Figures
The ORCID iD is missing for the corresponding author. The publisher apologizes for the error. Author Marcus A. Horwitz’s ORCID iD is: 0000-0001-6525-7147 (https://orcid.org/0000-0001-6525-7147).
In Table 2, Prothionamide was mistakenly abbreviated “PRS” instead of “PRO” in the second column, “Screening Test”. Please see the corrected Table 2 here.
On the right side of Fig 1, Group O was mistakenly omitted from the alphabetical list of drug regimen definitions. Please see the corrected Fig 1 here.
M. tuberculosis infected mice were sham treated (Treatment Group A) or treated with the Standard Regimen (Treatment Group B), PRS Regimen II (Treatment Group C) or one of the top 4-drug combinations (Treatment Groups D-Q) identified from macrophage screening using the PRS platform starting from a pool of 15 TB drugs 5 days per week for 3 weeks. Three days after the last treatment, mice were euthanized to determine bacterial number in the lung. Standard Regimen is comprised of INH, RIF, EMB and PZA at 25, 10, 100 and 150 mg/kg, respectively. PRS Regimen II is comprised of CFZ, BDQ, PZA and EMB at 25, 30, 450 and 100 mg/kg, respectively. Drug doses used in the top 4-drug experimental regimens are as follows: 200–50 mg/kg for AC, 30 mg/kg for BDQ, 25 mg/kg for CFZ, 2.5 mg/kg for DLM, 100 mg/kg for PA824, 450 mg/kg for PZA, 10 mg/kg for RPT and 25 mg/kg for SQ109.
Reference
- 1. Clemens DL, Lee B-Y, Silva A, Dillon BJ, Masleša-Galić S, Nava S, et al. (2019) Artificial intelligence enabled parabolic response surface platform identifies ultra-rapid near-universal TB drug treatment regimens comprising approved drugs. PLoS ONE 14(5): e0215607. https://doi.org/10.1371/journal.pone.0215607 pmid:31075149
Citation: The PLOS ONE Staff (2019) Correction: Artificial intelligence enabled parabolic response surface platform identifies ultra-rapid near-universal TB drug treatment regimens comprising approved drugs. PLoS ONE 14(5): e0217670. https://doi.org/10.1371/journal.pone.0217670
Published: May 30, 2019
Copyright: © 2019 The PLOS ONE Staff. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.