Why is GRIDALL So Compelling A Tool In Research?

In my previous post, I talked about GRIDALL and how we’ve incorporated it into Pipeline’s new Planning Module. But why is GRIDALL so compelling in research? Admittedly all the worked examples of GRIDALL found in Joe Stadler’s book [Project Management for Drug Developers] come to us from the development world — it IS a book about Development Project Management after all.

The first thing you learn about science in school, is that it’s all about storytelling -- storytelling with data and facts. You see that reflected in the best presentations and posters at any conference. What I find compelling about GRIDALL is it’s a tool for capturing all the elements of a story about a project.

Goals - what did we set out to prove or understand?

Risks/Issues - what were the impediments both potential and actual to achieving those goals?

Decisions - what decisions did we take along the way, why did we take them, what were our assumptions when we took them?

Lessons Learned - what did we learn along the way

This last bit is especially important since science is basically a methodology for accretive learning.

I spent part of my early career working on Knowledge Management systems, and one of the key aspects of that work was ensuring that once a discovery was made, it was reused and continuously improved upon.?

In the case of Lessons Learned, too often the initial importance of a discovery is not understood or applied elsewhere in the organisation. But imagine if you could take the lessons learned and bring them to the right person, at the right time. Then you have a means of ensuring that the impact of a discovery reaches beyond the bounds of a single project.

In more concrete terms, suppose you are a chemist who’s discovered a certain substructure that makes it easier for a compound with that moiety to bind to a particular domain or motif of a target protein? What if a chemist working on a different project could be notified of that discovery, when they’re designing a new compound library for a different protein with the same motif?

Moreover, by consistently "chunking" the information in this manner, it makes it easier for an LLM to ingest and learn from.

If you'd like to see how we're applying GRIDALL in Pipeline's Planning Module, contact Eric Robbibaro for a demonstration.