What is Indication Extrapolation and Should it be Allowed with Biological Medications?

September 23, 2014

By David Charles, M.D. and Mary Ann Chapman, Ph.D.

If a prescription medication is approved for the treatment of a specific disease or condition, do you assume that it has undergone full testing for that condition? Tis assumption is usually valid: New medications approved in the United States must undergo extensive testing for the conditions they are approved to treat, which then, if approved by the FDA, become known as indications for that drug. However, shortcuts do exist for generic drugs—conventional medications with exactly the same chemical composition as the original innovator drug. Because drugs such as generic aspirin and ibuprofen are chemically identical to the innovator brand drugs, it is assumed that they will act the same way as the brand drugs in all diseases and conditions. Consequently, generic drugs require only basic testing in healthy volunteers before being approved by the FDA for all indications of the original brand drug.

But this logical assumption doesn’t apply to biological medications—those made by living organisms or cells. Unlike generic drugs, biological medications or biologics cannot be exact copies of one another. As a result, follow-on biologics designed to be similar to already-approved innovator medications are known as biosimilars—not generics. Policymakers are currently considering to what extent biosimilars should be tested in patients with different diseases or whether they should be automatically approved for all of the innovator biologics’ indications, an alternative process known as indication extrapolation.

Given that biosimilars cannot be exact copies of the original innovator biological medications, they may not act the same way in every disease state, possibly triggering unforeseen adverse effects. For this reason, indication extrapolation should not be automatic for biosimilars. Instead, each biosimilar should be considered on a case by case basis to determine the extent of evidence required for patients with different diseases.

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