Single-Cell Data Science Consortium

Single Cell Logo (b4edfe2c-99e5-4d7d-a181-a7232519c3af).png_1672161329

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.

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

Due to their enormous potential for advancing drug discovery, there continues to be 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 manyfold. 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:

  • 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:

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 in staying 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) Members

  • BenevolentAI

  • Bristol Myers Squibb

  • Eisai

  • Janssen Pharmaceutical Companies of Johnson & Johnson

  • Novartis

  • Regeneron

  • Takeda

  • Vesalius Therapeutics


Membership in the Single-Cell Data Science Consortium

New members are welcome to Join the Consortium.
If you would like to sign up please click the button below