February 25, 2022, Rancho launched Single Cell Data Science Consortium with 4 Charter Members. This multi-year effort will deliver harmonized single cell experiments more quickly and cost effectively.

Due to their enormous potential for advancing drug discovery, there continues to be an exponential growth in the use of single cell sequencing methods, with pharmaceutical companies continuing to invest in them. In addition, there is an ever-increasing amount of single cell datasets being generated and deposited in the public domain.

The availability of vast amounts of publicly available single cell datasets offers pharmaceutical companies the opportunity to expand the universe of experiments available to their scientists many fold. While many of these datasets are freely available, they come with hidden costs that hinder the ability of companies to exploit them to their maximum potential:

More information on Single Cell Data Science Consortium

No common standards exist at present for publishing single cell datasets
It is time consuming and laborious for pharmaceutical companies to find, download and curate single cell datasets into an accepted common format so they can then be analyzed collectively

Algorithms for analysis of single cell data to help extract valuable information for drug discovery are also being published more frequently. However, it is challenging for pharmaceutical companies to:

Stay abreast of all developments given the volume of algorithms that is being published
Know which algorithms they invest time and effort in trying to use
Implement these algorithms, due to software quality and frequent lack of documentation

Funded by pharmaceutical companies with common goals and needs in single cell data, a pre-competitive approach will help to deliver:

Vastly more curated/standardized single cell datasets than would be possible by one company for a comparable level of investment
Intelligence to aid pharma companies stay abreast of new algorithms being published
Benchmarking to compare/contrast algorithms
Implementation of algorithms, prioritized by consortium members, that are re-written from scratch and provided with suitable documentation and support

Single Cell Data Science Consortium (SCDS)

BenevolentAI
Bristol Myers Squibb
Janssen Pharmaceutical Companies of Johnson & Johnson
Novartis
Regeneron
Vesalius Therapeutics

Benefits of Membership

Cost sharing approach, with far superior ROI to what one company could achieve on its own. ROI will continue to grow as more Members join.
With its expertise in data curation, Rancho can scale the effort much faster and more cost effectively than a single company.
Ability to interact regularly with like-minded peers at other pharmaceutical companies, in a pre-competitive manner, to share common challenges they face in working with single cell datasets and how the field can be advanced together

Membership in the Single Cell Data Science Consortium

New members are welcome to join the consortium
If you are interested in becoming a member, click on the link below