Are Clinical Trials Always Necessary?

The science of pharmacometrics is changing the way some therapeutic recommendations are expedited around the world.

By Jagdev Sidhu, PhD and Michael Tortorici, PhD

At CSL Behring, we have a keen understanding of the difference that accelerated access to vital therapies as well as therapeutic recommendations can mean for patients with rare and serious medical disorders.

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Pharmacometrics offers an exciting alternative to traditional clinical trials in certain instances by allowing the approval of more flexible usage of therapeutic products without a clinical trial. For the majority of patients with a rare disease who are on chronic therapies, this is good news indeed.

The approval of medicines and their therapeutic options takes place in a rigorous and uncompromising regulatory environment in which the wellbeing of patients is the main priority. At the same time, regulators around the world are increasingly engaging with the pharmaceutical companies to advance methodologies, such as the use of pharmacometrics that bring innovation to the drug development process.

Pharmacometrics is employed in model-based drug development using mathematical and statistical models to examine data from one or multiple trials…

Pharmacometrics is employed in model-based drug development (MBDD) using mathematical and statistical models to examine data from one or multiple trials, quantifying a medication’s time-course in the body as well as its clinical effects. Accordingly, this methodology can be applied to develop customized dosing based on individual patient needs. Flexible dosing recommendations for patients with a chronic disorder can be hugely beneficial with regard to patient acceptability and compliance.

Over the last two decades, pharmacometrics has increasingly been used in MBDD. It often uses pharmacokinetic (how the body processes a drug) data, and views it across populations to examine variability and develop conclusions about how certain drugs and their treatment regimens will behave in the population.

The role of pharmacometrics ranges from defining the doses of therapies taken into humans for the first time and helping define the design and interpretations of clinical trials, to being a cornerstone of dosing recommendations on a product’s prescribing information.

CSL Behring applied pharmacometrics in the protein therapeutics field to expedite new dosing recommendations for one of our immunoglobulin therapies.

CSL Behring applied pharmacometrics in the protein therapeutics field to expedite new dosing recommendations for one of our immunoglobulin therapies. In doing so, the conduct of a clinical trial program, which ordinarily would have been undertaken for the new dosing scheme, was avoided, thus expediting the new dosing recommendations to patients and their prescribers by a couple of years.

Within the patient and prescribing community, questions were frequently posed about the consequences of dosing the product in ways different from the label recommendations. The questions included whether to dose more or less of the product more or less frequently. Traditionally, a clinical trial program would have been conducted to investigate these questions and gain approval from global regulators to amend prescribing recommendations.

However, acknowledging that this task would have been unwieldy, lengthy and costly, CSL set about a different course. With a large amount of historical data available from the product’s clinical trial program, an extensive pharmacometrics exercise was undertaken to simulate and predict the outcomes of the various dosing scenarios posed.

…a wide range of patients now have the ability to individually tailor their usage of the product based on regulator-approved labelling recommendations.

This was closely joined with clinical rationales that the product’s efficacy and safety would remain uncompromised. The outcome was that regulator acceptance was obtained in several jurisdictions for a range of flexible dosing scenarios without conducting any clinical trial. Consequently, in a significantly expedited manner, a wide range of patients now have the ability to individually tailor their usage of the product based on regulator-approved labelling recommendations.

Through the application of pharmacometrics, considering the question whether a clinical trial is necessary has become a frequent practice, as research teams at CSL consider their strategies to provide insights to or recommendations on the use of vital medicines.

Authors

Dr. Jagdev Sidhu is CSL Behring’s Senior Director of Clinical Pharmacology & Early Development and Dr. Michael Tortorici is Director of Clinical Pharmacology.

2 thoughts on Are Clinical Trials Always Necessary?

  1. Thanks very much for sharing this exciting trend. The benefits are obvious and tremendous. I am amazed that CSL has already taken a significant stride with regulatory approval. I understand that with previous results a model could be extrapolated and trained. How good is the model’s predicting power? Could you please share a link to yours or others’ cases? Many thanks.

    Kind regards
    Xinyu

    • Xinyu, thank you for your feedback regarding pharmacometrics. According to Drs. Sidhu and Tortorici, the predictive power of any model is, unsurprisingly, predicated on the ‘experience’ in the model, i.e., the data on which the model was built. They go on to point out that caution should always be exercised with the issue of prediction vs. extrapolation. Prediction within the model’s ‘experience’ is no doubt more robust and reliable than extrapolation too far beyond the model’s training. This, of course, has to be considered in the context of how a pharmacometrics exercise is being deployed in a drug development program – e.g., regulatory approval, protocol dose selection or to guide internal program decision making.

      In the MBDD example with our immunoglobulin (Ig), which Drs. Jagdev and Tortorici cited in the post, the predictions for the alternate dosing regimens were for Ig dosing within the extent of the clinical Ig experience (in terms of total doses and systemic Ig levels) that had existed, which was an important aspect of the regulatory approval. Extrapolating or predicting too far beyond that clinical experience might be useful as a guide to what might be expected clinically, though it would make regulatory approval very difficult.

      We will send you literature references to similar cases as mentioned in BioBlog in an email.

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