The repurposing of Tebipenem pivoxil as alternative therapy for severe gastrointestinal infections caused by extensively drug resistant Shigella spp.

  1. Elena Fernández Alvaro  Is a corresponding author
  2. Phat Voong Vinh
  3. Cristina de Cozar
  4. David Willé
  5. Beatriz Urones
  6. Alvaro Cortés
  7. Alan Price
  8. Nhu Tran Do Hoang
  9. Tuyen Ha Thanh
  10. Molly McCloskey
  11. Shareef Shaheen
  12. Denise Dayao
  13. Jaime de Mercado
  14. Pablo Castañeda
  15. Adolfo García-Perez
  16. Benson Singa
  17. Patricia Pavlinac
  18. Judd Walson
  19. Maria Santos Martínez-Martínez
  20. Samuel LM Arnold
  21. Tzipori Saul
  22. Lluis Ballell
  23. Stephen Baker  Is a corresponding author
  1. GSK Global Health, Spain
  2. Oxford University Clinical Research Unit, Viet Nam
  3. GSK R&D, United Kingdom
  4. University of Washington School of Medicine, United States
  5. Tufts University, United States
  6. Kenya Medical Research Institute, Kenya
  7. University of Washington, United States
  8. University of Cambridge, United Kingdom

Abstract

<strong>Background:</strong> Diarrhoea remains one of the leading causes of childhood mortality globally. Recent epidemiological studies conducted in low-middle income countries (LMICs) identified Shigella spp. as the first and second most predominant agent of dysentery and moderate diarrhoea, respectively. Antimicrobial therapy is often necessary for Shigella infections; however, we are reaching a crisis point with efficacious antimicrobials. The rapid emergence of resistance against existing antimicrobials in Shigella spp. poses a serious global health problem. <strong>Methods:</strong> Aiming to identify alternative antimicrobial chemicals with activity against antimicrobial resistant Shigella, we initiated a collaborative academia-industry drug discovery project, applying high throughput phenotypic screening across broad chemical diversity and followed a lead compound through in vitro and in vivo characterisation. <strong>Results:</strong> We identified several known antimicrobial compound classes with antibacterial activity against Shigella. These compounds included the oral carbapenem Tebipenem, which was found to be highly potent against broadly susceptible Shigella and contemporary MDR variants for which we perform detailed pre-clinical testing. Additional in vitro screening demonstrated that Tebipenem had activity against a wide range of other non-Shigella enteric bacteria. Cognisant of the risk for the development of resistance against monotherapy, we identified synergistic behaviour of two different drug combinations incorporating Tebipenem. We found the orally bioavailable prodrug (Tebipenem pivoxil) had ideal pharmacokinetic properties for treating enteric pathogens and was effective in clearing the gut of infecting organisms when administered to Shigella-infected mice and gnotobiotic piglets. <strong>Conclusions:</strong> Our data highlight the emerging antimicrobial resistance crisis and shows that Tebipenem pivoxil (licenced for paediatric respiratory tract infections in Japan) should be accelerated into human trials and could be repurposed as an effective treatment for severe diarrhoea caused by MDR Shigella and other enteric pathogens in LMICs. <strong>Funding:</strong> Tres Cantos Open Lab Foundation (projects TC239 and TC246), the Bill and Melinda Gates Foundation (grant OPP1172483) and Wellcome (215515/Z/19/Z).

Data availability

All raw data for this project is available at 10.5281/zenodo.5929105. Exceptions include the propriety compound list owned by GSK. Access to compounds can be requested via the open lab foundation and GSK and the raw MALDI-TOF data are available upon request from the corresponding authors.

The following data sets were generated

Article and author information

Author details

  1. Elena Fernández Alvaro

    GSK Global Health, Madrid, Spain
    For correspondence
    elena.a.fernandez-alvaro@gsk.com
    Competing interests
    Elena Fernández Alvaro, is affiliated with GSK Global Health. The author has no other competing interests to declare..
  2. Phat Voong Vinh

    The Hospital for Tropical Diseases, Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam
    Competing interests
    No competing interests declared.
  3. Cristina de Cozar

    GSK Global Health, Madrid, Spain
    Competing interests
    Cristina de Cozar, is affiliated with GSK Global Health. The author has no other competing interests to declare..
  4. David Willé

    GSK R&D, Stevenage, United Kingdom
    Competing interests
    David Willé, is affiliated with GSK Global Health. The author has no other competing interests to declare..
  5. Beatriz Urones

    GSK Global Health, Madrid, Spain
    Competing interests
    Beatriz Urones, is affiliated with GSK Global Health. The author has no other competing interests to declare..
  6. Alvaro Cortés

    GSK Global Health, Madrid, Spain
    Competing interests
    Alvaro Cortés, is affiliated with GSK Global Health. The author has no other competing interests to declare..
  7. Alan Price

    GSK Global Health, Madrid, Spain
    Competing interests
    Alan Price, is affiliated with GSK Global Health. The author has no other competing interests to declare..
  8. Nhu Tran Do Hoang

    The Hospital for Tropical Diseases, Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam
    Competing interests
    No competing interests declared.
  9. Tuyen Ha Thanh

    The Hospital for Tropical Diseases, Wellcome Trust Major Overseas Programme, Oxford University Clinical Research Unit, Ho Chi Minh City, Viet Nam
    Competing interests
    No competing interests declared.
  10. Molly McCloskey

    Division of Allergy and Infectious Disease, Center for Emerging and Re-emerging Infectious Diseases, University of Washington School of Medicine, Seattle, United States
    Competing interests
    No competing interests declared.
  11. Shareef Shaheen

    Division of Allergy and Infectious Disease, Center for Emerging and Re-emerging Infectious Diseases, University of Washington School of Medicine, Seattle, United States
    Competing interests
    No competing interests declared.
  12. Denise Dayao

    Department of Infectious Disease and Global Health, Tufts University, North Grafton, United States
    Competing interests
    No competing interests declared.
  13. Jaime de Mercado

    GSK Global Health, Madrid, Spain
    Competing interests
    Jaime de Mercado, is affiliated with GSK Global Health. The author has no other competing interests to declare..
  14. Pablo Castañeda

    GSK Global Health, Madrid, Spain
    Competing interests
    Pablo Castañeda, is affiliated with GSK Global Health. The author has no other competing interests to declare..
  15. Adolfo García-Perez

    GSK Global Health, Madrid, Spain
    Competing interests
    Adolfo García-Perez, is affiliated with GSK Global Health. The author has no other competing interests to declare..
  16. Benson Singa

    Kenya Medical Research Institute, Nairobi, Kenya
    Competing interests
    No competing interests declared.
  17. Patricia Pavlinac

    Department of Global Health, University of Washington, Seattle, United States
    Competing interests
    No competing interests declared.
  18. Judd Walson

    Division of Allergy and Infectious Disease, Center for Emerging and Re-emerging Infectious Diseases, University of Washington School of Medicine, Seattle, United States
    Competing interests
    No competing interests declared.
  19. Maria Santos Martínez-Martínez

    GSK Global Health, Madrid, Spain
    Competing interests
    Maria Santos Martínez-Martínez, is affiliated with GSK Global Health. The author has no other competing interests to declare..
  20. Samuel LM Arnold

    Division of Allergy and Infectious Disease, Center for Emerging and Re-emerging Infectious Diseases, University of Washington School of Medicine, Seattle, United States
    Competing interests
    No competing interests declared.
  21. Tzipori Saul

    Department of Infectious Disease and Global Health, Tufts University, North Grafton, United States
    Competing interests
    No competing interests declared.
  22. Lluis Ballell

    GSK Global Health, Madrid, Spain
    Competing interests
    Lluis Ballell, is affiliated with GSK Global Health. The author has no other competing interests to declare..
  23. Stephen Baker

    Department of Medicine, University of Cambridge, Cambridge, United Kingdom
    For correspondence
    sgb47@medschl.cam.ac.uk
    Competing interests
    No competing interests declared.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-1308-5755

Funding

GSK Open Lab Foundation (TC239 and TC246)

  • Stephen Baker

Bill and Melinda Gates Foundation (OPP1172483)

  • Lluis Ballell

Wellcome Trust (215515/Z/19/Z)

  • Stephen Baker

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Animal experimentation: All studies were conducted in accordance with the European Directive 2010/63/EEC and the GSK Policy on the Care, Welfare and Treatment of Laboratory Animals or were reviewed by the Institutional Animal Care and Use Committee at the institution where the work was performed.

Reviewing Editor

  1. María Mercedes Zambrano, CorpoGen, Colombia

Publication history

  1. Received: April 27, 2021
  2. Accepted: March 9, 2022
  3. Accepted Manuscript published: March 15, 2022 (version 1)
  4. Accepted Manuscript updated: March 21, 2022 (version 2)
  5. Version of Record published: March 28, 2022 (version 3)
  6. Version of Record updated: April 6, 2022 (version 4)

Copyright

© 2022, Fernández Alvaro et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Elena Fernández Alvaro
  2. Phat Voong Vinh
  3. Cristina de Cozar
  4. David Willé
  5. Beatriz Urones
  6. Alvaro Cortés
  7. Alan Price
  8. Nhu Tran Do Hoang
  9. Tuyen Ha Thanh
  10. Molly McCloskey
  11. Shareef Shaheen
  12. Denise Dayao
  13. Jaime de Mercado
  14. Pablo Castañeda
  15. Adolfo García-Perez
  16. Benson Singa
  17. Patricia Pavlinac
  18. Judd Walson
  19. Maria Santos Martínez-Martínez
  20. Samuel LM Arnold
  21. Tzipori Saul
  22. Lluis Ballell
  23. Stephen Baker
(2022)
The repurposing of Tebipenem pivoxil as alternative therapy for severe gastrointestinal infections caused by extensively drug resistant Shigella spp.
eLife 11:e69798.
https://doi.org/10.7554/eLife.69798

Further reading

    1. Epidemiology and Global Health
    Yochai Edlitz, Eran Segal
    Research Article

    Background: Type 2 diabetes (T2D) accounts for ~90% of all cases of diabetes, resulting in an estimated 6.7 million deaths in 2021, according to the International Diabetes Federation (IDF). Early detection of patients with high risk of developing T2D can reduce the incidence of the disease through a change in lifestyle, diet, or medication. Since populations of lower socio-demographic status are more susceptible to T2D and might have limited resources or access to sophisticated computational resources, there is a need for accurate yet accessible prediction models.

    Methods: In this study, we analyzed data from 44,709 non-diabetic U.K. Biobank participants aged 40-69, predicting the risk of T2D onset within a selected timeframe (mean of 7.3 years with a standard deviation of 2.3 years). We started with 798 features that we identified as potential predictors for T2D onset. We first analyzed the data using gradient boosting decision trees, survival analysis, and logistic regression methods. We devised one non-laboratory model accessible to the general population and one more precise yet simple model that utilizes laboratory tests. We simplified both models to an accessible scorecard form, tested the models on normoglycemic and prediabetes sub cohorts, and compared the results to the results of the general cohort. We established the non-laboratory model using the following covariates: sex, age, weight, height, waist size, hip circumference, waist-to-hip Ratio (WHR), and Body-Mass Index (BMI). For the laboratory model, we used age and sex together with four common blood tests: HDL (high-density lipoprotein), gamma-glutamyl transferase, glycated hemoglobin, and triglycerides. As an external validation dataset, we used the electronic medical record database of Clalit Health Services.

    Results: The non-laboratory scorecard model achieved an Area Under the Receiver Operating Curve (auROC) of 0.81 (0.77-0.84 95% Confidence Interval (CI)) and an odds ratio (OR) between the upper and fifth prevalence deciles of 17.2 (5-66 95% CI). Using this model, we classified three risk groups, a group with 1% (0.8-1%), 5% (3-6%), and the third group with a 9% (7-12%) risk of developing T2D. We further analyzed the contribution of the laboratory-based model and devised a blood-test model based on age, sex and the four common blood tests noted above. In this scorecard model, we included age, sex, glycated hemoglobin (HbA1c%), gamma glutamyl-transferase, triglycerides, and HDL cholesterol. Using this model, we achieved an auROC of 0.87 (0.85-0.90 95% CI) and a deciles' OR of x48 (12-109 95% CI). Using this model, we classified the cohort into four risk groups with the following risks: 0.5% (0.4%-7%); 3% (2-4%); 10% (8-12%) and a high-risk group of 23% (10-37%) of developing T2D. When applying the blood tests model using the external validation cohort (Clalit), we achieved an auROC of 0.75 (0.74-0.75 95% CI). We analyzed several additional comprehensive models, which included genotyping data and other environmental factors. We found that these models did not provide cost-efficient benefits over the four blood test model. The commonly used German Diabetes Risk Score (GDRS) and Finnish Diabetes Risk Score (FINDRISC) models, trained using our data, achieved an auROC of 0.73 (0.69-0.76) and 0.66 (0.62-0.70), respectively, inferior to the results achieved by the four blood test model and by the Anthropometry models.

    Conclusions: The four blood tests and anthropometric models outperformed the commonly used non-laboratory models, the FINDRISC and the GDRS. We suggest that our models be used as tools for decision-makers to assess populations at elevated T2D risk and thus improve medical strategies. These models might also provide a personal catalyst for changing lifestyle, diet, or medication modifications to lower the risk of T2D onset.

    Funding: No Funders. The funders had no role in study design, data collection, interpretation, or the decision to submit the work for publication.

    1. Epidemiology and Global Health
    Guillermo Bosch et al.
    Research Article Updated

    Background:

    To assess the effect of the COVID-19 pandemic on performance indicators in the population-based breast cancer screening program of Parc de Salut Mar (PSMAR), Barcelona, Spain.

    Methods:

    We conducted a before-and-after, study to evaluate participation, recall, false positives, the cancer detection rate, and cancer characteristics in our screening population from March 2020 to March 2021 compared with the four previous rounds (2012–2019). Using multilevel logistic regression models, we estimated the adjusted odds ratios (aORs) of each of the performance indicators for the COVID-19 period, controlling by type of screening (prevalent or incident), socioeconomic index, family history of breast cancer, and menopausal status. We analyzed 144,779 invitations from 47,571women.

    Results:

    During the COVID-19 period, the odds of participation were lower in first-time invitees (aOR = 0.90 [95% CI = 0.84–0.96]) and in those who had previously participated regularly and irregularly (aOR = 0.63 [95% CI = 0.59–0.67] and aOR = 0.95 [95% CI = 0.86–1.05], respectively). Participation showed a modest increase in women not attending any of the previous rounds (aOR = 1.10 [95% CI = 1.01–1.20]). The recall rate decreased in both prevalent and incident screening (aOR = 0.74 [95% CI = 0.56–0.99] and aOR = 0.80 [95% CI = 0.68–0.95], respectively). False positives also decreased in both groups (prevalent aOR = 0.92 [95% CI = 0.66–1.28] and incident aOR = 0.72 [95% CI = 0.59–0.88]). No significant differences were observed in compliance with recall (OR = 1.26, 95% CI = 0.76–2.23), cancer detection rate (aOR = 0.91 [95% CI = 0.69–1.18]), or cancer stages.

    Conclusions:

    The COVID-19 pandemic negatively affected screening attendance, especially in previous participants and newcomers. We found a reduction in recall and false positives and no marked differences in cancer detection, indicating the robustness of the program. There is a need for further evaluations of interval cancers and potential diagnostic delays.

    Funding:

    This study has received funding by grants PI19/00007 and PI21/00058, funded by Instituto de Salud Carlos III (ISCIII) and cofunded by the European Union and Grant RD21/0016/0020 funded by Instituto de Salud Carlos III and by the European Union NextGenerationEU, Mecanismo para la Recuperación y la Resiliencia (MRR).