4.7 Article

Supporting Drug Development for Neglected Tropical Diseases Using Mathematical Modeling

Journal

CLINICAL INFECTIOUS DISEASES
Volume 73, Issue 6, Pages E1391-E1396

Publisher

OXFORD UNIV PRESS INC
DOI: 10.1093/cid/ciab350

Keywords

drug development; neglected tropical diseases; mathematical modeling; filariases; onchocerciasis

Funding

  1. Drugs for Neglected Diseases initiative (DNDi)
  2. NTD Modelling Consortium by the Bill and Melinda Gates Foundation [OPP 1184344]
  3. Medical Research Council (MRC) under the MRC/DFID Concordat agreement [MR/R015600/1]
  4. UK Department for International Development (DFID) under the MRC/DFID Concordat agreement [MR/R015600/1]
  5. European and Developing Countries Partnership for Clinical Trials (EDCTP2) program - European Union
  6. Doctoral Training Program studentship of the UK MRC
  7. MRC [MR/R015600/1] Funding Source: UKRI

Ask authors/readers for more resources

Drug-based interventions are crucial in addressing major diseases, with a growing consensus on the need for new therapeutic options in some cases. In this field, minimizing wastage of money and resources is essential.
Drug-based interventions are at the heart of global efforts to reach elimination as a public health problem (trachoma, soil-transmitted helminthiases, schistosomiasis, lymphatic filariasis) or elimination of transmission (onchocerciasis) for 5 of the most prevalent neglected tropical diseases tackled via the World Health Organization preventive chemotherapy strategy. While for some of these diseases there is optimism that currently available drugs will be sufficient to achieve the proposed elimination goals, for others-particularly onchocerciasis-there is a growing consensus that novel therapeutic options will be needed. Since in this area no high return of investment is possible, minimizing wasted money and resources is essential. Here, we use illustrative results to show how mathematical modeling can guide the drug development pathway, yielding resource-saving and efficiency payoffs, from the refinement of target product profiles and intended context of use to the design of clinical trials.

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