Prediction of antibiotic resistance: time for a new preclinical paradigm?

• Published in: Nature reviews. Microbiology Vol. 15; no. 11; pp. 689 - 696
• Main Authors: Sommer, Morten O. A., Munck, Christian, Toft-Kehler, Rasmus Vendler, Andersson, Dan I.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 01-11-2017; Nature Publishing Group
• Subjects: 631/326/1762; 631/326/22/1290; 631/326/22/1434; 631/326/2565/107; 631/326/325/2482; 631/326/41/1969/2038; 631/326/41/2529; Analysis; Anti-Bacterial Agents - pharmacology; Antibiotic resistance; Antibiotics; Bacteria; Bacteria - drug effects; Bacteria - genetics; Bacterial infections; Causes of; Complications and side effects; Diagnosis; Dosage and administration; Drug development; Drug Evaluation, Preclinical; Drug resistance; Drug Resistance, Multiple, Bacterial - genetics; Drug therapy; Evolution, Molecular; Fitness; Gene transfer; Gene Transfer, Horizontal; Health aspects; Host-Pathogen Interactions; Humans; Infectious Diseases; Life Sciences; Medical Microbiology; Microbial drug resistance; Microbiology; opinion-2; Parasitology; Predictions; Reproductive fitness; Risk assessment; Virology; Denmark; Sweden
• ISSN: 1740-1526; 1740-1534; 1740-1534
• DOI: 10.1038/nrmicro.2017.75

Risk assessment for the development of antibiotic resistance against a new drug candidate is of paramount importance in preclinical development. In this Opinion article, Sommer
et al
. propose a new preclinical paradigm for the prediction of antibiotic resistance.
Predicting the future is difficult, especially for evolutionary processes that are influenced by numerous unknown factors. Still, this is what is required of drug developers when they assess the risk of resistance arising against a new antibiotic candidate during preclinical development. In this Opinion article, we argue that the traditional procedures that are used for the prediction of antibiotic resistance today could be markedly improved by including a broader analysis of bacterial fitness, infection dynamics, horizontal gene transfer and other factors. This will lead to more informed preclinical decisions for continuing or discontinuing the development of drug candidates.