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. 2023 Mar;16(3):467-477.
doi: 10.1111/cts.13458. Epub 2022 Nov 23.

Using an animal model to predict the effective human dose for oral multiple sclerosis drugs

Wei Liu  1   2 , Zhiheng Yu  1   2 , Ziyu Wang  1   3 , Emmanuelle L Waubant  4 , Suodi Zhai  1 , Leslie Z Benet  1   2
Affiliations

Using an animal model to predict the effective human dose for oral multiple sclerosis drugs

Wei Liu et al. Clin Transl Sci. 2023 Mar.

Abstract

The objective of this study was to determine the potential usefulness of an animal model to predict the appropriate dose of newly developed drugs for treating relapsing remitting multiple sclerosis (RRMS). Conversion of the lowest effective dose (LEffD) for mice and rats in the experimental autoimmune encephalomyelitis (EAE) model was used to predict the human effective dose utilizing the body surface area correction factor found in the 2005 US Food and Drug Administration (FDA) Guidance for Industry in selecting safe starting doses for clinical trials. Predictions were also tested by comparison with doses estimated by scaling up the LEffD in the model by the human to animal clearance ratio. Although initial proof-of-concept studies of oral fingolimod tested the efficacy and safety of 1.25 and 5 mg in treating RRMS, the EAE animal model predicted the approved dose of this drug, 0.5 mg daily. This approach would have also provided useful predictions of the approved human oral doses for cladribine, dimethyl fumarate, ozanimod, ponesimod, siponimod, and teriflunomide, drugs developed with more than one supposed mechanism of action. The procedure was not useful for i.v. dosed drugs, including monoclonal antibodies. We maintain that drug development scientists should always examine a simple allometric method to predict the therapeutic effective dose in humans. Then, following clinical studies, we believe that the animal model might be expected to yield useful predictions of other drugs developed to treat the same condition. The methodology may not always be predictive, but the approach is so simple it should be investigated.

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Conflict of interest statement

Dr. Benet first became aware of the success of the methodology reported here while serving as an expert witness in a lawsuit concerning the validity of the fingolimod patent. All other authors declared no competing interests for this work.

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