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The implications of model–informed drug discovery and development for tuberculosis

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Gillespie_2016_DDT_Model_informedDrugDiscovery_AM.pdf (160.9Kb)
Date
03/2017
Author
Muliaditan, Morris
Davies, Geraint R.
Simonsson, Ulrika S. H.
Gillespie, Stephen H.
Pasqua, Oscar Della
Keywords
PKPD
Tuberculosis
Drug development
Modelling and simulation
RA0421 Public health. Hygiene. Preventive Medicine
T-NDAS
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Abstract
Despite promising advances in the field and highly effective first-line treatment, an estimated 9.6 million people are still infected with tuberculosis (TB). Innovative methods are required to effectively transition the growing number of compounds into novel combination regimens. However, progression of compounds into patients occurs despite the lack of clear understanding of the pharmacokinetic-pharmacodynamic (PK/PD) relations. The PreDiCT-TB consortium was established in response to the existing gaps in TB drug development. The aim of the consortium is to develop new preclinical tools in concert with an in silico model-based approach, grounded in PKPD principles. Here, we highlight the potential impact of such an integrated framework on various stages in TB drug development and on the dose rationale for drug combinations.
Citation
Muliaditan , M , Davies , G R , Simonsson , U S H , Gillespie , S H & Pasqua , O D 2017 , ' The implications of model–informed drug discovery and development for tuberculosis ' , Drug Discovery Today , vol. 22 , no. 3 , pp. 481-486 . https://doi.org/10.1016/j.drudis.2016.09.004
Publication
Drug Discovery Today
Status
Peer reviewed
DOI
https://doi.org/10.1016/j.drudis.2016.09.004
ISSN
1359-6446
Type
Journal article
Rights
© 2016, Elsevier. This work is made available online in accordance with the publisher’s policies. This is the author created, accepted version manuscript following peer review and may differ slightly from the final published version. The final published version of this work is available at www.sciencedirect.com / https://dx.doi.org/10.1016/j.drudis.2016.09.004
Description
The research leading to these results received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement n°115337, the resources of which comprise financial contributions from the European Union's Seventh Framework Programme (FP7/2007-2013) and EFPIA companies’ in kind contribution.
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  • University of St Andrews Research
URL
http://www.sciencedirect.com/science/article/pii/S1359644616303245#appd002
URI
http://hdl.handle.net/10023/11755

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