Ten takeaways from FDA’s DCT Draft Guidance

US Food and Drug Administration issued a draft guidance a couple of weeks ago titled “Decentralized Clinical Trials for Drugs, Biological Products and Devices – Guidance for Industry, Investigators, and Other Stakeholders”. This guidance is now open for comments from various industry stakeholders. This is issued to comply with the FDORA requirement to provide guidance to the industry no later than 29^th Dec 2023.

This blog post is to summarize 10 key takeaways from the draft guidance along with some of my thoughts.

1. Fully Decentralized Vs. Hybrid Trials: Guidance is to use fully decentralized trials for investigational products that are simple to administer, have well-characterized safety profiles, and do not require complex medical assessments.  If not, it is noted that hybrid trials may be more appropriate with the administration of IP or complex medical assessment is performed during a site visit and other follow-up assessments could be done remotely through ePROs, telehealth, in-home visits, or by local HCPs, as appropriate.
2. DCT challenges & planning:
   • Challenges like coordination of trial activities with individuals and facilities across multiple locations that are non-traditional clinical trial “sites”.
   • Plans to conduct DCTs should include:
     • use of local facilities, personnel, etc.
     • visits to patients’ homes
     • distribution of IP to participants, at home
     • Plans are to be reviewed with relevant FDA review divisions before starting.
3. DCT Designs:
   • Need for a physical location, which should be listed on Form 1572 or IDE, where all trial-related records for participants are available and trial personnel can be interviewed.
   • May not be appropriate for a “non-inferiority” study given the variance of assessments across HCPs and thus need to be reviewed with FDA divisions beforehand.
4. Visits & Activities:
   • Telehealth visits can be considered where no in-person interaction is needed and should be specified in protocols.
   • The Adverse Event (AE) reporting process to identify and manage should be specified in the protocol.
   • All documentation (CRFs) is expected for telehealth visits and patient identities should be confirmed.
   • All personnel and patients involved in the study should be trained, as needed, to ensure consistency.
5. Digital Health Technologies:
   • Recommendation from FDA draft guidance titled “Digital Health Technologies for Remote Data Acquisition in Clinical Investigations” to be used.
   • Any technology used in the study should be available and suitable.
   • In the case of BYOD, devices should be provided by sponsors to ensure patients that cannot afford them are not excluded from the study for socioeconomic reasons.
6. Key Stakeholder Responsibilities:
   • Sponsors:
     • Sponsor responsibilities remain the same for DCTs as with the traditional site-based studies.
     • Should strive for Diversity & Inclusiveness in the patient population.Should have a Data Management Plan (DMP).
     • Describe operational aspects of DCT in the protocol.
     • Ensure compliance with local laws, regulations, and licensing requirements.
     • Ensure proper monitoring of the investigation.
   • Investigators:
     • Responsible for the conduct of DCT and oversight of individuals delegated to perform trial-related activities according to the investigational plan, applicable regulations, etc.
     • May use local HCPs, if permitted by the protocol
     • May use technologies like videoconferencing for oversight.
     • Ensure enrollment is aligned with the ability to manage and supervise.
     • Appropriate delegated local HCPs should be listed as “subinvestigators” based on their assigned responsibilities and the significance of their contributions.
     • Ensure consistency of the process, activities, and practices to minimize variability across local HCPs through regular reviews and quality control measures.
     • Designated clinical laboratory facilities should be used, where needed, for critical data that is used to evaluate outcomes.
     • Health records should be obtained from local healthcare facilities, and primary providers for any emergency and/or routine visits, with permission from patients.
7. eConsent & Institutional Review Board:
   • eConsent can be obtained from patients at their remote locations provided all regulatory requirements regarding informed consent are met.
   • FDA recommends using central IRB to facilitate efficient review of the protocol, informed consent documents, and relevant trial-related information.
8. Investigational Products:
   • Should be administered under the supervision of the investigator or the subinvestigator, unless the drug has a well-characterized safety profile and does not require specialized monitoring, post-administration.For investigational devices, should consider the type of medical use, instructions for use, risk profile, etc.
   • Investigational products or devices can be shipped directly to patients based on the considerations documented in the protocol for appropriate handling, packaging, distribution, and use.
   • If any issues arise in the case of remote administration or use of IP, sponsors must discontinue the practice and use FDA or IRB to determine the continuation or stoppage of the trial.
9. Safety Monitoring:
   • Sponsors should implement a safety monitoring plan to ensure the safety and welfare of trial participants in DCT.
   • As with site-based trials, SMP should describe how adverse events will be reported, seek medical help by the participants, and collected and responded to by the investigators.
   • Investigational products or devices can be shipped directly to patients based on the considerations documented in the protocol for appropriate handling, packaging, distribution, and use.
10. Software:
    • Software to run DCTS can be used on a variety of platforms like tablets, cell phones, laptops, etc.
    • Must be 21 CFR Part 11 compliant.
    • Ensure data reliability, security, privacy, and confidentiality.
    • Real-time video interactions and telehealth are considered to be live interactions and hence not subject to 21 CFR Part 11 
    • The software can be used to manage eConsent, reports, eCRFs, visit scheduling, IP shipment tracking, DHT recorded data collection and communication between site personnel and participants.

In conclusion, some of the aspects of traditional clinical trials remain the same while DCTs will provide flexibility in many ways to reduce the site visits and leverage DHTs to collect data directly from patients. The guidance will certainly help all the stakeholders involved in clinical trials to take a measured approach to adopt DCTs. We also need to wait for public comments and feedback and how that will impact the final guidance. This is a great step forward to raise the awareness in the industry of what the FDA is thinking but also to help drive some standardization in how sponsors, sites, patients, technology & software providers, IRBs, etc. think and act to facilitate Decentralized Clinical Trials.

Please note that this post is to summarize the guidance and share some of my thoughts for information purposes. You can read the full guidance at the link provided at the beginning of this post.

Accelerating Decentralized Clinical Trials using 8 currencies of 5G

5G is one of the recent advances in technology that will have a profound impact on telecommunication worldwide. It will transform the speed of communication with 1000x faster than existing 4G. Another key benefit is the reduction in network latency which will enable huge amounts of data being transferred in a short period of time. Telecom companies are investing heavily in setting up infrastructure in urban areas and also expanding it to rural areas. These investments will accelerate adoption of 5G and drive Industry 4.0, the 4th Industrial Revolution aided by. Hans Vestberg, CEO of Verizon, famously noted about the 8 currencies of 5G as part of his keynote address at CES 2019. Eight currencies are:

1. Greater Throughput
2. Higher Data Volumes
3. Enhanced Mobility
4. More Connected Devices
5. Faster Service Deployment
6. Better Energy Efficiency
7. Higher Reliability and
8. Low Latency

As noted in my previous blog posts, Decentralized Clinical Trials is the future of Clinical Research. When studies came to a crashing halt with COVID 19 in 2020, industry figured out a way to conduct clinical research despite the challenging pandemic situation. A lot of stakeholders from regulators, to CROs, Sites, Investigators and Technology companies came to the rescue. However, clinical research is still impacted substantially and slowly picking up speed to get back to normal. This report from Medidata titled “COVID-19 and ClinicalTrials: The Medidata Perspective” is a good source to understand the continued impact and the progress being made by the industry to deliver treatments faster to the patients. One of the most impressive and a silver lining to the pandemic, if there is one, is increase in adoption of Decentralized Clinical Trial principles. A lot of progress is made in the 12 months than over previous 4 or 5 years by some estimates. Many stakeholders had to adapt technology, core to DCT, in order to continue the research.

As innovative technologies like 5G, Internet of Medical Things (IoMT), AI/ML, VR/AR, Digital Therapeutics (DTx) etc. continue to increase in adoption, many of these will be adopted for use cases within Healthcare and Life Sciences. Some of the use case examples can be found here:

• Putting Better Outcomes at Doctors’ Fingertips
• Envisioning the Future of Robotic Virtual Surgery

As noted above in the use cases, 5G is one of the key technologies that will be influencing Healthcare and Life Sciences. In this context, let’s look at how the eight currencies of 5G can be exploited to the benefit of accelerating DCTs. The acceleration is enabled by cashing in on the currencies. Each currency delivers certain benefits that will impact the stakeholders of clinical research.

As always, I welcome your feedback and comments.

Decentralized Clinical Trials : Leveraging Medidata Clinical Cloud to support adoption during COVID

As stated earlier in one of my previous posts, regulators like FDA and EMA have recognized that the COVID-19 pandemic will impact the conduct of clinical trials and has provided revised guidelines. Considerations include, sponsors evaluating alternative methods for assessments, like phone contacts or virtual visits and offering additional safety monitoring for those trial participants who may no longer have access to investigational product or the investigational site.

Given this situation, we believe that the time is ripe for adopting Decentralized Clinical Trials and the primary levers for decentralization are:

• Modern trial design and clinical outcome assessments, that can be conducted in a study participant’s home using patient facing technologies
• Reduced dependency on a physical location of a site

With this in mind, we predict the maturity and in turn the long-term strategy to adopt decentralized clinical trials will be based on a) where the data is captured and b) how and who captured the data. Based on these two attributes, a trial design may vary from Conventional design to Decentralized.

Adoption of DCTs also depend on maturity of the tools used in trial designs. Based on our knowledge and experience, the following observations are noted across the industry:

1. eConsent, eCOA and ePRO are most acceptable and mature from regulatory standpoint
2. Telemedicine for oversight and support with chat log etc.is fairly mature
3. Wearable trackers need further maturity, transparency in algorithm. These are predominantly used for alternative endpoints and necessarily for primary end point

Given this observation, let’s look at how item #1 above can be addressed by the existing commercial solutions in the market.

I have managed many partnerships and collaborated with many eClinical platform vendors. One of those partners, Medidata, is a renowned and leading eClinical technology vendor. Some of their applications can be leveraged to support the above-mentioned approach to leveraging DCT principles to achieve ongoing trial milestones or start new trials, despite the challenges during COVID. For those customers that are already using any of the tools from Medidata, I would strongly recommend considering the following tools to complement their existing tool set:

Function/Activity in Clinical Trial	Medidata Technology	Projected Timeframe for assessment and adoption
Informed consent and re-consent	Rave eConsent	4 – 8 weeks
Patient Engagement	Rave eCOA	4 – 12 weeks
Access to Care	Rave EDC	4 – 6 weeks
Data Collection	Rave eCOA	8 – 12 weeks
Patient Visits	Rave EDC	4 – 6 weeks
Lab Tests, Imaging or Diagnostic tests	Rave Imaging	4 – 6 weeks
Reduce patient visits while better engaging the patient	Medidata Patient Cloud	12 – 16 weeks

Medidata Product Suite to enable DCTs

I hope this post gives a jumpstart to those considering eClinical technologies to support their Decentralized Clinical Trials initiative and/or looking for ways to mitigate the impact of Covid-19.

Unboxing Clinical One EDC

One of the biggest challenges IT teams supporting Clinical Systems in Life Sciences is fragmentation of the systems. The heterogenous nature of various systems that make up the platform make it even more difficult to meet the ever changing business processes. Integrated or Unified Clinical Development Platform remained a holy grail until now. Oracle’s solution, to replace their existing offerings to address this challenge is ClinicalOne platform. Clinical One platform was launched with the release of its Randomization and Supplies Management (RTSM) capability in 2017. Now they have released the next capability, Data Collection, this summer, which goes beyond traditional EDC. 

This blog post contains our views on the latest features of the Clinical One unified platform.  We believe this will help you learn about the unique value of Clinical One.

Unboxing Clinical One EDC

Over the past 20 years, technology has emerged to address inefficiencies in specific processes in clinical research; however, this has resulted in a mess of siloed point solutions that don’t work together. Gartner described this best in the research report titled “Industry Vision: Life Science CIOs Must Transform Clinical Development With Digital Trials” which shows the evolution from point solutions to a unified platform like Clinical One.

With Clinical One, you can build a study once, enter data once, and do everything in one place.  People, processes, and data are no longer isolated – they are unified.

Detailed below are some of the most valued features of ClinicalOne, in our opinion:

A. Unified Platform:

The Clinical One unified platform maximizes productivity by easily collecting, processing and integrating data.  This system simplifies data collection, aggregation and analytics. The flexible architecture facilitates easy study build, deployment and hosting.  With a full suite of transfer features, the Clinical One Data Collection capability provides you with everything you need to run a clinical research study from setup to database lock.

Benefits of a unified platform

• Study Build: Reduces the complexity and effort involved in study start-up
• Mid-Study Changes: Study design changes during study conduct can be made easily and quickly
• Single User Interface: Navigation to multiple systems is not required and Sites can randomize and collect subject data in one place
• Inter-operating: No need to prepare IVRS data transfer specification and to reconcile data between IRT and EDC systems.
• Control: Sponsor gets more control over the drug shipment and assignment

B. Key Features

User friendliness

Clinical One has an easy-to-use and human-centric user interface. From the simple and clean landing page to the site home page with options to view subject-level history and open queries to be addressed,  which makes investigators’ lives a lot easier.  Investigators can randomize a Subject, request kit re-supply, view site inventory and perform data collection with just the “click of a button” within the same platform. The “Help” module in the platform is very comprehensive involving short training videos for most of the topics.

Study design and implementation 

The study design and deployment module enables anyone with minimum experience in study design to do it. It also offers several differentiators including but not restricted to simplified CRF and edit checks design, mid-study CRF changes, randomization and kit allocation configuration, simple drag and drop approach with study deployment to production.  All of these features make developing studies in Clinical One possible in days instead of weeks.  Imminent library features will further increase productivity and reduce build times.

Data collection and workflow

Clinical One enables the investigator to screen, randomize and dispense kits to the subjects. Investigators can request new kit shipments based on details from the site inventory section in the supplies module, code break, transfer subjects and sign case books. “Question Hint” can be provided adjacent to the fields in the CRF. These can be used by Sponsors to provide all necessary input to the investigator to control data entry related errors. CRAs can perform source verification and raise queries all within the same user interface.

Data Quality and Query Management

During study design, fields can be controlled with hard or soft validations and by programmed rules. Hard validations can be applied for data formats and play an important role in preventing invalid data being entered. For example, a tip message is displayed if a user attempts to enter a numeric field beyond the boundary limit. This alert feature avoids impossible values being recorded. Soft validations can alert a user to invalid responses such as too many answers or out of range critical items that will prevent screening or randomization. As with traditional EDC systems queries can be used to flag discrepant data. These queries can be auto-generated by Rules or can be manually applied. Queries can be marked as candidate queries for internal data review and cleaning activities. A Subject query report can be downloaded in HTML or PDF format, with the option of including the audit trail.

Reporting features

Standard reports can be generated to meet the needs of all stakeholders from the Reports module within the platform. For data management, we can pull reports by study, subject and queries. Filtering options are available to extract just the data you want in the report. You can download reports in a variety of formats, such as PDF, HTML & CSV. The “Download Report” option present in the left panel will have previous 20 historical report downloaded along with timestamp.

Audit Trail

The audit trail feature is impressive because it is adjacent to the eCRF view. On the side panel, under “Answer & Visit History”, the audit trail of all data changes (including queries and sign, verify and freeze) are available. At the subject level, kit dispensed history is displayed under “Subject History” section for individual subjects.

Medical Coding

The Medical Coding functionality integrates with the Oracle Central Coding system. This offer great value to existing InForm customers who can ensure ongoing consistent coding between Clinical One and InForm studies. Central Coding supports sending dictionary terms and queries to Clinical One. This allows auto-coding and manual coding to be performed and actions to be requested via queries. Coding fields are added to the CRF and mapped to a Central Coding dictionary along with set of “Read-Only” fields to collect return values from the dictionary. Multiple dictionaries can be used on the same CRF if needed.

C. Take Away:

Based on initial exploration and use of the platform, we believe Clinical One is really revolutionizing the way technology supports clinical trials.  Clinical One is a comprehensive, unified platform packed with features that can help Life Sciences companies digitize their clinical operations. It is a compelling solution for organizations looking to make the move to a cloud-based environment to increase efficiencies in clinical study conduct with unified randomization and supplies management and data collection capabilities.

Co-Author and Reviewer : Srinivasan M (mahasrini@hotmail.com)

Recommendations for Clinical Data Acquisition, Review and Standardization in line with COVID-19 regulatory guidance

 

OVERVIEW

In relation to the COVID 19 Pandemic, Health Authorities from most of the countries provides recommendations for the management of clinical trials during the pandemic period. FDA recommends collecting information in the CRF to be able to document the missing data due to the pandemic

We are sharing few generic approaches below, for additional data acquisition due to COVID 19.

DATA ACQUISITION:

1. Possible New CRFs :

Data that needs to be collected on Impacted Visits as basis to differentiate deviations due to pandemic from other protocol deviations and to collect details of COVID 19 symptoms and test results if applicable

1. COVID 19 Impacted Visits Form – Sponsors choose to capture the Impacted visits through a new form with following predefined comments on the scheduled visits in the study
   • Missed Visit
   • Virtual / Telephonic Visit
   • Visit Delayed but Completed
   • Incomplete site visit

• COVID 19 Study Drug interruption Form – To collect the Start and End dates of COVID related interruption during the study conduct

• COVID 19 symptoms Form  (Optional) – To collect the details about the different symptoms collected from Subject

• COVID 19 Test Form  (Optional) – To collect the details about the COVID 19 test and the outcome
  • Test date
  • Type of Sample collection
  • Test Outcome (Positive, Negative, Not Done)

• Possible EDC Changes (CRF / Completion Instructions) :

1. Study Completion Form – Reason for early discontinuation to be captured as COVID 19 in this form

COVID 19 infection and COVID 19 logistical restrictions can be added as reasons in the codelist

                                       (Or)

“Other” and reason for discontinuation to be entered as COVID 19

• Adverse Event Form – Adverse Event needs to be captured in case of COVID 19 infection and associated symptoms

 New field – “Is the event related to COVID 19?”

(Or)

Include the terms COVID-19 Infection or COVID 19 Positive Lab Test along with main diagnosis Verbatim

Impact assessment to be performed and applicable changes to be decided. Potential applicable EDC changes can be adapted based on the status of Study and Subject recruitment and effort must be spent to limit the EDC changes to minimum as possible to be able to rollout the changes on a large scale in parallel.

Data Review:

Data Management should adapt their data review strategy. Following are some examples of the Data review strategy; Organizations should adjust this list based on the defined policies and type of clinical study.

• Subject Visit: How Subject visit took place if it happened during COVID 19 period?
  • At Clinical site as per schedule
  • Telephonic / Video conferencing visit
  • Virtual visit
  • visit at alternate location as subject could not travel to clinical site

• Drug exposure: How drug was administered to the subject if done during COVID 19?
  • Drug dispensed at clinical site (in case of drug that is to be taken by subject at home)

• Drug delivered to subject (in case of drug that is to be taken by subject at home)
  • Who administered the drug (Trial staff / local physician trained on trial procedure)

• Adverse Events: AE related to COVID 19? (Directly or Indirectly)?
  • If yes, then Concomitant medications taken, COVID symptoms and status details are collected etc.
• Lab data collection: Identify any changes in the way and location where Lab data was collected
  • Done at a local laboratory or relevant clinical facility
• Protocol Deviations due to COVID 19 pandemic are captured. For example
  • PD’s at Subject level (visit windows),
  • Site level PDs due to unavailability of trained staff etc.
  • Vendor level (i.e. Lab or ECG)

Data Transformation:

Data transformation changes to the applicable domains like AE, DS needs to be studied carefully and implemented without affecting the existing data standards and processes.

Data collected in above new possible CRFs referred in Data acquisition section could be mapped to SUPPSV (#1) and FA (#2 to 4) domains. However, the impact of COVID 19 and considering associated disruption in data collection/drug administration /additional symptoms/health status of subjects, it does makes sense to create a custom SDTM domain and populate data for quick and easy analysis purposes.

Prepared by : Palanipandiyan Chokkalingam (karthick.er@gmail.com)

Reviewed by : M, Srinivasan (mahasrini@hotmail.com)

Contribution from : Ravi Mhatre, Devender Kumar, Thirumalai Nathan Sivaramakrishnan

Reference:

FDA Guidance March2020 release –  https://www.fda.gov/regulatory-information/search-fda-guidance-documents/fda-guidance-conduct-clinical-trials-medical-products-during-covid-19-public-health-emergency