Collaboration as the key to turning around the drug discovery business (Part 8) – Standards
Collaborative drug discovery platforms are broadly applicable across therapeutic areas, targets, and teams.
All drug discovery projects have numerous conserved technical and commercialization hurdles. The regulatory, scientific, and economic foundations of drug development are conserved. Apart from the fascinating, idiosyncratic manifestations arising from different molecules, targets, assays, and teams…there are common, systematic technical challenges inherent to the lead identification and optimization processes. So, despite the great variation in scientific projects and assay methods; fortuitously, at a data level for the vast majority of cases, the common standards have become self-evident (sdf, csv, SMILES, xls, plates, controls, IC50s, hyperlinks, attachments, protocols). This is exciting, because there is a universal language for drug discovery collaborations (and collaborators) that transcends cultures, languages, timelines, and budgets.
Common standards coupled with conserved drug optimization process workflows suggest a finite set of collaborative technologies can meet the vast majority of drug discovery informatics requirements. From individual researcher needs, a common foundation for collaborative science has emerged upon which “all ships can rise”.
From hundreds of experiences with leading commercial, academic, and government laboratories, we have learned that each researcher needs fine-grained data access control for effective collaborations. Control can be temporal, spatial (data type), or project specific. Providing facile control of each collaborator’s data access within natural workflows (with minimal activation barriers for data import and selective sharing) has been the key for more effective collaborations. Effective collaborations require fine-grained control in a secure environment for selective data sharing without multiple data uploads for pre-patent, pre-publication, and pre-Pubchem data (i.e. data/IP sharing capabilities as the data is being created). Researchers want the freedom to conveniently share data within their regular workflows with no one, anyone, or everyone. Researchers want to conveniently share data any time but need the default technology setting to provide maximum privacy as a safeguard.
There are two “activation barriers” that need to be lowered for facile collaboration around data. The first barrier of accurately and meaningfully capturing the data from the experiments is not as trivial as it sounds, and it is generally under appreciated. Conversely, the second barrier of needing to keep data private for commercialization reasons is generally over emphasized. In this context, it is worth remembering that even upon patenting, information is shared, albeit not directly in a reusable database format.
By lowering barriers for both archival and selective sharing, we can begin to reap the benefits of Internet-catalyzed collaborations across the entire academic, industry, non-profit, and government drug discovery ecosystem. To be competitive in a global economy, people increasingly collaborate between organizations.
The CDD Vault for chemical registration and SAR is lightweight for budget-sensitive labs and collaborative to scale. Today for the first time it does not matter if researchers are in the same room or across the globe, there are ways to the minute to “allow groups with diverse IP/data requirements to work together, as if one.”
P.S. Beyond collaboration as a more enlightened approach to science, here are the top 5 practical reasons collaborative scientists rock with CDD: https://www.collaborativedrug.com/buzz/2011/10/17/5-reasons-why-collaborative-scientists-use-cdd/
You can also download the full series “Collaboration as the key to turning around the drug discovery business” by Barry Bunin as a pdf document: