In a series of posts, we are going to talk about method validation.

1. Part 1: Introduction-Is it valid, invalid or non-validated?
2. Part 2: What is method validation?
3. Part 3: Can we use some­one else’s val­i­dated method?
4. Part 4: What trig­gers ver­i­fi­ca­tion, re-validation or out right new val­i­da­tion of a method?
5. Part 5: What are the essen­tial terms in method validation?
6. Part 6: What is qual­ity assur­ance and qual­ity control?

From time to time all instru­ments have error. This is just a fact of ana­lyt­i­cal test­ing. Machines break down, main­te­nance is needed, changes in the con­fig­u­ra­tion of the machines, soft­ware upgrades and the like are not infre­quent occur­rences. The ques­tion becomes when do we need to start from scratch and when do we sim­ply need to ver­ify the validation.

There are events that trig­ger ver­i­fi­ca­tion of the method, re-validation of the method, and even com­pletely new method val­i­da­tion studies.

Accord­ing to Huber, ana­lyt­i­cal meth­ods need to be val­i­dated or re-validated

1. before their intro­duc­tion into rou­tine use;
2. when­ever the con­di­tions change for which the method has been val­i­dated (e.g., an instru­ment with dif­fer­ent char­ac­ter­is­tics or sam­ples with a dif­fer­ent matrix); and
3. when­ever the method is changed and the change is out­side the orig­i­nal scope of the method.

A real life exam­ple of this would be when we switch from one oper­at­ing sys­tem to another. We will need to con­duct a full scale val­i­da­tion study from scratch. If we change the chro­mato­graphic con­di­tions of the oven, for exam­ple, in GC-FID work, then we would need to val­i­date the entire method anew. If we switch from sam­pling and test­ing urine to that of whole blood, we need to val­i­date from scratch. If we change a con­sum­able such as a col­umn or an inlet liner, we need to re-validate (robust ver­i­fi­ca­tion) before its employed sam­pling the unknowns again. If we re-calibrate our pipettes, then re-validation (robust ver­i­fi­ca­tion) is required. If we do some­thing minor, such as change the in the report that is gen­er­ated that the acqui­si­tion num­ber fol­lows the subject’s name instead of vice versa, then we do not need to val­i­date anew or re-validate at all. In essence, when in doubt, val­i­date anew.

The data from the method val­i­da­tion should be “clean” and it should rep­re­sent the most per­fect appli­ca­tion of the method pos­si­ble in that par­tic­u­lar envi­ron­ment on that par­tic­u­lar instru­men­ta­tion under those set conditions.

As a log­i­cal result, if we see errors in the data in the val­i­da­tion efforts, then we can­not trust that when unknowns are sam­pled and tested later that the results will be error free.

We have to really scru­ti­nize the under­ly­ing data in the val­i­da­tion study to deter­mine fairly and objec­tively whether or not the data sup­ports the con­tention that the method is indeed valid, mean­ing that it is suit­able for its intended pur­pose or whether it is just sim­ply someone’s opin­ion with no data to sup­port it.