Discovery of Efficacious Pseudomonas aeruginosa-Targeted

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Discovery of Efficacious Pseudomonas aeruginosa-Targeted SiderophoreConjugated Monocarbams by Application of a Semi-Mechanistic PK/PD Model Kerry E Murphy-Benenato, Pratik R. Bhagunde, April Chen, Hajnalka E Davis, Thomas F. Durand-Reville, David E Ehmann, Vince Galullo, Jennifer J. Harris, Holio HatoumMokdad, Haris Jahic, Aryun Kim, M R Manjunatha, Erika L. Manyak, John Mueller, Sara Patey, Olga Quiroga, Michael Rooney, Li Sha, Adam B. Shapiro, Mark Sylvester, Beesan Tan, Andy S Tsai, Maria Uria-Nickelsen, Ye Wu, Mark zambrowski, and Shannon X. Zhao J. Med. Chem., Just Accepted Manuscript • DOI: 10.1021/jm501506f • Publication Date (Web): 06 Feb 2015 Downloaded from http://pubs.acs.org on February 12, 2015

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Journal of Medicinal Chemistry

Discovery of Efficacious Pseudomonas aeruginosa-Targeted Siderophore-Conjugated Monocarbams by Application of a Semi-Mechanistic PK/PD Model

Kerry E. Murphy-Benenato,‡a* Pratik R. Bhagunde,‡b April Chen, Hajnalka E. Davis,‡ Thomas F. Durand-Réville,‡ David E. Ehmann,‡ Vincent Galullo,‡ Jennifer J. Harris,‡c Holia Hatoum-Mokdad,‡ Haris Jahić,‡ Aryun Kim,‡* M.R. Manjunatha,† Erika L. Manyak,ǁd John Mueller,‡ Sara Patey,‡ Olga Quiroga,‡ Michael Rooney,‡ Li Sha,‡ Adam B. Shapiro,‡ Mark Sylvester,‡ Beesan Tan,‡e Andy S. Tsai,‡f Maria Uria-Nickelsen,‡e Ye Wu,‡ Mark Zambrowski,‡g Shannon X. Zhao‡

‡

Infection Innovative Medicines, AstraZeneca R&D Boston, 35 Gatehouse Drive, Waltham,

Massachusetts 02451, USA †

Infection Innovative Medicines, AstraZeneca India Pvt. Ltd., Bellary Road, Bangalore

560024, India ǁ

Discovery Sciences, AstraZeneca R&D Boston, 35 Gatehouse Drive, Waltham,

Massachusetts 02451, USA

Abstract: In order to identify new agents for the treatment of multi-drug resistant Pseudomonas aeruginosa, we focused on siderophore-conjugated monocarbams. This class of monocyclic β-lactams is stable to metallo-β-lactamases and have excellent P. aeruginosa activities due to their ability to exploit the iron uptake machinery of Gram-negative bacteria. Our medicinal chemistry plan focused on identifying a molecule with optimal potency and physical properties and activity for in vivo efficacy. Modifications to the monocarbam linker, siderophore, and oxime portion of the molecules were examined. Through these efforts a

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series of pyrrolidinone-based monocarbams with good P. aeruginosa cellular activity (P. aeruginosa MIC90 = 2 µg/ml), free fraction levels (> 20 % free) and hydrolytic stability (t1/2 ≥ 100 h) were identified. In order to differentiate the lead compounds and enable prioritization for in vivo studies, we applied a mechanistic PK/PD model to enable prediction of in vivo efficacy from in vitro data. Introduction The need for treatment options for multi-drug resistant Gram-negative bacteria, especially Pseudomonas aeruginosa (P. aeruginosa) is becoming critical due to the constant evolution of resistance.1-3 Strategies to combat this issue are to develop new anti-infectives that have novel targets, therefore eliminating the concern for cross-resistance to other known agents, or optimize current chemotypes that address the known mechanisms of resistance. Nevertheless, the clinical pipeline for agents targeting Gram-negative bacteria is thin, with the carbapenems being the last novel chemotype to be introduced.4, 5 Despite their long history of use, β-lactam antibiotics offer a unique opportunity for the development of new Gram-negative agents.6 They are a clinically validated class of antibiotics with an improved safety profile as compared to other agents.7 Their targets, the penicillin-binding proteins (PBPs), are located in the periplasm, eliminating the need to traverse both cell membranes of the Gram-negative bacterium. Specifically, β-lactams’ target the high molecular weight PBPs which are responsible for the transpeptidation reaction in the synthesis of the bacterium peptidoglycan layer, a key component of all bacterium cell wall architectures. β-Lactams work by forming a stable acyl-enzyme complex with the active site serine of the PBPs. The target PBPs varies depending on the chemotype.8-10 Due to the wide-spread use of β-lactam antibiotics, most modes of resistance to current therapies are well-understood, enabling design efforts to combat them.11 In addition, for clinically used β-lactams there are well established pharmacokinetic/pharmacodynamic


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(PK/PD) relationships.12 Indeed, the successful development of new carbapenems, fourth generation cephalosporins and novel β-lactamase inhibitors leads one to believe there is potential for success in this area.13-15 Two of the largest threats to the effectiveness of P. aeruginosa-targeted βlactam antibiotics are inability to access the periplasmic space due to porin mutations and hydrolysis by β-lactamases.10, 16 One of the largest current clinical threats is the rise of panresistant metallo-β-lactamases in Gram-negative bacteria since there are no known inhibitors of this class of β-lactamases.17-19 Reports in the literature have highlighted a class of PBP3 selective inhibitors that address these issues due to a novel mode of penetration and a core structure that is stable to metallo-β-lactamases: siderophore-conjugated monocarbams (Figure 1).21-23 Originally reported in the mid-1980’s, these compounds, exemplified by 2 (Pirazmonam)21 and 3 (MC-1)23, have two key features which provide them with their unique activity: a monocyclic-β-lactam core which renders them stable to metallo-β-lactamases24, 25 and an iron-chelating moiety which is responsible for cellular uptake.26-28

Figure 1. Monocyclic β-lactams



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Bacteria require iron as a nutrient for survival in the host.29 In order to acquire this essential mineral, pathogens have evolved a number of strategies to sequester iron, including siderophore production.30 Siderophores are small chelating molecules secreted by bacteria, for the purpose of acquiring iron from the host and the environment. P. aeruginosa, like most Gram-negative pathogens, secretes multiple siderophores, each with a dedicated outer membrane receptor to allow import and eventual intracellular release.31 Compounds 2 and 3 (Figure 1) incorporate a 3-hydroxypyridinone moiety that mimics the bacteria’s natural siderophores and hijacks its iron uptake machinery for penetration into the periplasm.32, 33 This results in excellent in vitro potency against P. aeruginosa for this class (2 and 4, Table 1) and a clear improvement over the monocyclic β-lactam 1 (Aztreonam), (Figure 1).34 Comparison of the acylation rate constants for 1and compounds 2 and 4 for their PBP3 target reveals the enhanced P. aeruginosa susceptibility for siderophore conjugates is not related to target affinity and is likely due to better outer membrane permeability.35 Aspects for optimization of these compounds are the poor hydrolytic stability of 2 (t1/2 < 50 h) and the low free fraction of 4 (4% free). McPherson et. al. demonstrated that monocarbam 3, enters P. aeruginosa via the catechol siderophore receptors PiuA and PirA.36 Furthermore, they reported 3 is stable to a broad spectrum of serine and metallo-β-lactamases, and is not affected by porin deletions or over-expression of efflux pumps. They also concluded the first step resistance mutation to monocarbam 3, knockout of the siderophore receptor PiuA, is not relevant in vivo. However, a recent report by Tomaras et. al. on a related siderophore-conjugated monobactam MB-1 described adaptive resistance.37 In this report they described an in vitro assay which was predictive of the observed in vivo results however this assay has only been shown to be predictive for a single compound and no data to support its applicability to the monocarbam class has been reported. Therefore additional in vivo experiments will be required to


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establish a strong in vitro to in vivo correlation aimed at enabling the development of siderophore containing β-lactams. Recognizing successful progression for this project would require extensive in vivo experimentation, we anticipated that informed decisions on the selection of compounds for in vivo experiments would require quantitative PK/PD modeling. Thus, our program had two main goals: (1) identify monocarbam compounds with optimal physical properties (i.e., high free fraction and good hydrolytic stability) for in vivo efficacy, and (2) develop a semimechanistic PK/PD model to enable prediction of in vivo efficacy.38 The PK/PD relationship of β-lactam antibiotics are well described, and free time above MIC has been shown to be the driver for all classes of β-lactams.39 The previously mentioned lack of correlation between P. aeruginosa PBP target affinity and cellular activity led us to take a non-structure based drug design approach. Instead, we focused on chemical modifications aimed at optimizing the plasma protein binding (PPB) and clearance (CL) since free drug exposure is the key factor for efficacy for this class of compounds.40 Through our medicinal chemistry optimization we identified a series of pyrrolidinone-based monocarbams which demonstrated an unprecedented balance in their P. aeruginosa activity, hydrolytic stability, PPB and CL. Through our studies we developed the structure activity relationships (SAR) around permeation, efflux and target engagement. After establishing the in vitro activity of the series, we then applied a mechanistic PK/PD model which allows prediction of in vivo efficacy from in vitro kill kinetics and therefore prioritization of in vivo experiments aimed at identifying potential clinical candidates. Chemistry The synthesis of the siderophore-conjugated monocarbams utilized one of two general synthetic schemes: (1) monocarbam formation with desired heterocycle followed by introduction of the siderophore piece (Scheme 1), or (2) coupling of the siderophore to the



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desired heterocycle, followed by monocarbam formation (Scheme 2). Two representative examples are depicted here. As can be seen in Scheme 1, coupling of known aminothiazole β-lactam 541, 42 with unfunctionalized heterocycles (e.g., 6) under traditional monocarbam formation conditions,22, 23 followed by azide reduction provided coupling partner 7. Amide formation and two-step deprotection afforded the target compound 9. Alternatively, coupling of a protected siderophore (e.g., 8)27 to the target heterocycle (10), followed by monocarbam formation and deprotection steps, provided fully elaborated monocarbams 13. The key challenge in accessing the monocarbams was purification and isolation of intermediates and final compounds due to their instability and polar nature. Synthetic details for all monocarbams can be found in the supporting information. Scheme 1. Example of general route 1 for the synthesis of siderophore-conjugated monocarbams

(a) (i) MSTFA, THF; (ii) CSI, DCM, 0 °C; (iii) THF, 0 °C – rt, 66%; (b) H2, 10 mol % Pd/C, EtOH; (c) HATU, i-Pr2EtN, DMF; (d) H2, Pd black, MeOH; (e) TFA, DCM, 0 °C, 17% over four steps

Scheme 2. Example of general route 2 for the synthesis of siderophore-conjugated monocarbams


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(a) 8, EDCI, HOBT, DMF, 89%; (b) (i) MSTFA, THF; (ii) 5, CSI, DCM, 0 °C; (iii) THF/DCM, 0 °C - rt; (c) H2, Pd black, MeOH; (d) TFA, DCM, 33% over three steps

Results and Discussion Structure activity relationships of the monocarbam scaffold. From the outset, our goal was to identify potent inhibitors of P. aeruginosa which addressed the hydrolytic stability and physical property concerns of the previously reported monocarbams.23 The initial designs focused on introduction of a saturated linker, analogous to compound 2,21 in order to reduce the planarity of the molecule and therefore increase free fraction.40 A variety of saturated heterocycles (9, 13-16) were synthesized in addition to compounds with shortened linkers (17, 18) (Table 1). To evaluate these compounds, P. aeruginosa whole cell activity (MICs), P. aeruginosa PBP3 acylation rate constants,35 human PPB, rat CL, and hydrolytic stability were analyzed. Except for dihydrotriazinone 14 and aniline 18, all compounds demonstrated excellent activity against the multiple efflux pump knock-out strain P. aeruginosa ARC546 and good to moderate activity against wild type P. aeruginosa (ARC545, PAO1). In addition, all compounds displayed PBP3 acylation rate constants of >1 × 103 M-1s-1. Overall, these compounds are effective inhibitors of P. aeruginosa PBP3 and are able to permeate the outer membrane of the Gram-negative bacteria. As can be seen in Table 1, the monocarbams with saturated linkers afforded free fraction values similar to 2, a 4 to 10-fold increase over triazolone 4. In addition, the rat PK of some of the more potent analogs (9 and 13) showed reasonable clearance levels. In general, this set of compounds had good hydrolytic stability, demonstrating excellent stabilities of >100 h. Examination of the hydrolytic stability reaction profiles indicated the major degradation products of resulted from decomposition of the side-chains and not βlactam hydrolysis. Table 1. Antibacterial activity and physiochemical properties of novel monocarbams



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Compound 1 2 4 9 13 14 15 16 17 18 a

P. aeruginosa MIC (µg/mL) ARC545b ARC546a 0.25 4 0.06 0.25 150e 51 ± 5.3 e >150 114 ± 30

P. aeruginosa ARC546 = PAO1 ∆MexABCDXY; bP. aeruginosa ARC545 = PAO1; cn = 3, standard deviation; dpH = 7.4,

37 °C; eNot determined.

To date, there has been limited SAR generated on the siderophore moiety in the monocarbam series.44 SAR from other classes of siderophore-containing monocyclic βlactams indicate some differences in activity can be observed between a 3-hydroxypyridinone and a 1,3-dihydroxypyridinone,45 however this has never been explored in the monocarbam class. To investigate this feature 1,3-dihydroxypyridinone derivatives of compounds with differing activities were synthesized. The compounds and data for both the parent 3hydroxypyridinone and 1,3-dihydroxypyridinone derivatives are highlighted in Table 3. Comparison of the modified siderophore compounds with the parent compounds presented a few trends as well as some unexpected effects. The P. aeruginosa MIC value of compound 28 was similar to 9, however the free fraction was reduced (24 to 8% free). Comparison of ureas 21 and 29 showed a marked improvement in potency (PAO1 MIC = 0.5 µg/ml versus 16 µg/ml) and hydrolytic stability (87 h versus 30 h). The amino acid derivatives 30 and 31 provided decreased MICs, and increased acylation rate constants and free fraction compared to the parent compounds (23 and 24, respectively). In general, the 1,3-dihydroxypyridinone analogs afforded compounds with improved potency and hydrolytic stability compared to the corresponding 3-hydroxypyridinones while maintaining good free fractions. Attempts to correlate the changes in PPB and hydrolytic stability to changes in the pKa of the siderophore did not reveal any information. It was concluded the changes we observed are due to unpredicted effects caused by the modified 3-dimensional structures of the compounds.


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Initial attempts to predict the 3-dimensional shapes and create computational models to corroborate these hypotheses were not successful and continued efforts were out of scope of the presented project. However a deeper understanding of how the identity of the siderophore and its linker to the scaffold would provide useful incite for future design. Table 3. Comparison of the antibacterial activity and physiochemical properties of 3hydroxypyridinone and 1,3-hydroxypyridinone siderophore-conjugated monocarbams

Compound 9 28 21 29 23 30 24 31 a

P. aeruginosa MIC (µg/mL) a b ARC546 ARC545 150 >150f


37 °C; en = 1; fNot determined

To expand the SAR we next examined introduction and removal of a methyl substituent on several portions of the scaffold as can be seen in Table 4. These changes had large effects on chemical stability and potency. Methylation of the urea nitrogens had little effect on potency or PPB, however compound 32 had a significant reduction in stability presumably due to the increased basicity of the nitrogen and therefore favoring elimination. Removal of the gem-dimethyl substituent from the amino-thiazole oxime (34) resulted in a loss of antimicrobial activity against P. aeruginosa and 10-fold reduction in acylation efficiency. Based on reported crystal structures of amino-thiazole oxime containing βlactams, this reduction in target engagement is due to loss of hydrophobic interactions in that



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portion of the P. aeruginosa PBP3 pocket, however the efflux mutant P. aeruginosa MIC (ARC546 MIC = 0.13 µg/ml) indicates a high rate constant is not critical for cellular activity.43 Introduction of an additional methyl to the β-lactam core (35) resulted in a marked increase in MIC and a large decrease in acylation rate constant. It has been shown that this substitution is tolerated on monobactams and monosulfactams. However with the larger activating group of a monocarbam the additional substituent on the β-lactam core causes unfavorable clashes with the enzyme.43, 46 These data indicate that modification of the parts of the inhibitors that interact with the PBP3 enzyme has a direct effect on acylation rate constants but this does not always correlate with antimicrobial activity. Table 4. Antibacterial activity and physiochemical properties of monocarbam analogs

P. aeruginosa MIC (µg/mL) Compound 29 32 33 34 35 a

1

R Me Me Me H Me

2

R H H H H Me

3

R H Me H H H

4

R H H Me H H

a

ARC546 150 87 ± 20 >150e


37 °C; dNot determined

Population MICs and PK properties. After identification of a number of compounds with favorable potency and properties (P. aeruginosa PAO1 MICs ≤ 1, free fractions >20%, and stabilities >100 h) we profiled them further for differentiation in terms of susceptibility or PK. Data for select compounds can be seen in Table 5. These compounds, though not as potent as triazolone 4, are effective against a panel of clinical isolates of P. aeruginosa, including strains containing metallo-β-lactamases and P. aeruginosa specific extended


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spectrum β-lactamases (ESBLs),47 with MIC90 values of ≤ 2 µg/ml (details of the strains included in the MIC90 panels can be found in the supporting information). Against other Gram-negative pathogens, they were less effective agents (Table 5). Reasons for the elevated MIC90 values against the enterobacteriacea are due to the susceptibility of these compounds to certain classes of ESBLs (e.g., TEM, CTX-M, SHV) which are prevalent in this class of bacteria. Reduced susceptibility to Acinetobacter baumannii did not correlate with the βlactamase content suggesting the elevated MICs are due to poor penetration. The new pyrrolidinone-based monocarbams consistently demonstrate acceptable levels of free drug. The rat free fraction, showing similar trends to the human free fraction, is increased compared to compound 4 while low clearance is observed. Overall the monocarbams have PK properties consistent with other β-lactams (e.g.1, Table 5).48

Table 5. Population MICs and PK properties of monocarbam analogs

P. aeruginosa b

E. coli

K. pneumoniaeb A. baumannii

b

1 1024 (4 - >1024) >512 (0.03 - >512) >512 (0.25 - >512) >512 (16 - >512)

4 0.25 (0.03 - 2) 16 (0.016 - 128) 8 (0.03 - 32) >128 (1 - >128)

MIC90 (µg/mL) (range) 9 2 (0.13 - 2) 32 (0.03 - >128) 32 (0.03 - 64) >64 (2 - >64)

60 ± 0.10 21 0.30 0.44

4d 9 0.39 0.28

6 ± 0.94 16 0.34 0.44

a

13 2 (0.13 - 8) 64 (0.25 - >128) 64 (0.03 - >32) >128 (8 - >128)

29 2 (0.13 - 2) 16 (0.06 - >128) 32 (0.03 - >128) >128 (1 - >128)

15 ± 3.4 12 0.37 0.42

29 ± 1.2 9 0.49 0.29

c

PK Properties Rat PPBd (% free) Rat CL (mL/min/kg) Rat t1/2 (h) Rat Vss (L/kg) a

n = 22 for E. coli and n = 20 for P. aeruginosa, K. pneumonia, A. baumannii. b E. coli = Escherichia coli; K. pneumoniae = Klebsiella pneumoniae; A. baumannii = Acinetobacter baumannii. cHan Wistar Rat (male), iv infusion, 1 mg/kg, n = 2; dn = 3, standard deviation; eNot determined

PK/PD modeling to predict in vivo efficacy from in vitro killing kinetics. As can be seen from the MIC90 data in Table 5, the compounds were effective anti-P. aeruginosa agents. However the in vitro MICs did not differentiate between a variety of chemotypes. To address this concern, we sought to utilize an in vitro tool that would enable us to differentiate and



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therefore prioritize compounds for in vivo efficacy studies.

Two compounds with similar in

vitro profiles but different structural motifs, triazinone 13 and pyrrolidinone 29, were selected for PK/PD modeling and simulation. Monocarbam 4 was also evaluated for validation purposes since it had been shown to be efficacious in vivo against a strain of P. aeruginosa.36 For all PK/PD modeling work, metallo-β-lactamase producing P. aeruginosa ARC3502 (VIM-1) was utilized as the study strain. For each compound, the relationship between free drug concentration and bacterial response was evaluated as a function of time by generating in vitro kill kinetics (fixed static concentrations over time) and in vivo kill kinetics (dynamic concentration-time profiles following single dose) in an immuno-compromised mouse thigh infection model.49 A full dose-ranging efficacy experiment was additionally generated for compound 4 to verify predictions of in vivo response at the 24 h endpoint following multiple doses every 3 h. A PK/PD model previously validated to effectively describe the in vivo response of P. aeruginosa to β-lactams50-53 was used to fit the in vitro kill kinetics for compound 4 against P. aeruginosa ARC3502. As seen in Figures 2a and 2b, the model fit the in vitro data for monocarbam 4 reasonably well (r2 = 0.90). Next, the estimated model (bacterial kill rate, Kk = 1.2 h-1; half-maximal effective concentration, EC50 = 0.01 mg/ml) was used to simulate the in vivo response. Figures 2c and 2d, respectively, show the estimated model generated from in vitro data reasonably predicted the in vivo response for the single-dose kill kinetics and for the dose-ranging efficacy experiment. Model validation was established with compound 4, as the simulated data correctly predicted net bacterial stasis at 24 h with 50 mg/kg every 3 h and 2-log kill with the highest dosing regimen, 200 mg/kg every 3 h (Figure 2d).


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Figure 2. PK/PD modeling for compound 4 against P. aeruginosa ARC3502. (a) Model fit of in vitro kill kinetics at fixed static concentrations (Kk = 1.2 h-1, EC50 = 0.01 mg/mL).

Symbols represent observations; solid lines are model

fit/predictions. (b) Observations versus model predictions for in vitro data fit. (c) Prediction of in vivo kill kinetics following single doses by estimated model. Symbols represent observations; solid lines are model fit/predictions. (d) Prediction of in vivo efficacy following multiple doses in a dose-ranging experiment. Symbols represent observations at 24 h time point (6 h for vehicle); solid lines are model fit/predictions.

The modeling of in vitro kill kinetics and subsequent prediction of in vivo response was repeated for compounds 13 and 29. Again we fit the in vitro data to the model and then employed estimated parameters (13, Kk = 4.3 h-1, EC50 = 2.1 mg/ml; 29, Kk = 5.2 h1

, EC50 = 1.4 mg/ml) to simulate the in vivo response. Figures 3a and 4a show the model fit

the in vitro kill kinetics for 13 and 29, respectively, with both compounds demonstrating a similar in vitro profile. The in vitro observed bacterial burdens were in line with the model predictions, with an r2 of 0.95 and 0.91 for 13 (Figure 3b) and 29 (Figure 4b), respectively. Once more, the model was efficient in predicting the in vivo kill kinetics for both compounds (Figure 3c for 13, Figure 4c for 29) and correctly predicted the higher rate of bacterial kill in vivo for pyrrolidinone 29 irrespective of the similar in vitro profiles. This is because when predicting in vivo response the model combines the growth and kill parameters with the in



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vivo pharmacokinetics, which is significantly different between 13 and 29 for the same dose levels. For example, the unbound AUC of 29 is approximately 2-fold higher as compared to the unbound AUC of 13 (PK parameters are reported in the supporting information). The result is a meaningful difference in in vivo response between 13 and 29. Taking it one step further, we utilized the model to simulate a full dose-ranging efficacy experiment (multiple doses every 3 h) for 13 and 29 in a similar fashion as monocarbam 4. As seen in Figures 3d and 4d, differences between these two compounds are highlighted by our PK/PD modeling, with 29 predicted to be more efficacious in vivo than 13 against this strain of P. aeruginosa. Similar to compound 4, pyrrolidinone 29 was predicted to achieve stasis with the 50 mg/kg every 3 h regimen and 2-log kill with 200 mg/kg every 3 h.

Figure 3. PK/PD modeling for compound 13 against P. aeruginosa ARC3502. (a) Model fit of in vitro kill kinetics at fixed static concentrations (Kk = 4.3 h-1, EC50 = 2.1 mg/mL). Symbols represent observations; solid lines are model fit/predictions. (b) Observations versus model predictions for in vitro data fit. (c) Prediction of in vivo kill kinetics following single doses by estimated model.

Symbols represent observations; solid lines are model predictions.

Prediction of in vivo efficacy following multiple doses in a dose-ranging experiment. Solid lines are model predictions.


(d)

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Figure 4. PK/PD modeling for compound 29 against P. aeruginosa ARC3502. (a) Model fit of in vitro kill kinetics at fixed static concentrations (Kk = 5.2 h-1, EC50 = 1.4 mg/mL). Symbols represent observations; solid lines are model fit/predictions. (b) Observations versus model predictions for in vitro data fit. (c) Prediction of in vivo kill kinetics following single doses by estimated model.

Symbols represent observations; solid lines are model predictions.

(d)

Prediction of in vivo efficacy following multiple doses in a dose-ranging experiment. Solid lines are model predictions.

It should be noted that despite a similar in vitro killing profile for the three compounds (Figures 2a, 3a, 4a), the estimated kill rate of compound 4 (Kk = 1.2 h-1) is approximately 2-3 fold lower than the estimated kill rates for compounds 13 and 29 (Kk = 4.3 h-1 and Kk = 5.2 h-1 respectively).

This is because the in vitro kill kinetics study for

compound 4 was performed in isosensitest media, where Mueller Hinton Broth (MHB) media was used for compounds 13 and 29. Due to the different media, the in vitro growth rate of the bacterium was 2-3-fold lower for compound 4 as compared to the growth rates in the experiments with compounds 13 and 29.

Since bacterial population dynamics are a

combination of growth and kill rates, the estimated kill rate for compound 4 was lower than for compounds 13 and 29. Therefore, with media adjusted growth and kill rates, the model is



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able to predict the in vivo response for all three compounds reasonably well, demonstrating the robustness of the modeling approach. Overall we have shown that a range of parameters are essential to predicting in vivo response.

There is a complex interplay between the various parameters, which

combined with the inherent model nonlinearity provided in vivo predictions. With these results we were confident we had a predictive tool to enable compound prioritization for further in vivo testing. The results from the further in vivo pharmacology will be reported elsewhere.54 Conclusion In summary, we have identified a new series of siderophore-conjugated monocarbams which display excellent biochemical and cellular P. aeruginosa activity, good hydrolytic stability, and favorable PK parameters. We developed this series with the aim of addressing the known physical property and stability issues of monocarbams. By introduction of a saturated linker we succeeded in significantly increasing free fraction compared to triazolones. Modifying the siderophore to a 1,3-dihydroxypyridinone provided compounds with improved potencies and physical properties. We observed these compounds were not prone to hydrolysis of the β-lactam, but instead suffered from decomposition of the sidechains. Throughout our optimization we were able to maintain low clearance values while increasing the human free fraction and therefore free drug concentrations. We applied a semi-mechanistic PK/PD model which enables differentiation of compounds and prediction of in vivo efficacy from in vitro kill kinetics. This enabled us, with minimal compound requirements (

Discovery of Efficacious Pseudomonas aeruginosa-Targeted

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