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    The data gathering exercise results in quantitative data in abundance. How you want to analyze it depends broadly on your plan to arrive at the solution. Neverthel
    According to USFDA, a combination product is one composed of any combination of a drug and device; biological product and device; drug and biological product
    ess, it depends on three fundamental questions. But as a precursor to these questions, one must keep in mind that the larger purpose of using wide ranging interact
    ; or drug, device, and biological product and fixed dose combination would include two or more combinations of drug.

    Examples of combination products may in
    ing data is to understand the processes, problems and the best possible solutions as applied to Six Sigma implementation.

    Six Sigma: Statistical Thinking

    Statist
    lude drug-coated devices, drugs packaged with delivery devices in medical kits, and drugs and devices packaged separately but intended to be used together.

    ical thinking involves the tendency to want to study the complete contextual situation when a wide ranging statistical inputs and control factors of several nature
    here is enormous increase in the number of combination products entering the market in the recent years. Combination products have proven advantages but fixe
    s may be interacting simultaneously to produce a particular output.

    To understand the principle better, one can begin with the one factor at a time (OFAT) theory,
    d dose combinations are still in the process of convincing regulatory authority on their advantages over the single ingredient formulations.

    Combination pro
    which refers to the natural tendency of the investigator to change only one factor at a time and ‘record’ the results until all other factors are tested this way.
    ucts have become life saving products for the pharmaceutical companies who doesn’t have many innovative molecules in their product pipeline and have been inc
    The results need to be put in place in the natural logical manner that would have occurred had the study been conducted in the opposite of OFAT.

    The Fundamental
    easingly used in the product life cycle management. Even the companies having product patents are trying to extend their product life cycle through the combi
    Question

    As we discussed earlier, there are three fundamental questions that need to be addressed in the order that the data is analyzed.

    1. Whether the level of
    nation products and maximize the revenues. But the companies involved in this practice are overlooking that they are burdening the patients both economically
    the measurement of the variables is known? If yes;

    a. Nominal or Crude Ordinal

    b. Good Ordinal or Interval or Ratio

    2. Size of the sample is another considerat
    and physically. They need to rightly judge the benefits of the combination products and they have to even look at the risks involved when combining the produ
    ion. What kinds and how many of them are being considered?

    a. One sample only

    b. Two samples; Specify either dependent or independent

    c. Multiple samples; Speci
    ts. Some of the combination products were well accepted by physicians while others suffered. Companies involved in development of combination products are fi
    fy either dependent or independent

    3. What are my anticipations about the statements on data that I will be able to make?

    a. Define the sample data but without
    ding difficulty in defining their combination products and facing various challenges from selecting a combination to marketing it.

    Following aspects would a
    generalizing to the larger batch size

    i. Discuss each factor such as distribution, central tendency and variation in the context of a single variable.

    ii. Discu
    dd to the challenges in developing combination products:

    Which markets to tap where the combination products can do fairly well?
    Which combination prod
    ss the relationship between two or more variables if that is the case.

    b. Now, moving away a bit, generalize the samples to the batch size from which they were dr
    cts are meaningful and rational?
    Which therapeutic categories to select?
    Which Combinations can address unmet needs of the patients?
    Do combin
    awn. The process of statistical inference or hypothesis testing, as this is called, relies on the probability theory to determine the risk of an inaccurate genera
    tions increase the patient compliance?
    What would be the developing cost?
    How to tackle the risks encountered during combination product developmen
    lization.

    i. For a single variable, discuss the various factors in the same way as in the above case.

    ii. For two or more samples discuss the differences betwe
    t?

    As combination products don't fit into the traditional categories of drugs, medical devices, or biological products, the USFDA is in the process of devel
    en them concerning whether they are independent or dependent?

    iii. Relationship between two variables and again the relationship shared between more variables.

    I
    ping new procedures for reviewing their safety, efficacy and quality.

    Professional from academic institutions, pharmaceutical industries, health care indust
    n continuance with the discussion, the choice for adopting the appropriate statistical technique and going ahead with the task on hand rests with the answers to th
    y and representatives from various regulatory agencies are working out to design the regulatory requirements for manufacture and sale of combination products
    e above questions. Nevertheless, the philosophy of effective statistical thinking and action on a further course is better based on the following guiding principle
    .

    As there is an increasing trend of the combination products companies manufacturing such products should be able to tackle the problems involved in the de
    s:

    1. In a system all reactions occur in interconnected processes

    2. Variation is part and parcel of all processes

    3. The key to success lies in understanding a
    elopment. They need to be wiser in analyzing the market trends and the regulatory requirements.

    Companies that provide selfless information through particip
    nd reducing variations

    Statistical thinking succeeds in paving the way for a holistic approach to the deployment of Six Sigma. It can’t be thought of in isolation


    tion in industry events and feedback to regulatory authorities would be able to face the challenges and will be successful in developing combination products

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