- Whitelab Genomics is involved in projects developing DNA-based therapies for metabolic diseases, cell therapies for blood diseases, and immuno-gene therapies for cancers.
- With funding and collaborations, Whitelab Genomics aims to accelerate the development of these life-saving treatments, reducing costs and improving patient access.
- Some biotherapies cost $1 Million, Whitelab's technology not only reduces the development time of these therapies but also provides cheaper therapeutic solutions.
Whitelab Genomics, a French-American biotech, with a mission to transform the development of genomic therapies, was founded in 2019.
Using artificial intelligence (AI) and machine learning, Whitelab Genomics streamlines the discovery and design of these remedial treatments to make them more affordable and accessible to patients.
The Birth of Whitelab Genomics
David Del Bourgo, a former engineer at General Electric Healthcare together with Julien Cottineau, a geneticist who trained at the Institut Imagine; developed a simulation software for the design of gene therapies to introduce genetic material into cells to treat a disease.
The traditional methods for developing genre and cell therapies usually involve a time-consuming trial-and-error approach. This is the problem that Whitelab Genomics solves with its refined AI platform.
With the use of genomics, data science, machine learning, and computational biology for genomic therapies Whitelab Genomics helps companies cure more diseases at an affordable cost.
The platform processes this information and predicts the most effective molecular design for a specific therapy decreasing the risk of a failure at each development stage.
Whitelab Genomics partners with academics, biotech, and pharmaceutical companies to improve their R&D processes for genomic therapies. The platform helps researchers:
- By analyzing vast datasets, the platform identifies potential therapies with a higher chance of success.
- The platform assists in designing the delivery systems (vectors) and the therapeutic components (payloads) for greater efficacy and safety.
- Whitelab Genomics' platform provides valuable insights to researchers, enabling them to optimize their development strategies and select the most promising candidates for further testing.
Whitelab Genomics: Fostering Innovation through Collaboration
In collaboration with leading research institutions and pharmaceutical companies, Whitelab also strives to advance gene therapy development. Some notable partnerships were:
- 2021: Accelerator for Technological Research in Genomic Therapies (ART-TG): This collaboration used Whitelab Genomics' AI platform to optimize bioproduction processes for lentiviral vectors, aiming to increase yield and reduce costs.
- 2021: Genethon: Focused on utilizing AI to develop next-generation gene therapy vectors, Genethon researchers used Whitelab Genomics' platform to design new capsids (vectors) with improved targeting and reduced immunogenicity.
- 2023: WIDGeT Consortium (Sanofi, Imagine Institute, Nantes University): This major initiative aims to accelerate the development of AAV-based gene therapies for various diseases. Whitelab Genomics' AI expertise will be used to design next-generation vectors for enhanced efficacy, reduced side effects, and lower production costs.
- 2024: Strategic partnership with Siren Biotechnology: This platform focuses on uncovering promising new cancer therapies through the use of AAV immuno-gene therapy. Essentially, WhiteLab Genomics' AI expertise will be used to analyze vast datasets and identify high-potential cancer targets for Siren's innovative gene therapy approach.
With a Series A funding of €10 million secured in 2022, Whitelab Genomics turned its focus on the US market, planning to build a team in Boston and Cambridge to better serve their American customers.
By harnessing the power of AI and fostering collaboration, Whitelab Genomics is paving the way for a future where more patients can benefit from the transformative potential of genomic therapies.
Edited By Annette George
