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Advanced Therapies: Scalable and Sustainable Cell and Gene Therapies


An interesting Webinar titled “Advanced Therapies: Scalable and Sustainable Cell and Gene Therapies” will be organized on Mary Ann Liebert platform (tissue Engineering and Human Gene Therapy publications) on May 16th, 2023, 8:00 PT, 11:00 ET, 17:00 CET (the webinar will be recorded and will be host on the platform for 6 months).

The Webinar would like to underline the enormous therapeutic potential of ATMP in cell and gene therapy and show the latest research in developing ATMPs and delivering a scalable and sustainable future of medicine in cell and gene therapies.

Speakers will also analyze the potential opportunities, costs, and sustainability of ATMPs in transforming healthcare systems across the USA and Europe.

Speakers, drawn from the international scientific and technical communities engaged in R&D of advanced therapies, will discuss their latest experiences relating to advanced gene, cell, and tissue therapies; and highlight the value of collaboration between science, industry and architects to accelerate the adoption of ATMPs for the treatment of cancer and rare diseases.

 

Viewers of this webinar will learn:

  • How adoption of an open participation model, based on engagement between healthcare, industry, and academia, will help identify solutions to meet health needs.
  • How to support development and cooperation in the sector, including production, deployment, cost analysis, scalability, and sustainability of ATMPs.
  • How the scientific community can provide solutions to support the delivery and equitable access to transformative therapies.

This is the link if you are interested and would like to get more info on the webinar or register to follow it: CLICK HERE 

In case of questions, call Cristina Zanini, BD and scientific manager Advanced Therapies Department: c.zanini@bioair.it

 

Closed Systems vs Open Systems: Operational cost savings*





Total Saving

Energy

Validations

Decontamination

Gowning

* Values are given for an identical production output


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