring that enrollment plans remain relevant and accurate.

The application supports the manual entry of actual enrollment and dropout figures. This functionality allows users to record the real-time progress of participant enrollment and any dropouts that occur during the study. By capturing this data, users can closely monitor the study's progress and make necessary adjustments to their plans.

Additionally, users can adjust "Do Not Ship" lead times for defined segments of demand. This feature enables the customization of lead times for shipment restrictions, ensuring that supplies are managed according to the specific needs of different demand segments within the trial.

The application provides robust tools for viewing and analyzing calculation results in both chart and table form. This allows users to visualize and interpret their data effectively, facilitating informed decision-making based on comprehensive analyses.

For comparative analysis, users can compare calculation results for two scenarios of the same study. This feature helps identify differences and evaluate the impact of varying scenarios, aiding in the selection of the most effective planning strategy.

Users can configure scenario-specific alerts for selected monitoring levels, such as competition group, randomization group, or site group participating in competitive enrollment. These alerts help in proactively monitoring key metrics and ensuring that any deviations from the expected parameters are promptly addressed.

The application enables users to view triggered alerts and the corresponding deviations from thresholds. By monitoring these alerts, users can quickly identify and respond to issues that may arise during the study, maintaining control over the trial's progress.

Users can also monitor the enrollment progress of a scenario in terms of planned versus actual enrolled subjects or planned versus projected Last Subject First Visit (LSFV) date. This monitoring ensures that enrollment goals are being met and timelines are being adhered to, allowing for timely interventions if necessary.

Finally, the application allows users to push demand to Supply Planning in SAP S/4HANA by site group and depot. This integration ensures that demand planning is synchronized with supply chain management, facilitating the efficient and coordinated distribution of trial materials.

In summary, this application provides a comprehensive suite of tools for calculating, planning, monitoring, and analyzing various aspects of clinical trials. Users can generate detailed projections, manually adjust plans, record real-time data, customize lead times, analyze results, compare scenarios, configure alerts, monitor progress, and integrate with supply planning. These functionalities collectively enhance the accuracy, efficiency, and effectiveness of clinical trial management

Users can leverage this application to comprehensively manage Interactive Response Technology (IRT) settings and master data, ensuring accurate integration and mapping of clinical trial information.

Firstly, the application allows users to create IRT actuals settings. This functionality enables users to define and configure the settings required for capturing and processing actual data from IRT systems. By setting up IRT actuals, users ensure that real-time data regarding subject enrollment, treatment administration, and other critical trial activities are accurately recorded and integrated into the clinical trial management system.

In addition to creating IRT actuals settings, users can also edit a source of IRT actuals. This feature provides the flexibility to modify existing settings and configurations as needed, accommodating changes in the trial protocol or data requirements. By editing the source of IRT actuals, users can maintain the relevance and accuracy of the data being captured from IRT systems.

The application further supports the management of IRT master data, which includes subject statuses, treatment arms, dose levels, and phases. This functionality allows users to define and organize key elements of the clinical trial structure within the IRT system. By managing this master data, users ensure that all aspects of the trial are systematically categorized and accurately represented, facilitating efficient trial management and reporting.

Moreover, users can map IRT master data to study treatment groups. This feature enables users to align the treatment arms, dose levels, and phases defined in the IRT system with the specific treatment groups established for the study. By mapping IRT data to study treatment groups, users ensure consistency and coherence between the IRT system and the trial management system, enhancing the accuracy of data integration and interpretation.

Additionally, the application allows users to map IRT subject statuses to study subject statuses. This functionality ensures that the statuses of subjects captured in the IRT system are accurately reflected in the clinical trial management system. By mapping IRT subject statuses to study subject statuses, users maintain a clear and unified view of subject progression and status changes throughout the trial.

In summary, this application provides users with a robust set of tools to manage IRT settings and master data. Users can create and edit IRT actuals settings, manage critical elements like subject statuses, treatment arms, dose levels, and phases, map IRT master data to study treatment groups, and align IRT subject statuses with study subject statuses. These functionalities collectively enhance the accuracy, consistency, and efficiency of integrating and managing IRT data within clinical trials.

Users can leverage this application to efficiently review and manage Interactive Response Technology (IRT) actual data, ensuring both an aggregated overview and detailed, subject-level insights, along with the capability to address any mapping issues that may arise.

Firstly, the application enables users to review processed IRT actual data at both aggregated and subject levels. This functionality provides a comprehensive view of the collected data, allowing users to analyze overall trends and metrics for the clinical trial as a whole, as well as drill down into the specifics of individual subjects. By reviewing data at these two levels, users can gain a holistic understanding of the trial’s progress and performance while also being able to identify and examine detailed individual subject data where necessary.

At the aggregated level, users can observe summarized data, such as overall enrollment figures, treatment administration rates, and other key performance indicators. This perspective is crucial for high-level decision-making and monitoring the trial’s overall adherence to its protocols and timelines.

At the subject level, users can delve into granular data points for each participant in the trial. This includes specific details about each subject’s enrollment status, treatment progress, dose levels, and any other pertinent individual metrics. Reviewing subject-level data allows for closer scrutiny of individual participant experiences and outcomes, which can be essential for identifying anomalies and ensuring the accuracy of recorded information.

In addition to data review capabilities, the application also allows users to view and resolve mapping issues. This feature ensures that any discrepancies or inconsistencies between the IRT actual data and the clinical trial management system are identified and addressed promptly. By viewing mapping issues, users can quickly pinpoint where data alignment problems exist, such as mismatches between IRT subject statuses and study subject statuses or incorrect associations between treatment arms and study groups.

The resolution of mapping issues involves correcting these discrepancies to ensure that all data is accurately integrated and reflects the true state of the trial. Users can make necessary adjustments to the mappings, ensuring that the IRT data is correctly synchronized with the study data. This process maintains data integrity and ensures that all stakeholders have access to reliable and accurate information for making informed decisions.

In summary, this application provides users with essential tools for reviewing and managing IRT actual data. Users can analyze processed data at both aggregated and subject levels, gaining valuable insights into overall trial performance and individual subject details. Additionally, users can view and resolve any mapping issues, ensuring accurate data integration and maintaining the integrity of the clinical trial information. These functionalities collectively support efficient data management and enhance the accuracy and reliability of trial monitoring and reporting.

Users can utilize this application to effectively view, filter, and manage a list of items received from Clinical Trial Management System (CTMS) repositories. This comprehensive functionality is designed to ensure that users can easily access and analyze detailed information about the data being integrated into their clinical trial management processes.

Firstly, the application provides users with the capability to view and filter a list of items received from CTMS repositories. This list includes a range of critical details such as the source system from which the data originated, the date and time the data was received, and the linked protocol associated with the data. By providing these details, users can quickly identify and assess the relevance and timeliness of the received items.

Additionally, the list includes information about the status, description, and type of the linked study. This ensures that users have a comprehensive view of each item's context and how it relates to ongoing clinical trials. The inclusion of these attributes allows users to make informed decisions about how to process and utilize the received data.

Users can also apply filters to this list, enabling them to sort and narrow down items based on specific criteria. This filtering capability is particularly useful for managing large volumes of data, allowing users to focus on the most relevant items and streamline their workflow. By filtering the list, users can quickly locate specific items that require attention or further analysis.

Once users have identified an item of interest, they can open it to see the specific information received from the CTMS. This detailed view allows users to drill down into the content of the received data, providing a clear understanding of the information being integrated into the clinical trial management system. By examining this detailed information, users can ensure that the data is accurate, complete, and appropriately linked to the relevant study protocols.

In summary, this application equips users with powerful tools for managing data received from CTMS repositories. Users can view and filter a detailed list of received items, including essential attributes such as source system, date and time received, linked protocol, study status, description, and type. Additionally, users can open items to access and analyze the specific information received from the CTMS. These functionalities collectively enhance the ability to manage and utilize data from CTMS repositories efficiently, ensuring accurate and up-to-date information within the clinical trial management processes.

Users can utilize this application to comprehensively manage and review demand forecasts by leveraging a range of detailed viewing and navigation features designed to enhance their demand planning processes.

Firstly, the application enables users to see a breakdown of demand forecasts by calculation status. This functionality provides a clear and organized view of the status of all demand forecasts, categorizing them based on their calculation outcomes. For example, forecasts can be grouped into categories such as successful calculations, pending calculations, and calculations that encountered errors. By breaking down demand forecasts by their calculation status, users can efficiently monitor the overall health and progress of their demand planning activities.

Additionally, users can navigate to a list of demand forecasts prefiltered by the selected calculation status. This feature allows users to quickly access and focus on specific subsets of forecasts that require attention. For instance, if a user is interested in investigating issues with failed calculations, they can select the corresponding status to view only those forecasts. This prefiltered navigation enhances efficiency by enabling users to zero in on the most relevant data without sifting through unrelated items.

The application also provides users with the ability to see lists of successful and failed forecast calculations. These lists can be sorted by time or message severity, giving users multiple dimensions to analyze the data. Sorting by time allows users to track the chronological order of forecast calculations, making it easier to identify recent trends or recurring issues. Sorting by message severity, on the other hand, helps users prioritize their actions based on the criticality of the messages associated with each calculation. This dual sorting capability ensures that users can effectively manage and respond to both successful and problematic forecasts.

Moreover, users can navigate to a specific demand forecast. By selecting a particular forecast from the list, users can delve into detailed information about that forecast, including the underlying data, assumptions, and any specific issues encountered during the calculation process. This detailed view allows for thorough analysis and troubleshooting, ensuring that users can address any problems and refine their demand forecasts as needed.

In summary, this application offers users a robust set of tools to manage and review demand forecasts with a high level of detail and precision. Users can see a breakdown of demand forecasts by calculation status, navigate to prefiltered lists based on selected statuses, view and sort lists of successful and failed forecast calculations by time or message severity, and access detailed information for specific demand forecasts. These functionalities collectively enhance the accuracy and efficiency of demand planning processes, ensuring that users can effectively monitor, analyze, and respond to their demand forecasting activities.

Users can leverage this application to efficiently manage shelf life data for materials used in clinical studies, ensuring compliance with country-specific regulations and maintaining the integrity of trial materials.

Firstly, the application allows users to create a shelf life version for a combination of study and primary pack material or for a study-flavor ID combination. This functionality enables users to define shelf lives for different configurations of study materials, ensuring that each combination is accurately tracked and managed. By creating specific shelf life versions, users can maintain precise control over the expiration dates of various materials used in clinical trials.

Additionally, users can enter the validity period for each shelf life version. This feature allows users to specify the duration for which the material remains usable, providing a clear timeframe for its effectiveness. By entering the validity period, users ensure that materials are only used within their approved shelf life, maintaining the quality and reliability of the clinical trial.

The application also supports entering and editing country-specific shelf lives. This functionality is particularly important for multinational studies where regulatory requirements differ from country to country. Users can define unique shelf life durations for each country, ensuring compliance with local regulations and standards. By editing country-specific shelf lives, users can update and maintain accurate data as regulations change.

Furthermore, users can specify whether the material is approved for use in each country. This feature allows users to indicate which countries have given regulatory approval for the use of a particular material. By tracking these approvals, users can ensure that materials are only used in countries where they are authorized, avoiding regulatory issues and ensuring compliance.

The application provides the option to choose limited, unlimited, or no shelf life auto-approval. This functionality enables users to set the level of automation for shelf life approvals based on their specific needs and regulatory environments. Limited auto-approval might be used in settings with stringent regulations, while unlimited auto-approval could be appropriate for less restrictive environments. No auto-approval requires manual intervention for all shelf life approvals. By choosing the appropriate auto-approval setting, users can balance automation with the need for oversight and compliance.

Additionally, users can choose whether to synchronize the shelf life data with a Regulatory Information Management (RIM) system. This feature ensures that shelf life data is kept up-to-date and consistent across different systems, improving data integrity and facilitating regulatory compliance. By synchronizing with a RIM system, users can streamline data management and ensure that all relevant parties have access to accurate shelf life information.

The application also allows users to indicate whether only the Investigator's Brochure is relevant for a country. This feature is useful in scenarios where specific countries require only the general information provided in the Investigator's Brochure, rather than detailed shelf life data. By indicating this, users can tailor the information provided to meet the specific regulatory requirements of each country.

Finally, users can view the packaging-relevant shelf lives calculated by the system. This functionality provides a clear overview of the shelf lives of materials based on packaging configurations. By viewing these calculated shelf lives, users can ensure that all materials are packaged and stored in a manner that maintains their validity and effectiveness throughout the study.

In summary, this application equips users with a comprehensive suite of tools to manage shelf life data for clinical study materials. Users can create specific shelf life versions, enter and update validity periods and country-specific shelf lives, specify material approval status, choose auto-approval settings, synchronize data with RIM systems, indicate the relevance of the Investigator's Brochure, and view calculated packaging-relevant shelf lives. These functionalities collectively enhance the organization, compliance, and efficiency of managing shelf life data in clinical trials.

Users can find detailed information about implementing the app in the SAP Fiori apps reference library. For latest delivery please see: SAP Fiori Apps Reference Library - Manage Shelf Life Data

In the material master of the PP material in Plant data/stor. 1 view, users will find a section for the Shelf life data. 

This information is used in the Manage Shelf Life Data app to calculate packaging-relevant shelf life.

The following data should be maintained: total shelf life (required in months).

Shelf-Life Management will be used in the Validate Clinical Batches and Expiry date app to calculate the packaging control number (PCN) expiry date.

• Create a shelf-life version for a combination of study and primary pack material
• Enter and edit country-specific shelf lives
• Update shelf-life via RIMS interface to automatically update country-specific regulatory data for your studies
• Choose limited, unlimited, or no auto-approval
• Indicate whether only the Investigator's Brochure is relevant for a country
• View the packaging-relevant shelf lives calculated by the system:
  • no auto approval = minimum (total shelf life, approved shelf life)
  • limited auto approval = minimum (limit, total shelf life)
  • others = total shelf life
• Change log functionality now available
• Additional support for flavors

Users can leverage this application to efficiently manage and monitor medication numbers associated with specific clinical studies and protocol IDs. The comprehensive features provided by the application facilitate detailed tracking and management of medication numbers, ensuring transparent and organized operations.

Firstly, the application allows users to view and filter a list of medication numbers belonging to a specific study and protocol ID. This functionality enables users to access a consolidated view of all medication numbers relevant to a particular study, streamlining the process of locating and managing these numbers. By applying filters, users can narrow down the list based on specific criteria, making it easier to find the medication numbers pertinent to their needs and ensuring efficient data management.

The application also provides users with the capability to view the status of each medication number. The various statuses include Created, Available, Assigned, Packed, Completed, Rework, or Scrapped. By displaying the current status, users can immediately ascertain the progress and condition of each medication number, from its creation to its final disposition. This real-time visibility into the status of medication numbers helps users effectively track their lifecycle and make informed decisions regarding their utilization and management.

Additionally, users can view the full details of the use of medication numbers. This detailed view includes information such as the orders to which the medication numbers have been assigned, the kit types for which they will be used, and the countries to which kits containing these medication numbers have been shipped. By providing comprehensive usage details, the application ensures that users have a thorough understanding of how and where each medication number is being utilized.

For instance, users can see which specific orders medication numbers have been allocated to, helping them track the fulfillment and logistical aspects of clinical trials. Users can also identify the kit types associated with each medication number, ensuring that the correct numbers are used for the appropriate kits, thereby maintaining consistency and accuracy in the study materials. Furthermore, information on the shipment of kits to various countries ensures that users can monitor the distribution and reach of clinical trial materials, facilitating compliance with international regulations and logistical planning.

In summary, this application provides users with robust tools to view, filter, and manage medication numbers affiliated with specific studies and protocol IDs. Users can access a filtered list of medication numbers, view their status, and delve into detailed usage information, including order assignments, kit type associations, and shipment destinations. These features collectively enhance the efficiency, transparency, and accuracy of managing medication numbers within clinical trials, supporting streamlined operations and informed decision-making.

Users can find detailed information about implementing the app in the SAP Fiori apps reference library. For latest delivery please see: SAP Fiori Apps Reference Library - Medication Number Status