WIIFY Part 3 – Modern Drug Discovery Tools for Large Collaborative Consortia

A three part series exploring the unique challenges of Consortia scientists

Part 3 – What’s in it for you, the person who actually has to do the work

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You are the one actually doing the work, the hard work that others eschew.   Parts of science can feel like working in quicksand, with handcuffs on.  There are multiple problems, and as soon as you fix a problem, new ones emerge.   You must do reproducible science – the hallmark of good science.   On top of all the experimental challenges, you have this mountain of data to deal with.   Big data typically means big headaches.  And whose lap does all this data fall into – why yours, of course.   As if you are not busy enough?  Isn’t it enough to just run all these experiments?   Who has time to look at thousands or even millions of data points?   Even worse than the numbers are the formats, the raw data from the plate readers or other instruments is different than the format needed to make heads or tails of the data relative to the controls you painstakingly included in the appropriate columns.  When something unexpected happens (and when doesn’t that happen) like an instrument hiccup, or running out of a key reagent midway through a run, then the data must be looked at within the context of whatever the unexpected anomaly happens to be this time.  Yes big data = big headaches.  Well fret no more, you have a partner by your side each step of the way with CDD.

CDD has felt your pain and is your ally in the fight for your right to generate understandable, reproducible, and manageable data.   Wasn’t that in the constitution somewhere?

You need to demonstrate for yourself, your boss, and your collaborators that you have done the experiments right.   If you can show the results are reproducible, then you will be trusted.  You can and should deliver.  That is your job, maybe a thankless job at times, but a job you want to keep.

In the Internet era where software should be easy and even fun to use, it is nice to see a company that gets it.   CDD Vault has optimized all the complex processing, QC, and data capture from your painstaking experiments.  CDD Vault is flexible in an inflexible world.  When details change or the experiment goes awry, it is nice to have software that allows you to manipulate the data on the fly for each run without forcing you to do repetitive tasks each time.   You can capture the results and the changes, even the nuanced details, like a 2/3 full final plate that is different from all the others in the run.

When there are outliers or even entire bad plates, they are easily identified.   Experimental and data irregularities are gracefully handled, so you and your colleagues can illuminate the real trends.   Now you can separate the wheat from the chaff.  Since CDD is collaborative, even social, all the benefits you get from CDD (security, QC, time saved, trends found) for your own data extends to data from others who wish to share with you.   This of course includes your existing direct collaborators and over 100 public datasets.

Of course CDD provides the workhorse for your lab.   It is intuitive, useful software created with great care and passion.  And via the Help forum, contact with support, and personalized training via GoToMeetings, you can learn from the collective real life experiences that CDD has aggregated from the over 36,000 customer logins/year.

Usually data is an afterthought.   It is refreshing to work with CDD Vault, where clearly folks have obsessed over all these details that are so important when working with data.  As part of the next generation, you can help CDD co-evolve.   As others have done for you, you will leave your mark for others.   Your results are now captured securely for future reference in CDD Vault.   You can point directly to all your hard, important work.    Heck, after publication (or patenting), you or your Vault Administrator might even (with attribution for credit) share your results with the whole scientific community via CDD Public.   GlaxoSmithKline did it for malaria data with their Nature paper.   Maybe you will be next?

Download the entire three part series below: