Initiatives

Today, NESTcc announced 12 new Real-World Evidence (RWE) Test-Cases.  These projects will answer questions of importance to the medical device ecosystem through collaborations between NESTcc Network Collaborators and submitting organizations, including health systems, government organizations, non-profit patient organizations, and medical device manufacturers.  NESTcc’s Test-Case portfolio now includes 20 projects that span the Total Project Life Cycle (TPLC); leverage multiple data sources including device registries, electronic health records (EHR), claims, and patient-generated health data (PGD); and include technologies of interest across 9 disease areas and along the 510(k) and premarket approval regulatory pathways.  Included in these new projects are the first Test-Cases to utilize patient-generated health data (PGD), the first active surveillance project, and the project in response to a question submitted from a patient advocacy organization.

Read the full Press Release, including a full overview of NESTcc’s projects and collaborating organizations, here.

On April 2, 2019, MDIC’s External Evidence Methods (EEM) program hosted an Executive & Fellows meeting with about 70 subject matter experts from FDA, industry, and non-profit organizations to discuss the existing methods and identify gaps for the use of external data.

MDIC’s EEM program aims to establish a more predictable pathway for use of external evidence methods, such as new, innovative (Frequentist/Bayesian) methods and the cataloging of existing methods for evidence fusion from data external to a clinical trial. External trial data includes but is not limited to real-world data (RWD), real-world evidence (RWE), engineering modeling and simulation, and similar device clinical trial data to support regulatory medical device decisions and other stakeholder decisions.

The meeting started with updates about MDIC and the program, followed by morning sessions led by FDA representatives highlighting the utility of the Medical Device Development Tools (MDDT) program in promoting innovation in medical device development and regulatory science to help bridge the gap between the research of medical devices and the delivery of devices to patients. Attendees also heard about the progress made through NESTcc initiative towards sustainable generation and use of timely, reliable, and cost-effective RWE throughout the total product lifecycle, using RWD. NESTcc’s Data Network Director Robert Zusterzeel also outlined the efforts made by NESTcc Data Quality and Methods Subcommittees towards developing data quality and methodological standards, design processes for demonstrating conformance to the standards, and recommendations for their implementation.

The morning concluded with a demonstration of one of the novel industry-FDA collaborative projects aimed at transforming the medical device innovation ecosystem with InSilico clinical trials and hearing ase studies focused on leveraging external data to generate evidence. Attendees were also able to learn how FDA and industry collaborated on a mock IDE submission sponsored by MDIC to augment a clinical study with Virtual Patient models. All resources related to this mock submission can be found here.

In the afternoon, the SMEs were split into four breakout sessions, as shown below – each group with equal distribution of FDA and industry members – and addressed different buckets of external data.

1. Historical Clinical study data (US/OUS); Led by Chris Mullin (NAMSA)
2. Registry Data; Led by Yun-Ling Xu (FDA)
3. Modelling and Simulation; Led by Tarek Haddad (Medtronic)
4. Admin Data (EHR, Claims etc.); Led by Ted Lystig (Medtronic)

The groups discussed characterizing data type (data quality; access; relevance), cataloging existing statistical methods that can be utilized (Frequentist/Bayesian), describing limitations of existing methods/data type, identifying areas where new methods need to be developed, and identifying examples for the use of external data as evidence.

Please follow MDIC’s EEM webpage for the latest updates.

MDIC will release a Request for Information (RFI) on March 30, 2019. We are requesting technical information about available and possible approaches for creating a set of human cell lines that include all–or subsets of– specific variants. The variants were drawn from a larger list developed by the MDIC SRS working group and include clinically actionable oncogene variants as defined by (1) those that are included in companion diagnostic labels or described in NCCN guidelines (Level 1) or(2) variants included in registrational trials (Level 2). Please note that MDIC SRS is also interested to incorporate variants in tumor suppressor genes into a possible set of future reference samples.

The RFI will be available for download, on March 30 at 5:00pm in MDIC’s Resource Library.

A webinar will be held on Thursday, April 4 at 4:00 pm ET for Q&A on the RFI. For more information click here.

Dr. Marc Horner, MDIC’s Blood Damage Modeling Working Group Chair, will discuss the Blood Damage Modeling project updates and future directions at the BMES/FDA Frontiers in Medical Devices Conference: The Role of Digital Evidence to Support Personalized Patient Healthcare on March 19-21, 2019 at the College Park Marriott Hotel and Conference Center at the University of Maryland.

This conference will provide a forum for participants involved in the development and evaluation of medical devices to meet and share their expertise, establish collaborations, and discuss strategies to effectively utilize computational modeling to support patient care and improve final outcomes.

MDIC’s Blood Damage Modeling Working Group was established in 2014 to explore the opportunity for computational modeling as a regulatory science tool to augment safety evidence for medical devices. The focus area of the Working Group is the in-silico evaluation of mechanical blood damage, specifically hemolysis, and thrombosis. The Working Group is comprised of computational modelers and experimentalists from FDA, medical device manufacturers, and nonprofits. The group working in close collaboration to generate data, develop and/or evaluate computational models using experimental systems that can assess and predict blood damage under a variety of conditions and to provide measures of precision and multi-laboratory reproducibility. MDIC’s Data Science & Technology Program Director, Dr. Jithesh Veetil, will be available at the conference to discuss various initiatives and opportunity for collaborations.

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