TB-Platform for the Aggregation of Preclinical Experiments Data (TB-APEX)
The TB-APEX data platform is designed to catalyze and accelerate TB research by curating and standardizing preclinical study data and making this data publicly available to qualified researchers.
Overview
TB-APEX data platform mission:
The TB-APEX data platform is designed to catalyze and accelerate TB research by curating and standardizing tuberculosis (TB) preclinical data and making this data publicly available to qualified researchers. These researchers can access and analyze data in aggregate, or filter and view individual subject-level data. Additional preclinical trial data may be available in the future.
What does the TB-APEX data platform contain?
The platform contains Preclinical TB trial datasets currently consisting of Hollow Fiber Systems (In Vitro) and Animal Studies (In Vivo) contributed by the following organizations, to C-Path for use by qualified TB researchers.
1. Evotec
2. Baylor University
3. Johns Hopkins University (JHU)
4. Colorado State University (CSU)
With C-Path’s continued engagement with various TB research initiatives, additional preclinical trial data may be available in the future.
Acknowledgements:
Creation of the TB-APEX data platform was made possible by a grant from the Bill & Melinda Gates Foundation.
Continued hosting and maintenance for the TB-APEX data platform is made possible by a grant from the Innovative Medicines Initiative 2 Joint Undertaking (JU) under grant agreement No. 853989. The JU receives support from the European Union’s Horizon 2020 research and innovation programme, and in-kind support from European Federation of Pharmaceutical Industries and Associations (EFPIA), Global Alliance for TB Drug Development, Bill & Melinda Gates Foundation and University of Dundee.
TB-APEX data platform content and access:
The TB-APEX data platform will catalog contemporary (TB) preclinical trial data sets and make these data sets available to qualified researchers. Approved researchers can access patient-level data from at least sixty preclinical trials. Additional trial data is expected to be made available in the future.
For more information on TB-APEX or how your organization can contribute data, please contact: codr-eu@c-path.eu.
Access the TB-APEX platform
TB-Platform for the Aggregation of Preclinical Experiments Data (TB-APEX) hosted by Critical Path Institute.
Please, click here for further details and guidance regarding the hosted platform.
TB-APEX Platform
| Study ID | Area | No. of Animals or Cartridges | Title | Drugs | Contributors | Study Type |
|---|---|---|---|---|---|---|
| EV-LY-TBa19003 | Tuberculosis Mouse Model | 265 | EV-LY-TBa19003 | Bedaquiline, Isoniazid, Linezolid, Moxifloxacin, Pretomanid, Rifampicin, Pyrazinamide | EVOTEC | In Vivo |
| EV-TL-PK2019 | Tuberculosis Mouse Model | 144 | EV-TL-PK2019 | Bedaquiline, Isoniazid, Linezolid, Moxifloxacin, Pretomanid, Rifampicin, Pyrazinamide | EVOTEC | In Vivo |
| Gates-03 | Tuberculosis Mouse Model | 174 | Gates-03 | Rifampin, Isoniazid, Moxifloxacin, Pyrazinamide, Ethambutol | Colorado State University (CSU) | In Vivo |
| Gates-11 | Tuberculosis Mouse Model | 194 | Gates-11 | Rifampin, Isoniazid, Pyrazinamide, Ethambutol | Colorado State University (CSU) | In Vivo |
| Gates-12 | Tuberculosis Mouse Model | 36 | Gates-12 | Rifampin, Isoniazid, Pyrazinamide, Ethambutol | Colorado State University (CSU) | In Vivo |
| Gates-17 | Tuberculosis Mouse Model | 38 | Gates-17 | Rifampin, Isoniazid, Pyrazinamide, Ethambutol | Colorado State University (CSU) | In Vivo |
| Gates-B | Tuberculosis Mouse Model | 477 | Gates-B | Rifampin, Isoniazid, Pyrazinamide, Moxifloxacin | Colorado State University (CSU) | In Vivo |
| JHU-2013-Expt-3c | Tuberculosis Mouse Model | 241 | JHU-2013-Expt-3c | Rifampin, Isoniazid, Pyrazinamide, Bedaquiline, Pretomanid, Linezolid, Sutezolid | Johns Hopkins University (JHU) | In Vivo |
| JHU-2014-Expt-3c | Tuberculosis Mouse Model | 160 | JHU-2014-Expt-3c | Rifampin, Isoniazid, Pyrazinamide, Bedaquiline, Pretomanid, Linezolid | Johns Hopkins University (JHU) | In Vivo |
| JHU-2016-Expt-3c | Tuberculosis Mouse Model | 72 | JHU-2016-Expt-3c | Bedaquiline, Pretomanid, Linezolid | Johns Hopkins University (JHU) | In Vivo |
| JHU-CFZ-Study1 | Tuberculosis Mouse Model | 100 | JHU-CFZ-Study1 | Rifampin, Isoniazid, Pyrazinamide, Ethambutol | Johns Hopkins University (JHU) | In Vivo |
| JHU-CFZ-Study2 | Tuberculosis Mouse Model | 54 | JHU-CFZ-Study2 | Rifampin, Isoniazid, Pyrazinamide, Ethambutol | Johns Hopkins University (JHU) | In Vivo |
| JHU-CFZ-Study3 | Tuberculosis Mouse Model | 83 | JHU-CFZ-Study3 | Rifampin, Isoniazid, Pyrazinamide, Ethambutol | Johns Hopkins University (JHU) | In Vivo |
| JHU-CFZ-Study4 | Tuberculosis Mouse Model | 81 | JHU-CFZ-Study4 | Rifampin, Isoniazid, Pyrazinamide, Ethambutol | Johns Hopkins University (JHU) | In Vivo |
| JHU-CFZ-Study5 | Tuberculosis Mouse Model | 63 | JHU-CFZ-Study5 | Rifampin, Isoniazid, Pyrazinamide, Ethambutol | Johns Hopkins University (JHU) | In Vivo |
| JHU-MXF-Study1 | Tuberculosis Mouse Model | 157 | JHU-MXF-Study1 | Rifampin, Isoniazid, Pyrazinamide, Moxifloxacin | Johns Hopkins University (JHU) | In Vivo |
| JHU-MXF-Study2 | Tuberculosis Mouse Model | 254 | JHU-MXF-Study2 | Rifampin, Isoniazid, Pyrazinamide, Moxifloxacin | Johns Hopkins University (JHU) | In Vivo |
| JHU-PMD-Study1 | Tuberculosis Mouse Model | 96 | JHU-PMD-Study1 | Rifampin, Pyrazinamide, Moxifloxacin, Pretomanid | Johns Hopkins University (JHU) | In Vivo |
| JHU-PMD-Study2 | Tuberculosis Mouse Model | 283 | JHU-PMD-Study2 | Rifampin, Isoniazid, Pyrazinamide, Moxifloxacin, Pretomanid | Johns Hopkins University (JHU) | In Vivo |
| JHU-PMD-Study3 | Tuberculosis Mouse Model | 112 | JHU-PMD-Study3 | Rifampin, Isoniazid, Rifapentine, Pyrazinamide, Moxifloxacin, Pretomanid | Johns Hopkins University (JHU) | In Vivo |
| JHU-PMD-Study4 | Tuberculosis Mouse Model | 194 | JHU-PMD-Study4 | Rifampin, Isoniazid, Bedaquiline, Pyrazinamide, Moxifloxacin, Pretomanid | Johns Hopkins University (JHU) | In Vivo |
| JHU-PMD-Study5 | Tuberculosis Mouse Model | 242 | JHU-PMD-Study5 | Rifampin, Isoniazid, Pyrazinamide, Moxifloxacin, Pretomanid | Johns Hopkins University (JHU) | In Vivo |
| JHU-PMD-Study6 | Tuberculosis Mouse Model | 100 | JHU-PMD-Study6 | Rifampin, Isoniazid, Pyrazinamide, Moxifloxacin, Pretomanid | Johns Hopkins University (JHU) | In Vivo |
| JHU-PMD-Study7 | Tuberculosis Mouse Model | 172 | JHU-PMD-Study7 | Rifampin, Isoniazid, Pyrazinamide, Moxifloxacin, Pretomanid | Johns Hopkins University (JHU) | In Vivo |
| JHU-PMD-Study8 | Tuberculosis Mouse Model | 181 | JHU-PMD-Study8 | Rifampin, Isoniazid, Pyrazinamide, Moxifloxacin, Pretomanid | Johns Hopkins University (JHU) | In Vivo |
| JHU-PZA-Study1 | Tuberculosis Mouse Model | 107 | JHU-PZA-Study1 | Rifampin, Isoniazid, Pyrazinamide, Ethambutol | Johns Hopkins University (JHU) | In Vivo |
| JHU-REMox-Study1 | Tuberculosis Mouse Model | 136 | JHU-REMox-Study1 | Rifampin, Isoniazid, Pyrazinamide, Moxifloxacin, Ethambutol | Johns Hopkins University (JHU) | In Vivo |
| JHU-RPT-Study1 | Tuberculosis Mouse Model | 220 | JHU-RPT-Study1 | Rifampin, Isoniazid, Pyrazinamide, Moxifloxacin, Rifapentine | Johns Hopkins University (JHU) | In Vivo |
| JHU-RPT-Study2 | Tuberculosis Mouse Model | 156 | JHU-RPT-Study2 | Rifampin, Isoniazid, Pyrazinamide, Moxifloxacin, Rifapentine | Johns Hopkins University (JHU) | In Vivo |
| HFS-50 | Tuberculosis Hollow Fiber | 12 | PAMZ_log_phase_CPTR | PA-824, Moxifloxacin, Pyrazinamide, Isoniazid, Rifampicin | BAYLOR | In Vitro |
| HFS-53 | Tuberculosis Hollow Fiber | 12 | PaMZ_semidormant | PA-824, Moxifloxacin, Pyrazinamide, Isoniazid, Rifampicin | BAYLOR | In Vitro |
| HFS-63 | Tuberculosis Hollow Fiber | 12 | PaMZ_Intracellular | PA-824, Moxifloxacin, Pyrazinamide, Isoniazid, Rifampicin | BAYLOR | In Vitro |
| HFS-64 | Tuberculosis Hollow Fiber | 24 | HF64_CPTR_Sutezolid Revised.2 | Sutezolid | BAYLOR | In Vitro |
| HFS-82 | Tuberculosis Hollow Fiber | 24 | HF82_CPTR_Sutezolid Final Data Set | Sutezolid | BAYLOR | In Vitro |
| HFS-83 | Tuberculosis Hollow Fiber | 24 | HF83_CPTR_Sutezolid @ ph5.8 | Sutezolid | BAYLOR | In Vitro |
| HFS-84 | Tuberculosis Hollow Fiber | 30 | HFS84_CPTR_Delamanid_data_set_LPG | Delamanid | BAYLOR | In Vitro |
| HFS-86 | Tuberculosis Hollow Fiber | 6 | HF86_CPTR_BDQ pK Data Set | Bedaquiline | BAYLOR | In Vitro |
| HFS-87 | Tuberculosis Hollow Fiber | 18 | CPTR HFS 87_Oxazolidinine_LPG | Linezolid, Sutezolid, Tedizolid | BAYLOR | In Vitro |
| HFS-94 | Tuberculosis Hollow Fiber | 24 | HF94_CPTR_Delaminid at 5.8_Data Set | Delamanid | BAYLOR | In Vitro |
| HFS-96 | Tuberculosis Hollow Fiber | 24 | HFS-96_OPC_LogPhase | OPC | BAYLOR | In Vitro |
| HFS-97 | Tuberculosis Hollow Fiber | 12 | CPTR HF97_Oxazolidinine_head-to-head_SDB | Linezolid, Sutezolid, Tedizolid | BAYLOR | In Vitro |
| HFS-99 | Tuberculosis Hollow Fiber | 20 | HFS99 Delamanid_data_set_intracellular | Delaminid | BAYLOR | In Vitro |
| HFS-100 | Tuberculosis Hollow Fiber | 12 | CPTR_HF100_IC_oxzolidinone_head-to-head | Linezolid, Sutezolid, Tedizolid | BAYLOR | In Vitro |
| HFS-101 | Tuberculosis Hollow Fiber | 24 | HFS-101_OPC_H37Ra_IntraCellular_ | OPC | BAYLOR | In Vitro |
| HFS-102 | Tuberculosis Hollow Fiber | 24 | HFS-102_OPC_H37Rv_SemiDormant_Phase | OPC | BAYLOR | In Vitro |
| HFS-105 | Tuberculosis Hollow Fiber | 24 | HSF-105 sutezolid plus metabolite | Sutezolid, metabolite | BAYLOR | In Vitro |
| HFS-107 | Tuberculosis Hollow Fiber | 26 | HF107_CPTR_OPC_Del_H37Ra LogPhase | OPC-167832 &/or Delaminid or Isoniazid, Rifampicin, Pyrazinamide | BAYLOR | In Vitro |
| HFS-108 | Tuberculosis Hollow Fiber | 26 | HF108_OPC_Del_Combo_H37Rv_Sterilizing | OPC-167832 &/or Delaminid or Isoniazid, Rifampicin, Pyrazinamide | BAYLOR | In Vitro |
| HFS-109 | Tuberculosis Hollow Fiber | 26 | HF109_OPC_Del_Combo_H37Ra_IntraCellular | OPC-167832 &/or Delaminid or Isoniazid, Rifampicin, Pyrazinamide | BAYLOR | In Vitro |
| HFS-115 | Tuberculosis Hollow Fiber | 24 | HF115_CPTR_Bedaquiline_H37Rv_SRB | Bedaquiline | BAYLOR | In Vitro |
| HFS-116 | Tuberculosis Hollow Fiber | 22 | HF116_CPTR_Comb_H37Rv_SRB_Final_Report | Bedaquiline, Delaminid, Moxifloxacin, OPC, Pretomanid, Sutezolid, Pyrazinamide, INH, RMP | BAYLOR | In Vitro |
| HFS-117 | Tuberculosis Hollow Fiber | 22 | HF117_CPTR_Comb_H37Ra_LogPhase_Final Rpt | Bedaquiline, Delaminid, Moxifloxacin, OPC, Pretomanid, Sutezolid, Pyrazinamide, INH, RMP | BAYLOR | In Vitro |
| HRZE-R1 | Tuberculosis Hollow Fiber | 10 | HRZE R1 | Isoniazid, Rifampicin, Pyrazinamide, Ethambutol | EVOTEC | In Vitro |
| HRZE-R2 | Tuberculosis Hollow Fiber | 10 | HRZE R2 | Isoniazid, Rifampicin, Pyrazinamide, Ethambutol | EVOTEC | In Vitro |
| HRZE-R3 | Tuberculosis Hollow Fiber | 10 | HRZE R3 | Isoniazid, Rifampicin, Pyrazinamide, Ethambutol | EVOTEC | In Vitro |
| PaMZ-R1 | Tuberculosis Hollow Fiber | 10 | PaMZ R1 | Pretomanid, Moxifloxacin, Pyrazinamide | EVOTEC | In Vitro |
| PaMZ-R2 | Tuberculosis Hollow Fiber | 10 | PaMZ R2 | Pretomanid, Moxifloxacin, Pyrazinamide | EVOTEC | In Vitro |
| PaMZ-R3 | Tuberculosis Hollow Fiber | 10 | PaMZ R3 | Pretomanid, Moxifloxacin, Pyrazinamide | EVOTEC | In Vitro |
| REMox-R1 | Tuberculosis Hollow Fiber | 10 | REMox R1 | Rifampicin, Ethambutol, Moxifloxacin, Pyrazinamide | EVOTEC | In Vitro |
| REMox-R2 | Tuberculosis Hollow Fiber | 10 | REMox R2 | Rifampicin, Ethambutol, Moxifloxacin, Pyrazinamide | EVOTEC | In Vitro |
| REMox-R3 | Tuberculosis Hollow Fiber | 10 | REMox R3 | Rifampicin, Ethambutol, Moxifloxacin, Pyrazinamide | EVOTEC | In Vitro |
Important Information about the TB-APEX Platform Content and Access:
The platform contains Preclinical TB trial datasets currently consisting of Hollow Fiber Systems (In Vitro) and Animal Studies (In Vivo) contributed by the following organizations, to C-Path for use by qualified TB researchers.
1. Evotec
2. Baylor University
3. Johns Hopkins University (JHU)
4. Colorado State University (CSU)
With C-Path’s continued engagement with various TB research initiatives, additional preclinical trial data may be available in the future.
- Treatments
- Drug Resistance
- Demographics
- Biospecimen Events
- Body Weight
- Disposition
- Pharmacokinetics Concentration
- Pharmacokinetics Parameters
- Microbiology Specimen
- Microbiology Susceptibility
- Biospecimen Events
- Trial Level Data
Please note that in light of differences in experimental protocols and approaches per data contributor, the data listed above may vary per study. All data have been remapped to a common data standard such that data can be analyzed across all studies.
The TB-APEX Data Platform is available to qualified researchers who have submitted a sound TB research proposal, have agreed to the “TB-APEX Terms and Conditions for Data Use”, and have been approved through the TB-APEX access review process.
The data is mapped to the Clinical Data Interchange Standards Consortium (CDISC) Standard for Exchange of Nonclinical Data (SEND), Standard Data Tabulation Model (SDTM), Animal Rule Guide (SENDIG-AR v1.0) and Pharmacogenomics/Genetics Guide (PGxIG v1). Knowledge of SDTM and SEND is required for effective use of the data. Information and training on SDTM and SEND are available on the CDISC website.
| Selected domains contained in the TB-APEX Data Platform | |
| CDISC Domain | Variables of Interest |
| DM | Age, Gender, Species, Strain, Trial Arm |
| MS | Drug Resistance Information |
| MB | Culture Results (CFU) |
| BW | Body Weight of Animal |
| EX | Drug Name, Drug Dose, Route & Drug Strength |
| AG | Procedure Agent Name & Dose |
| PC | Concentration measurements for administered compounds and their metabolites |
General Questions:
A: There is no fee to use the TB-APEX data platform.
A: We appreciate suggestions on improvements to the TB-APEX data platform. Please send your comments and suggestions to: codr-eu@c-path.eu.
A: The TB-APEX data platform contains TB preclinical study data, which includes demographic information, dose/concentration information, drug resistance information, biospecimen events, subject body weight, subject disposition, PK results and parameter, microbiological specimen results and study level information.
Additional information specific to data content will be available to registered users of the TB-APEX data platform.
A: The data is mapped to the Clinical Data Interchange Standards Consortium (CDISC) Standard for Exchange of Nonclinical Data (SEND), Standard Data Tabulation Model (SDTM), Animal Rule Guide (SENDIG-AR v1.0) and Pharmacogenomics/Genetics Guide (PGxIG v1) to maximize utility of aggregated data for statistical analysis.
Registration for Access Questions:
A: Visit the Data Archive Platform page on this website to register for access. You must first review and agree to the Terms and Conditions for Use of the TB-APEX data platform. Once completed, researchers will be directed to the online application form.
A: The TB-APEX Steering Committee will review all user access applications in a timely manner, and this may take up to 4 weeks to process.
Data Contribution Questions:
A: Individuals, organizations, institutions, and countries (health ministries, national TB programs, etc.) are encouraged to contribute preclinical study data. In addition to the study dataset, submitting organizations will be requested to provide information regarding study methodology and demographic data for their submissions. For additional information please contact: codr-eu@c-path.eu.
A: Yes, data ownership is always retained by the data contributor.
A: TB-APEX data platform policies for data transfer, validation, processing and access include the following features to ensure that the data are safe and secure:
- Secure file transfer
- OS hardening and security updates
- Host-based intrusion detection/prevention system
- Anti-malware protection
- Automated log monitoring and alert system
- Data access controls for incoming server, investigational database, analysis datasets
- Data backup and disaster recovery
- Data provenance – changes to data will be traceable and auditable throughout its lifecycle
- Multi-factor authentication
- Multi-tier network structure
- File integrity monitor
A: Multiple data formats can be accommodated including text, csv, xls or SAS transport files. Supporting information can be PDF, text, Microsoft Word or other document formats. Critical Path Institute will provide guidance as needed to data contributors.
