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Standalone DTx: clinical & economic evidence
As DTx companies look for their place in the market, in order to convince the different healthcare stakeholders (payers, physicians, etc), they need to generate clinical and economic data that validates their products and services. The evidence requirements and challenges to generate it differ depending on the type of DTx; on this occasion we will focus on standalone DTx (DTx products used independently of drugs). Join this informal conversation with other senior leaders in the space to discuss the following:
- Level of clinical and economic evidence required for standalone DTx - how does this change depending on the stakeholder, mode of action, risk of the product, disease, etc?
- Particularities and Challenges of the Study Design for standalone DTx (e.g selecting the right comparators, inclusion/exclusion criteria, endpoints, the role of RWE, etc)
- What is the most efficient way to generate economic evidence? What methods can be used to generate this data in the different stages of a product?
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Standalone DTx: clinical & economic evidence
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As DTx companies look for their place in the market, in order to convince the different healthcare stakeholders (payers, physicians, etc), they need to generate clinical and economic data that validates their products and services. The evidence requirements and challenges to generate it differ depending on the type of DTx; on this occasion we will focus on standalone DTx (DTx products used independently of drugs). Join this informal conversation with other senior leaders in the space to discuss the following:
- Level of clinical and economic evidence required for standalone DTx - how does this change depending on the stakeholder, mode of action, risk of the product, disease, etc?
- Particularities and Challenges of the Study Design for standalone DTx (e.g selecting the right comparators, inclusion/exclusion criteria, endpoints, the role of RWE, etc)
- What is the most efficient way to generate economic evidence? What methods can be used to generate this data in the different stages of a product?
Participants
Participants
Todd Greenwood
Director, Evidence Generation and Outcomes Research, ZS
Matthias Essenpreis
Chief Technology Officer, Roche Diagnostics
Adam Samson
Sr. Director of Clinical Operations & Customer Success
Kyloon Chuah
Co-Founder & CEO @ Veriteos
Rick Bartels
Managing Partner , DTxCC
Chris Wasden
Chief Strategy Officer, Twill
Chris Cera
CEO, Arcweb Technologies
Up to 12
Standalone DTx: clinical & economic evidence
As DTx companies look for their place in the market, in order to convince the different healthcare stakeholders (payers, physicians, etc), they need to generate clinical and economic data that validates their products and services. The evidence requirements and challenges to generate it differ depending on the type of DTx; on this occasion we will focus on standalone DTx (DTx products used independently of drugs). Join this informal conversation with other senior leaders in the space to discuss the following:
- Level of clinical and economic evidence required for standalone DTx - how does this change depending on the stakeholder, mode of action, risk of the product, disease, etc?
- Particularities and Challenges of the Study Design for standalone DTx (e.g selecting the right comparators, inclusion/exclusion criteria, endpoints, the role of RWE, etc)
- What is the most efficient way to generate economic evidence? What methods can be used to generate this data in the different stages of a product?
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Set up a free HealthXL platform account for a taste of what the community has to offer. Or talk to us about upgrading to a premium account:
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- Join specialised communities in areas like DTx, AI, Clinical Trials Innovation and more
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Standalone DTx: clinical & economic evidence
Standalone DTx: clinical & economic evidence
Standalone DTx: clinical & economic evidence
As DTx companies look for their place in the market, in order to convince the different healthcare stakeholders (payers, physicians, etc), they need to generate clinical and economic data that validates their products and services. The evidence requirements and challenges to generate it differ depending on the type of DTx; on this occasion we will focus on standalone DTx (DTx products used independently of drugs). Join this informal conversation with other senior leaders in the space to discuss the following:
- Level of clinical and economic evidence required for standalone DTx - how does this change depending on the stakeholder, mode of action, risk of the product, disease, etc?
- Particularities and Challenges of the Study Design for standalone DTx (e.g selecting the right comparators, inclusion/exclusion criteria, endpoints, the role of RWE, etc)
- What is the most efficient way to generate economic evidence? What methods can be used to generate this data in the different stages of a product?
Join this group of peers and get a feel of what it's like to belong to a community of digital health gamechangers.
All meetings are limited to 10 people to allow for honest discussions, so apply fast or become a HealthXL member and get priority access to all meetings, latest industry reports and and much more.
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As member of HealthXL, you join a community of digital health thought leaders, innovators and game changers around the world. With your membership, you get access to hundreds of insights, reports and resources. You can browse a database with over 90k healthcare organizations and view their active strategic partnerships, commercial relationships, latest funding rounds and research. Through our in-house curated digital health newsfeed, you stay informed on the most impactful news and you can regularly meet with members to share learnings, discuss the latest developments and connect with peers of different demographical stakeholder groups. Contact us today to find out about pricing options.
Through focus groups, we bring together 6-10 thought leaders and industry stakeholders in a series of virtual meetings to collaborate around a defined topic. Each meeting gives the group the opportunity to examine, analyze and collaborate with one another around a digital health topic as well as produce a shareable result.
