Über die Autorin bzw. den Autor

Following his PhD thesis in 1983, Stavros Kromidas worked as a sales manager for Waters Chromatography . From 1989 to 2001 he was Managing Director of Novia GmbH, a consultancy company for analytical chemistry, and he has been an independent consultant since then. He has been working in the field of HPLC since 1978 and has given lectures and training courses since 1984. He is the author and co-author of numerous articles and several successful books.

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Alongside developing new ones, the optimization of existing methods is a key task in the HPLC laboratory. And a task that nowadays has to be solved increasingly fast and cost-efficiently. This handbook provides well-founded assistance in better meeting this challenge. Internationally renowned authors cover both the general basics and strategies in optimization, as well as the specific aspects involved in such different methods as RP-HPLC, NP-HPLC, micro- and nano-HPLC, and hyphenated techniques, such as LC/MS. Nor are such topics as column selection and chiral separations left uncovered. Some of the contributions present applications using common optimization software, such as DryLab or ChromSword. All of the chapters concentrate on the essentials and are written in a practically oriented style, while their self-contained structure allows for targeted references. Throughout the text, the authors offer concrete, practical tips as well as pertinent background information, together with insights into the optimization methods of seven major international companies from various sectors. The whole is rounded off with real-life reports from experienced users coming from the different areas of application, in particular the life sciences, such as proteomics or drug development.

Aus dem Klappentext

Alongside developing new ones, the optimization of existing methods is a key task in the HPLC laboratory. And a task that nowadays has to be solved increasingly fast and cost-efficiently.
This handbook provides well-founded assistance in better meeting this challenge. Internationally renowned authors cover both the general basics and strategies in optimization, as well as the specific aspects involved in such different methods as RP-HPLC, NP-HPLC, micro- and nano-HPLC, and hyphenated techniques, such as LC/MS. Nor are such topics as column selection and chiral separations left uncovered. Some of the contributions present applications using common optimization software, such as DryLab or ChromSword. All of the chapters concentrate on the essentials and are written in a practically oriented style, while their self-contained structure allows for targeted references.
Throughout the text, the authors offer concrete, practical tips as well as pertinent background information, together with insights into the optimization methods of seven major international companies from various sectors.
The whole is rounded off with real-life reports from experienced users coming from the different areas of application, in particular the life sciences, such as proteomics or drug development.

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HPLC Made to Measure

John Wiley & Sons

Chapter One

Principles of the Optimization of HPLC Illustrated by RP-Chromatography

Stavros Kromidas

First of all, some questions will be discussed, which should reasonably be answered before beginning method development. Subsequently, we will treat the principal possibilities for improving the resolution in HPLC. It follows a discussion about efficiency and the "right" sequence of such measures for the isocratic and the gradient mode. There is a particular focus on strategies and concepts for developing a method and checking peak homogeneity.

The last section will show ways to achieve other aims than "better separation": "make it faster", "raise sensitivity" or "save money". The chapter ends with a conclusion and an outlook.

1.1.1 Before the First Steps of Optimization

For economic reasons, one really ought to address the following questions prior to commencing the development of a method or the optimization of a given separation. What do I want? In other words, what is the true intention of the separation?

What do I have? That is to say, what relevant information about the analytical purpose and the samples is available?

How should I do it? Do I have all what I need, and is what I want to do really possible?

At first glance, these questions might appear too theoretical or even over-critical. Nevertheless, careful consideration of the actual aims and realistic possibilities for solving an analytical problem would seem to be important at the outset. An early discussion with my boss, a colleague or my client - if you are short, even with yourself - can later prevent a good deal of trouble, time expenditure, and last but not least costs. This time-saving can be considered a good investment.

As regards the first question: "What do I want?"

If it is at all possible, at the outset the following or similar questions should be answered:

Do I need a method for the accurate quantification of this toxic metabolite, or is the aim that the authorities just accept my method?

What is most important in this case: short analysis times, durable columns, robust conditions, or simply optimal specificity?

Must the relative standard deviation [S.sub.rel] be no higher than 2%? What loss of quality would be incurred if [S.sub.rel] were to be 2.5%? Is there actually a correlation between the cost of the analysis and real improvement in the quality of the product?

In other words, is the aim just to meet the requirements in this specific case or is the real "truth" at stake, i.e., are formal aspects or analytical questions in the foreground? This question should be consciously and truthfully answered because of the possible consequences.

How difficult it can be to stand by meaningful and well-considered decisions without being regarded as outlandish or as a troublemaker has been documented elsewhere. Where possible, one should question all aspects. Unconventional questions frequently result in simple solutions.

As regards the second question: "What do I have?"

Information on the sample makes the design of a suitable method easier.

Some examples:

What is written in the report of colleagues from the chemical development department on the light sensitivity and the sorption properties on glass surfaces of a new drug?

Can I contact these colleagues quickly? That is to say, can I get relevant information with a minimum of effort?

There may be information about similar separations in the past, which were not pursued further, in an internal database (which is perhaps rarely updated and even more rarely accessed).

May I quickly calculate the p[K.sub.a] value of the known main component in the sample with appropriate software (see Chapter 1.4)?

Has a colleague in a neighboring department worked in the past with similar compounds and might therefore be able to provide valuable insights?

As far as possible, all means of communication with colleagues should be pursued to gather information. At times it may be helpful not to make this public.

As regards the third question: "How should I do it?"

One should assess the feasibility of the proposed work absolutely unconditionally.

Some examples:

Can I convince my boss that it is useful from the overall company point of view to discuss in advance with the later routine users the design of the method and additional details? If fear of loss of know-how or questions of budget or other psychological and social barriers make impossible de facto a discussion with "the others", it is a bitter reality that one must accept.

On the other hand, is it worth fighting for a change of the following well-known and accepted situation? A deadline is fixed and therefore a validation must be finished in two weeks. Later, the burden of subsequent, substantial costs for a repeat of the measurements, complaints, out-of-spec situations, etc., which inevitably result because an analytical method can hardly be validated within two weeks under real conditions, is not placed on "us" but on quality control, and as testing costs they have been accepted since decades in the absence of overall considerations. The reader may imagine the consequences, or viewed more positively, the possibilities for improvement.

Is it really worthwhile in the case of the development of a routine method, which shall be applied all over the world, to opt for a polar RP-phase because of the frequently observed higher selectivity, even if one has to expect problems with the charge-to-charge reproducibility? Might a hydrophobic, more rugged column with a lower but still sufficient selectivity the better choice?

Is it useful to demonstrate my analytical "knowledge" by further trimming the relative standard deviation of a method being used in diverse plant laboratories to a value of 0.7%?

Realities - and opinions are also realities - which determine the success or failure of an analytical activity should, wherever possible, influence the design of the method. It is useful if the number of meetings can be reduced to "a cup of coffee" or "lunch often together". The point is to improve the communication and this can turn out to be easier in a less formal situation.

In conclusion, two basic preconditions for successful method development may be noted:

1. Expert knowledge exists or can be loaned or sold.

2. The analytical possibilities correspond with the requirements, and it is possible to talk about them.

In the author's opinion, a clear definition of requirements, unequivocally formulated, understandable goals for all involved persons, shortcuts to information, and a critical estimation of possibilities/risks are more important, not only in analytics, than obtaining exemplary results such as low detection limit, correlation factors around 0.999, [S.sub.rel] smaller than 1%, or 30% less expensive equipment.

1.1.2 What Exactly Do We Mean By "Optimization"?

Optimization of a separation is principally directed by the following goals:

to separate better (higher resolution),

to separate faster (shorter retention time),

to see more (lower detection limit),

to separate at lower cost (economic effort),

to separate more (higher throughput)....