Why Do We Test On Healthy Volunteers?
Bioequivalence guidelines state that, in general, bioequivalence and bioavailability studies should be conducted preferentially from a healthy volunteer population unless the drug carries safety concerns that make this unethical.
It is with this guidance in mind that, and the fact that these nontherapeutic studies are without any direct benefit to the participants, which makes them so critical to the drug development process; and indeed why choosing the right testing provider who understands the complexities of conducting them is so vital.
In such studies, which are conducted as a part of regulatory requirements to establish that a generic drug is equivalent to the innovator drugs, requirements outline that the population should be selected with the aim of permitting the detection of differences between pharmaceutical products. In order to reduce variability not related to differences between products, the studies should be performed in the most homogenous group possible.
This in-vivo healthy volunteers model is regarded in most instances to detect formulation differences and to therefore allow the extrapolation of the results to populations for which the reference medicinal product is actually approved – the elderly, children, patients with liver impairment, etc.
In further detail, it is set out that subjects should be 18 years of age or older and preferably have a Body Mass Index between 18.5 and 30 kg/m2. They should also be screened for suitability by means of clinical laboratory tests, a medical history, and a physical examination, and depending on the drug’s therapeutic class and safety profile, special medical investigations and precautions may have to be carried out before, during, and after the completion of the study. All of which should be clearly stated in the inclusion/exclusion criteria within the testing protocol.
With a massive database of qualified and experienced volunteers, QUINTA-ANALYTICA are experts in this field and are able to recruit very specific population types. They can filter their extensive lists to include just one sex, different age ranges or specific laboratory results, and visa versa, may exclude subjects based on specific requirements in EKG, genotype, etc.
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