Comprehensive Resistance Prediction for Tuberculosis: an International Consortium (CRyPTIC)
Lead Research Organisation:
University of Oxford
Department Name: UNLISTED
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Technical Summary
Our aim is to achieve sufficiently accurate genetic prediction of resistance to all anti-tuberculosis
drugs for whole genome sequencing (WGS) to replace slow, cumbersome, culture-based drug
susceptibility testing (DST) for Mycobacterium tuberculosis complex (MTBC). This would enable
rapid-turnaround near-to-patient assays to revolutionize drug-resistant TB identification and
management.
This multidisciplinary collaboration including TB experts from five continents, WHO,
statisticians/mathematicians and software engineers will integrate machine-learning, statistical
genetics and molecular genetics methods to uncover all genomic variation causing at least 1%
resistance to first- and second-line anti-TB drugs with >1% resistance prevalence. We will use largescale
global and clade-representative WGS (>90,000), with initially >37,000 isolates with extended DST. Approaches include better WGS assembly to identify more variants with more precision,
improved statistical methods to detect associations between variants and DST, and selected
molecular validation of predicted resistant variants.
The project will create an automatically-updating, free, publically accessible, comprehensive data
repository of resistance-conferring variants. This will provide accurate genetic resistance prediction
for all drugs for any new MTBC WGS; superior design of near-to-patient amplification-based
molecular drug-resistance tests as alternatives to ‘WGS-only’ solutions; and better, faster and more
targeted drug-resistant TB treatment, facilitating improved control and WHO’s initiative to eliminate
TB by 2050.
drugs for whole genome sequencing (WGS) to replace slow, cumbersome, culture-based drug
susceptibility testing (DST) for Mycobacterium tuberculosis complex (MTBC). This would enable
rapid-turnaround near-to-patient assays to revolutionize drug-resistant TB identification and
management.
This multidisciplinary collaboration including TB experts from five continents, WHO,
statisticians/mathematicians and software engineers will integrate machine-learning, statistical
genetics and molecular genetics methods to uncover all genomic variation causing at least 1%
resistance to first- and second-line anti-TB drugs with >1% resistance prevalence. We will use largescale
global and clade-representative WGS (>90,000), with initially >37,000 isolates with extended DST. Approaches include better WGS assembly to identify more variants with more precision,
improved statistical methods to detect associations between variants and DST, and selected
molecular validation of predicted resistant variants.
The project will create an automatically-updating, free, publically accessible, comprehensive data
repository of resistance-conferring variants. This will provide accurate genetic resistance prediction
for all drugs for any new MTBC WGS; superior design of near-to-patient amplification-based
molecular drug-resistance tests as alternatives to ‘WGS-only’ solutions; and better, faster and more
targeted drug-resistant TB treatment, facilitating improved control and WHO’s initiative to eliminate
TB by 2050.
Organisations
- University of Oxford (Lead Research Organisation)
- Otsuka Pharmaceutical (Collaboration)
- University of California, San Francisco (Collaboration)
- Swiss Tropical & Public Health Institute (Collaboration)
- University of Antwerp (Collaboration)
- EMBL European Bioinformatics Institute (EMBL - EBI) (Collaboration)
- Fidelity Management & Research (Collaboration)
- Icahn School of Medicine at Mount Sinai (Collaboration)
- IML red GmbH (Collaboration)
- Foundation for Innovative New Diagnostics (FIND) (Collaboration)
- HARVARD UNIVERSITY (Collaboration)
- San Raffaele Hospital (Collaboration)
- PUBLIC HEALTH ENGLAND (Collaboration)
- Cayetano Heredia University (Collaboration)
- P. D. Hinduja Hospital and Medical Research Centre (Collaboration)
- Centers for Disease Control Taiwan (Collaboration)
- Instituto Adolfo Lutz (Collaboration)
- Emory University (Collaboration)
- London School of Hygiene and Tropical Medicine (LSHTM) (Collaboration)
- National University of Singapore (Collaboration)
- The Global Alliance for TB Drug Development (Collaboration)
- University of Lille (Collaboration)
- Chinese Center for Disease Control and Prevention (China CDC) (Collaboration)
- Yale University (Collaboration)
- UNIVERSITY OF BRITISH COLUMBIA (Collaboration)
- Monash University (Collaboration)
- NHS Lothian (Collaboration)
- University of Sydney (Collaboration)
- Wits Health Consortium (Collaboration)
- Indian Council of Medical Research (ICMR) (Collaboration)
- Royal Centre for Disease Control (Collaboration)
- Janssen Pharmaceutica NV (Collaboration)
- Borstel Research Centre (Collaboration)
- Stockholm University (Collaboration)
- Centre for HIV and Sexually Transmitted Infections, National Institute for Communicable Diseases, National Health Laboratory Service in Johannesburg (Collaboration)
- Public Health Wales NHS Trust (Collaboration)
- Stellenbosch University (Collaboration)
- National Institute for Public Health and Environment (RIVM) (Collaboration)
- UNIVERSITY OF LIVERPOOL (Collaboration)
- Public Health Ontario (Collaboration)
- Critical Path to TB Drug Regimens (CPTR) (Collaboration)
- University of Cape Town (Collaboration)
- World Health Organization (WHO) (Collaboration)
- Centers for Disease Control and Prevention (CDC) (Collaboration)
- Trinity College Dublin (Collaboration)
- IMPERIAL COLLEGE LONDON (Collaboration)
- Wadsworth Center (Collaboration)
- Africa Health Research Institute (Collaboration)
- Pasteur Institute of Madagascar (Collaboration)
People |
ORCID iD |
Publications
Carter J
(2019)
Prediction of Pyrazinamide Resistance in <i>Mycobacterium Tuberculosis</i> Using Structure-Based Machine Learning Approaches
in SSRN Electronic Journal
CRyPTIC Consortium And The 100,000 Genomes Project
(2018)
Prediction of Susceptibility to First-Line Tuberculosis Drugs by DNA Sequencing.
in The New England journal of medicine
Donovan J
(2020)
Xpert MTB/RIF Ultra for the Diagnosis of Tuberculous Meningitis: A Small Step Forward.
in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
Dreyer V
(2021)
Transmission of pre-XDR and XDR-TB in the Mumbai Metropolitan Region, India
in SSRN Electronic Journal
Ezewudo M
(2018)
Integrating standardized whole genome sequence analysis with a global Mycobacterium tuberculosis antibiotic resistance knowledgebase.
in Scientific reports
Fowler PW
(2018)
Automated detection of bacterial growth on 96-well plates for high-throughput drug susceptibility testing of Mycobacterium tuberculosis.
in Microbiology (Reading, England)
Fowler PW
(2019)
Corrigendum: Automated detection of bacterial growth on 96-well plates for high-throughput drug susceptibility testing of Mycobacterium tuberculosis.
in Microbiology (Reading, England)
Grobbel HP
(2021)
Design of Multidrug-Resistant Tuberculosis Treatment Regimens Based on DNA Sequencing.
in Clinical infectious diseases : an official publication of the Infectious Diseases Society of America
Hunt M
(2019)
Antibiotic resistance prediction for Mycobacterium tuberculosis from genome sequence data with Mykrobe.
in Wellcome open research
Kouchaki S
(2019)
Application of machine learning techniques to tuberculosis drug resistance analysis.
in Bioinformatics (Oxford, England)
Kouchaki S
(2020)
Multi-Label Random Forest Model for Tuberculosis Drug Resistance Classification and Mutation Ranking
in Frontiers in Microbiology
Liu D
(2022)
Whole-genome sequencing for surveillance of tuberculosis drug resistance and determination of resistance level in China.
in Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases
Rancoita PMV
(2018)
Validating a 14-Drug Microtiter Plate Containing Bedaquiline and Delamanid for Large-Scale Research Susceptibility Testing of Mycobacterium tuberculosis.
in Antimicrobial agents and chemotherapy
Walker TM
(2022)
The 2021 WHO catalogue of Mycobacterium tuberculosis complex mutations associated with drug resistance: A genotypic analysis.
in The Lancet. Microbe
Wang XN
(2018)
Prevalence of and risk factors for tuberculosis among healthcare workers in Chinese tuberculosis facilities.
in Infectious diseases of poverty
Wilson DJ
(2020)
GenomegaMap: Within-Species Genome-Wide dN/dS Estimation from over 10,000 Genomes.
in Molecular biology and evolution
Yang Y
(2021)
An end-to-end heterogeneous graph attention network for Mycobacterium tuberculosis drug-resistance prediction.
in Briefings in bioinformatics
Yang Y
(2019)
DeepAMR for predicting co-occurrent resistance of Mycobacterium tuberculosis.
in Bioinformatics (Oxford, England)
Yang-Turner F
(2018)
An Open-Source Azure Solution for Scalable Genomics Workflows
| Title | Susceptible by Anna Dumitriu |
| Description | Artist in Residence Anna Dumitriu has created a data-driven interactive digital artwork based on research from the CRyPTIC project. |
| Type Of Art | Artistic/Creative Exhibition |
| Year Produced | 2020 |
| Impact | A video version of Susceptible has been featured in 3 international exhibitions: - Neural Network Apophenia as part of the EVERART Festival in Moscow, Russia (3rd July and 3rd August 2020) - EFECT DE LA MICRO LA MACRO as part of Quantum Questions 2020 in Cluj-Napoca, Romania (24th November to 12th December 2020) - Artificio at the Museo Bolivariano De Arte Contemporaneo in Santa Marta, Colombia (20th October 2021 - on going) |
| URL | https://annadumitriu.co.uk/portfolio/susceptible/ |
| Description | Better predicting TB antituberculosis drug resistance and used by diagnostic tests |
| First Year Of Impact | 2022 |
| Sector | Healthcare |
| Impact Types | Policy & public services |
| Description | The WHO TB mutation catalogue |
| Geographic Reach | Multiple continents/international |
| Policy Influence Type | Citation in other policy documents |
| Impact | The impacts have been as follows; 1. Provides a systematic knowledge base for determining genomic susceptibility of TB to anti-tuberculosis drugs 2. This is used to guide improved rapid diagnostic tests supported by the World Health Organisation (WHO) 3. Provides improved resistance prediction for genome sequencing diagnostic results 4. Strengthens personalised treatment of multiresistant TB 5. Simplifies and improves patient management pathways for TB 6. Lilley to improve outcomes in the treatment of TB |
| URL | https://www.who.int/publications/i/item/9789240028173 |
| Description | Enriching Engagement - broadening and deepening public participation in BashTheBug.net |
| Amount | £20,429 (GBP) |
| Organisation | Wellcome Trust |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 11/2019 |
| End | 09/2020 |
| Description | Establishing a statistically confidence-graded catalogue of TB mutations catalogue for WHO review |
| Amount | $112,731 (USD) |
| Organisation | Foundation for Innovative New Diagnostics (FIND) |
| Sector | Charity/Non Profit |
| Country | Switzerland |
| Start | 01/2020 |
| End | 07/2021 |
| Description | HPRU HAI and AMR |
| Amount | £5,761,932 (GBP) |
| Funding ID | NIHR200915 |
| Organisation | National Institute for Health Research |
| Sector | Public |
| Country | United Kingdom |
| Start | 04/2020 |
| End | 03/2025 |
| Description | Innovations' Innovator award, SP3: Scalable Software for Pathogen Reads to Clinical Research using Next Generation Sequencing |
| Amount | £1,029,833 (GBP) |
| Funding ID | 215800/Z/19/Z |
| Organisation | Wellcome Trust |
| Sector | Charity/Non Profit |
| Country | United Kingdom |
| Start | 03/2020 |
| End | 02/2022 |
| Title | Pipeline developed to analyse TB WGS including SNPs and indels |
| Description | A pipeline has been developed improving existing pipelines to identify both SNPs and Indels in TB WGS., |
| Type Of Material | Improvements to research infrastructure |
| Year Produced | 2018 |
| Provided To Others? | No |
| Impact | None yet |
| Title | CRyPTIC Resistance Prediction catalogue |
| Description | Catalogue outlining the Mtb resistance-conferring mutations for antimicrobial drugs based on existing literature and publications. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2019 |
| Provided To Others? | Yes |
| Impact | No impact yet, but has been passed others in similar fields to compare to their own catalogue. |
| Title | CliRes database hosted at OUCRU to collect DST and epidemiological data from across the world |
| Description | A database hosted at Oxford University Clinical Research Unit which allows all sites acros the world to record DST results and epidemiological data relating to the patients and isolates which can be accessed by the analyses team. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2017 |
| Provided To Others? | No |
| Impact | ability to record data from all sites in a formatted way to allow analyses team to systematically align WGS with DST data |
| Title | Data collection of Mtb whole genome sequences and metadata |
| Description | Dataset of approximately 15,000 Mtb whole geneome sequences and metadata (phenotype data) from across the world to contibute the CRyPTIC dataset. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2020 |
| Provided To Others? | No |
| Impact | Contributes to the CRyPTIC dataset |
| Title | MTB WGS database |
| Description | A database containing approximately 55,000 Mtb Whole Genome sequences and variant calling from participating sites across the world and downloaded from ENA |
| Type Of Material | Database/Collection of data |
| Year Produced | 2018 |
| Provided To Others? | No |
| Impact | Generation of the Mtb Resistance prediction catalogue and provides a dataset for validation. |
| Description | China CDC collaboration |
| Organisation | Chinese Center for Disease Control and Prevention (China CDC) |
| Country | China |
| Sector | Public |
| PI Contribution | Coordination of project and analyses of DST and WGS from approximately 100,000 clinical TB isolates across the world to determine whether antimicrobial resistance can be predicted through whole genome sequencing. |
| Collaborator Contribution | Contribute ~3100 WGS and DST from TB clinical isolates. Contibute to the analyses of the data and help identify further research questions and opportunties arising from the dataset. Member of the General Assembly |
| Impact | No outcome as yet, project just started. |
| Start Year | 2016 |
| Description | Collaboration Aldolfo Lutz |
| Organisation | Instituto Adolfo Lutz |
| Country | Brazil |
| Sector | Public |
| PI Contribution | Co-ordination of the project and analyses of DST and WGS from approximately 100,000 TB clinical isoaltes across the world to determine whether antimicrobial resistance can be predicted through WGS |
| Collaborator Contribution | Contribute DST and WGS from 400 TB isolates. Contibute to analyses and help identify research opportunities and questions from dataset. Member of the general assembly |
| Impact | None, project just started |
| Start Year | 2016 |
| Description | Collaboration CPTR |
| Organisation | Critical Path to TB Drug Regimens (CPTR) |
| Country | United States |
| Sector | Public |
| PI Contribution | Co-ordination of the project and analyses of DST and WGS from approximately 100,000 TB clinical samples across the world to determine whether antimicrobial resistance can be predicted through WGS. |
| Collaborator Contribution | Assistance with co-ordination at the start of project. Financial assistance to sequence 1000 TB genomes Work closely on data interoperability with regards to TB |
| Impact | None, project just started |
| Start Year | 2016 |
| Description | Collaboration EBI |
| Organisation | EMBL European Bioinformatics Institute (EMBL - EBI) |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | co-ordination ofthe project and analyses of DST and WGS from approximately 100,000 TB clinical samples across the world to determine whether antimicrobial resistance can be predicted from WGS. |
| Collaborator Contribution | Co-applicant Zamin Iqbal has moved to EBI. EBI will be developing and and hosting the "data warehouse" allowing the upload of sequences generated across the world for view initially by the research team and them open access. Will be developing variant calling software for the sequences. |
| Impact | None, project just started. |
| Start Year | 2017 |
| Description | Collaboration Janssen |
| Organisation | Janssen Pharmaceutica NV |
| Country | Belgium |
| Sector | Private |
| PI Contribution | Co-ordination of project and analyse of DST and WGS from approximately 100,000 TB clinical samples across the world to determine whether antimicrobial resistance can be predicted through WGS |
| Collaborator Contribution | Provide research service to allow bedaquiline testing in Taiwan using microtitre plates. Provide bedaquiline for inclusion of the CRyPTIC generated DST plates. Provide general advice regarding microtitre DST and bedaquiline. |
| Impact | Microtitre DST plate for use under CRyPTIC project |
| Start Year | 2016 |
| Description | Collaboration NICD |
| Organisation | Centre for HIV and Sexually Transmitted Infections, National Institute for Communicable Diseases, National Health Laboratory Service in Johannesburg |
| Country | South Africa |
| Sector | Hospitals |
| PI Contribution | Coodination of project and analyses of DST and WGS from approximately 100,000 TB clinical samples across the world to determine whether antimicrobial resistance can be predicted through WGS |
| Collaborator Contribution | Contribute WGS and DST from 2300 TB clinical isolates. Contribute to the analyses and help identify further research opportunities and questions arising from the data. Member of the General Assembly |
| Impact | No output, project just started |
| Start Year | 2016 |
| Description | Collaboration with AHRI |
| Organisation | Africa Health Research Institute |
| Country | South Africa |
| Sector | Charity/Non Profit |
| PI Contribution | Building of a Mtb resistance prediction catalogue by running 10,000s Mtb sequences through the CRyPTIC variant calling pipeline and identifying rare resistance conferring variants. Sharing the catalogue with the community. Providing support for clinical outcome analyses of drug resistant Mtb |
| Collaborator Contribution | Providing 100 WGS, extensive phenotype data and clinical data for MDR-Mtb. |
| Impact | No output |
| Start Year | 2018 |
| Description | Collaboration with AHRI |
| Organisation | University of Liverpool |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Building of a Mtb resistance prediction catalogue by running 10,000s Mtb sequences through the CRyPTIC variant calling pipeline and identifying rare resistance conferring variants. Sharing the catalogue with the community. Providing support for clinical outcome analyses of drug resistant Mtb |
| Collaborator Contribution | Providing 100 WGS, extensive phenotype data and clinical data for MDR-Mtb. |
| Impact | No output |
| Start Year | 2018 |
| Description | Collaboration with Atlanta CDC |
| Organisation | Centers for Disease Control and Prevention (CDC) |
| Country | United States |
| Sector | Public |
| PI Contribution | Co-ordination of project and analyses of DST and WGS from approximately 100,000 TB Clinical samples across the world to determine whether antimicrobial resistance can be predicted through WGS |
| Collaborator Contribution | validation of novel gene variants conferring resistance to antimicrobials. Member of the General Assembly |
| Impact | No outputs, project just started. |
| Start Year | 2016 |
| Description | Collaboration with Bhutan |
| Organisation | Royal Centre for Disease Control |
| Country | Bhutan |
| Sector | Academic/University |
| PI Contribution | Building a Mtb resistance prediction catalogue by running 10,000s of Mtb WGS thought a variant calling pipeline and identifying rare resistance-conferring variants. Sharing the catalogue with the community |
| Collaborator Contribution | Contributing 1000 Mtb WGS and phenotype data |
| Impact | No output |
| Start Year | 2018 |
| Description | Collaboration with Emory |
| Organisation | Emory University |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | Provide analysis of a large Mtb sequence and phenotype dataset |
| Collaborator Contribution | Donation of Mtb sequences and phenotypes |
| Impact | None yet |
| Start Year | 2020 |
| Description | Collaboration with Germany |
| Organisation | Borstel Research Centre |
| Country | Germany |
| Sector | Private |
| PI Contribution | Co-ordination of the project and analyses of DST and WGS from approximately 100,000 TB clinical isolates across the world to determine whether antimicrobial resistacnce can be predicted through WGS. |
| Collaborator Contribution | Contribute WGS and DST from 2000 TB clinical isolates. Contribute to analyses and help identify further research questions from dataset. Members of the General Assembly |
| Impact | No output, project just started. |
| Start Year | 2016 |
| Description | Collaboration with Germany |
| Organisation | IML red GmbH |
| Department | Institute of Microbiology and Laboratory Medicine |
| Country | Germany |
| Sector | Learned Society |
| PI Contribution | Co-ordination of the project and analyses of DST and WGS from approximately 100,000 TB clinical isolates across the world to determine whether antimicrobial resistacnce can be predicted through WGS. |
| Collaborator Contribution | Contribute WGS and DST from 2000 TB clinical isolates. Contribute to analyses and help identify further research questions from dataset. Members of the General Assembly |
| Impact | No output, project just started. |
| Start Year | 2016 |
| Description | Collaboration with Harvard |
| Organisation | Harvard University |
| Department | Harvard Medical School |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | Provide analysis of a large Mtb sequence and phenotype dataset |
| Collaborator Contribution | Donation of Mtb sequence and phenotype data |
| Impact | None yet |
| Start Year | 2020 |
| Description | Collaboration with IPM |
| Organisation | Pasteur Institute of Madagascar |
| Country | Madagascar |
| Sector | Academic/University |
| PI Contribution | Building a Mtb resistance prediction catalogue by running 10,000s of Mtb sequences from across the world through the CRyPTIC variant calling pipeline and identifying rare variants. Sharing knowledge with the community. |
| Collaborator Contribution | Contributing 668 Mtb WGS and phenotype data to the project |
| Impact | No outcome yet |
| Start Year | 2018 |
| Description | Collaboration with Monash |
| Organisation | Monash University |
| Country | Australia |
| Sector | Academic/University |
| PI Contribution | Provide analysis of a large Mtb sequence and phenotype dataset |
| Collaborator Contribution | Donation of Mtb sequences and phenotypes |
| Impact | None yet |
| Start Year | 2020 |
| Description | Collaboration with National University of Singapore |
| Organisation | National University of Singapore |
| Country | Singapore |
| Sector | Academic/University |
| PI Contribution | Analyses of WGS and DST data from samples collected as part of clinical trial in Philippines |
| Collaborator Contribution | Contribution of WGS and DST data from samples collected as part of clinical trail in Philliipines. Funding provided by collaborator. |
| Impact | No outputs yet |
| Start Year | 2017 |
| Description | Collaboration with Ontario |
| Organisation | Public Health Ontario |
| Country | Canada |
| Sector | Hospitals |
| PI Contribution | Provide analysis of a large Mtb sequence and phenotype dataset |
| Collaborator Contribution | Donate Mtb Sequence and metadata |
| Impact | None yet |
| Start Year | 2020 |
| Description | Collaboration with Otsuka |
| Organisation | Otsuka Pharmaceutical |
| Country | Japan |
| Sector | Private |
| PI Contribution | Coordination of project and analses of DST and WGS from approximately 100,000 TB clinical samples from across the world to determine whether antimicrobial resistance can be predicted through WGS |
| Collaborator Contribution | provided Delamind for the microtitre DST plates used under the project which is not commercially available. |
| Impact | Microtitre plate containing delamanid manufactured by Thermofisher for research use only. |
| Start Year | 2016 |
| Description | Collaboration with PHW |
| Organisation | Public Health Wales NHS Trust |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | Provide analysis of a large Mtb sequence and phenotype dataset |
| Collaborator Contribution | Donate Mtb sequences and phenotype data |
| Impact | None yet |
| Start Year | 2019 |
| Description | Collaboration with Public Health Sweden |
| Organisation | Stockholm University |
| Department | Public Health |
| Country | Sweden |
| Sector | Academic/University |
| PI Contribution | Analyses of the WGS and DST data generated on clinical isolates from Sweden as part of the CRyPTIC objectives. |
| Collaborator Contribution | Contibution of DST and DST data generated from clinical isolates. |
| Impact | No outputs to date |
| Start Year | 2017 |
| Description | Collaboration with SRI |
| Organisation | San Raffaele Hospital |
| Country | Italy |
| Sector | Hospitals |
| PI Contribution | Co-ordination of project and analyses of DST and WGS from approximately 100,000 TB clinical samples across the world to determine whether antimicrobial resistance can be predicted through WGS |
| Collaborator Contribution | Contribute to WGS and DST from 2000 clinical isolates. Contribute to the analyses and help identify further research quesitons and opportunity from data. Member of the General Assembly |
| Impact | No output, project just started. |
| Start Year | 2016 |
| Description | Collaboration with South Africa |
| Organisation | Wits Health Consortium |
| Country | South Africa |
| Sector | Private |
| PI Contribution | Co-ordination of the project and analyses of DST and WGS fro approximately 100,000 TB clinical samples across the world to determine whether antimicrobial resistance can be predicted through WGS |
| Collaborator Contribution | Legal entity for National Institute of Communicable Diseases, Johannesberg, South Africa |
| Impact | No output yet, project only just started. |
| Start Year | 2016 |
| Description | Collaboration with Swisstph |
| Organisation | Swiss Tropical & Public Health Institute |
| Country | Switzerland |
| Sector | Academic/University |
| PI Contribution | Provide analysis of a large Mtb sequence and phenotype dataset |
| Collaborator Contribution | Donation of Mtb sequences and phenotypes |
| Impact | None yet |
| Start Year | 2020 |
| Description | Collaboration with Taiwan |
| Organisation | Centers for Disease Control Taiwan |
| Country | Taiwan, Province of China |
| Sector | Public |
| PI Contribution | Analyses DST and WGS data of clinical isolates from Taiwan as part of worldwide dataset |
| Collaborator Contribution | Contributing DST and WGS data from Taiwan |
| Impact | No output yet |
| Start Year | 2017 |
| Description | Collaboration with Torch consortium |
| Organisation | University of Antwerp |
| Country | Belgium |
| Sector | Academic/University |
| PI Contribution | building a Mtb resistance prediction catalogue by running 10,000s of Mtb sequences through the variant calling pipeline and identifying rare variants conferring resistance. Sharing the catalogue with the community. Providing support with secondary projects using the data, such as machine learning. |
| Collaborator Contribution | Contributing ~1200 Mtb and phenotype data to the cryptic consortium |
| Impact | None yet |
| Start Year | 2018 |
| Description | Collaboration with Torch consortium |
| Organisation | University of Stellenbosch |
| Country | South Africa |
| Sector | Academic/University |
| PI Contribution | building a Mtb resistance prediction catalogue by running 10,000s of Mtb sequences through the variant calling pipeline and identifying rare variants conferring resistance. Sharing the catalogue with the community. Providing support with secondary projects using the data, such as machine learning. |
| Collaborator Contribution | Contributing ~1200 Mtb and phenotype data to the cryptic consortium |
| Impact | None yet |
| Start Year | 2018 |
| Description | Collaboration with Trinity College Dublin |
| Organisation | Trinity College Dublin |
| Country | Ireland |
| Sector | Academic/University |
| PI Contribution | Provide analysis of a large Mtb sequence and phenotype dataset |
| Collaborator Contribution | Donation of Mtb sequence and phenotype data |
| Impact | None yet |
| Start Year | 2020 |
| Description | Collaboration with UCSF |
| Organisation | University of California, San Francisco |
| Department | School of Medicine (UCSF) |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | Provide analysis of a large Mtb sequence and phenotype dataset |
| Collaborator Contribution | Donate Mtb sequences and phenotype data. |
| Impact | None yet |
| Start Year | 2020 |
| Description | Collaboration with Uni Peruana Cayetano Heredia |
| Organisation | Cayetano Heredia University |
| Country | Peru |
| Sector | Academic/University |
| PI Contribution | Co-ordination of project and analyses of DAT and WGS from approximately 100,000 TB clinical samples across the world to determine whether antimicrobial resistance can be predicted through WGS |
| Collaborator Contribution | Contribute 3100 WGS and DST data from TB clinical isolates. Contibute to analyses and help identify further research opportunities and questions arising from the dataset. |
| Impact | None as yet as project just started. |
| Start Year | 2016 |
| Description | Collaboration with Wadsworth |
| Organisation | Wadsworth Center |
| Country | United States |
| Sector | Public |
| PI Contribution | Building a Mtb resistance prediction catalogue by running 10,000s of Mtb sequences through the variant calling pipeline and identifying rare reistance conferring mutations. Sharing the catalogue with the community. |
| Collaborator Contribution | Contribution of Mtb 780 WGS and phenotype data |
| Impact | No output |
| Start Year | 2018 |
| Description | Collaboration with Yale |
| Organisation | Yale University |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | Building a Mtb resistance prediction catalogue by running 10,000s of Mtb WGS though the variant calling pipeline and identifying rare resistance conferring mutations. Sharing the cataogue with the community |
| Collaborator Contribution | Contribution of 500 MTb WGS and Phenoptye data |
| Impact | No output |
| Start Year | 2018 |
| Description | Collaboration with sites providing existing data and advisors |
| Organisation | Imperial College London |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Co-ordination of the project and analyses of WGS and DST from approximately 100,000 TB clinical isolates across the world to determine whether antimicrobial resistance can be predicted through whole genome sequencing |
| Collaborator Contribution | Contibution of existing WGS and DST from TB isolates. Contribution to analyses and help identify further research questions from the dataset. Members of the General Assembly |
| Impact | None, project just started |
| Start Year | 2016 |
| Description | Collaboration with sites providing existing data and advisors |
| Organisation | NHS Lothian |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | Co-ordination of the project and analyses of WGS and DST from approximately 100,000 TB clinical isolates across the world to determine whether antimicrobial resistance can be predicted through whole genome sequencing |
| Collaborator Contribution | Contibution of existing WGS and DST from TB isolates. Contribution to analyses and help identify further research questions from the dataset. Members of the General Assembly |
| Impact | None, project just started |
| Start Year | 2016 |
| Description | Collaboration with sites providing existing data and advisors |
| Organisation | University of British Columbia |
| Country | Canada |
| Sector | Academic/University |
| PI Contribution | Co-ordination of the project and analyses of WGS and DST from approximately 100,000 TB clinical isolates across the world to determine whether antimicrobial resistance can be predicted through whole genome sequencing |
| Collaborator Contribution | Contibution of existing WGS and DST from TB isolates. Contribution to analyses and help identify further research questions from the dataset. Members of the General Assembly |
| Impact | None, project just started |
| Start Year | 2016 |
| Description | Collaboration with sites providing existing data and advisors |
| Organisation | University of Cape Town |
| Country | South Africa |
| Sector | Academic/University |
| PI Contribution | Co-ordination of the project and analyses of WGS and DST from approximately 100,000 TB clinical isolates across the world to determine whether antimicrobial resistance can be predicted through whole genome sequencing |
| Collaborator Contribution | Contibution of existing WGS and DST from TB isolates. Contribution to analyses and help identify further research questions from the dataset. Members of the General Assembly |
| Impact | None, project just started |
| Start Year | 2016 |
| Description | Collaboration with the Netherlands Public Health RIVM |
| Organisation | National Institute for Public Health and Environment (RIVM) |
| Country | Netherlands |
| Sector | Academic/University |
| PI Contribution | Provide analysis of a large Mtb sequence and phenotype dataset |
| Collaborator Contribution | donate Mtb Sequences and phenotype |
| Impact | None yet |
| Start Year | 2020 |
| Description | External Advisory Board |
| Organisation | Foundation for Innovative New Diagnostics (FIND) |
| Country | Switzerland |
| Sector | Charity/Non Profit |
| PI Contribution | Coordination of the project and analyses of DST and WGS from approximately 100,000 TB clinical samples across the world to determine whether antimicrobial resistance can be predicted through WGS |
| Collaborator Contribution | External Advisory Board i) providing advice on resolution of problems identified by the Executive Committee; and ii) reviewing and monitoring overall progress of the project and providing advice to the Executive Committee with regards to achieving deliverables; and iii) providing strategic oversight of effective dissemination, publication and deployment of project aims and outputs. |
| Impact | No output project just started. |
| Start Year | 2016 |
| Description | External Advisory Board |
| Organisation | Indian Council of Medical Research (ICMR) |
| Country | India |
| Sector | Public |
| PI Contribution | Coordination of the project and analyses of DST and WGS from approximately 100,000 TB clinical samples across the world to determine whether antimicrobial resistance can be predicted through WGS |
| Collaborator Contribution | External Advisory Board i) providing advice on resolution of problems identified by the Executive Committee; and ii) reviewing and monitoring overall progress of the project and providing advice to the Executive Committee with regards to achieving deliverables; and iii) providing strategic oversight of effective dissemination, publication and deployment of project aims and outputs. |
| Impact | No output project just started. |
| Start Year | 2016 |
| Description | External Advisory Board |
| Organisation | University of Lille |
| Country | France |
| Sector | Academic/University |
| PI Contribution | Coordination of the project and analyses of DST and WGS from approximately 100,000 TB clinical samples across the world to determine whether antimicrobial resistance can be predicted through WGS |
| Collaborator Contribution | External Advisory Board i) providing advice on resolution of problems identified by the Executive Committee; and ii) reviewing and monitoring overall progress of the project and providing advice to the Executive Committee with regards to achieving deliverables; and iii) providing strategic oversight of effective dissemination, publication and deployment of project aims and outputs. |
| Impact | No output project just started. |
| Start Year | 2016 |
| Description | External Advisory Board |
| Organisation | World Health Organization (WHO) |
| Country | Global |
| Sector | Public |
| PI Contribution | Coordination of the project and analyses of DST and WGS from approximately 100,000 TB clinical samples across the world to determine whether antimicrobial resistance can be predicted through WGS |
| Collaborator Contribution | External Advisory Board i) providing advice on resolution of problems identified by the Executive Committee; and ii) reviewing and monitoring overall progress of the project and providing advice to the Executive Committee with regards to achieving deliverables; and iii) providing strategic oversight of effective dissemination, publication and deployment of project aims and outputs. |
| Impact | No output project just started. |
| Start Year | 2016 |
| Description | FIND/WHO collaboration |
| Organisation | Foundation for Innovative New Diagnostics (FIND) |
| Country | Switzerland |
| Sector | Charity/Non Profit |
| PI Contribution | - Provide a catalogue of variants conferring anti-tuberculosis drug resistance classified by strength of supporting statistical evidence - Provide a working cloud based whole genome sequence analysis pipeline for FASTQ processing, variant calling, resistance prediction and cluster analysis in World Health Organisation AWS environment - Provide working STATA analysis code for analysis of the combined genomic and phenotypic data quantifying the association between DR mutations and phenotypic resistance yielding LRs and ORs in WHO AWS environment - Complete transfer of all genotypic and phenotypic data used for creation of mutation catalogue to WHO AWS environment |
| Collaborator Contribution | Provided funding and intellectual input and support delivery of the objectives. Facilitated access to additional WGS datasets to allow further building of drug resistance prediction catalogue. |
| Impact | No outcomes yet, grant is still active. |
| Start Year | 2020 |
| Description | FMR Collaboration |
| Organisation | Fidelity Management & Research |
| Country | India |
| Sector | Private |
| PI Contribution | Lead institution contributing to analysis of the TB WGS and DST results from the project |
| Collaborator Contribution | Providing ~6000 WGS on TB clinical samples and some DST results. Contribute to analyses and help identify research questions from dataset. Member of the General Assembly |
| Impact | The project has just started, DNA extracted from clinical TB samples and sent for sequencing. PZA DST results generated by FMR |
| Start Year | 2016 |
| Description | Hinduja Hosp Collaboration |
| Organisation | P. D. Hinduja Hospital and Medical Research Centre |
| Country | India |
| Sector | Hospitals |
| PI Contribution | Lead Insitution, coordinator and analyses of WGS and DST from TB clinical samples across the world. |
| Collaborator Contribution | Will provide DST information on ~6000 clinical TB isolates. Contribute to analyses and help identify further research questions from data. Member of the General Assembly |
| Impact | None yet, project just started. |
| Start Year | 2016 |
| Description | PacBio sequencing |
| Organisation | Icahn School of Medicine at Mount Sinai |
| Country | United States |
| Sector | Academic/University |
| PI Contribution | Investigation of plasmid structure |
| Collaborator Contribution | Sequencing and analysis Member of the CRyPTIC General Assembly. Member of REHAB Steering Committee |
| Impact | Two publications |
| Start Year | 2014 |
| Description | Provision of Pretomanid by TB alliance |
| Organisation | The Global Alliance for TB Drug Development |
| Country | Global |
| Sector | Private |
| PI Contribution | Provided evidence for the use of a microtitre plate for dried antibiotics as a method of phenotyping Mtb isolates |
| Collaborator Contribution | Providing pretonamid drug on a microtitre plate intended to be available commercially. |
| Impact | None yet |
| Start Year | 2019 |
| Description | Public Health England (PHE) |
| Organisation | Public Health England |
| Country | United Kingdom |
| Sector | Public |
| PI Contribution | Access to sequencing data and research results. |
| Collaborator Contribution | Access to S. aureus, Norovirus, C. difficile and TB samples and related epidemiological data. Staff to collect the samples and data and to ship this to Oxford and the Wellcome Trust Sanger Institute for sequencing. As well as intellectual input into the research. Member of REHAB Steering Committee |
| Impact | Successful translation of next generation sequencing into public health microbiology |
| Start Year | 2009 |
| Description | World Health Organisation contribution of data |
| Organisation | World Health Organization (WHO) |
| Country | Global |
| Sector | Public |
| PI Contribution | Building a resistance prediction catalogue by running 10000s of Mtb sequences though pathogen variant calling pipeline, identifying rare variants and sharing with the community. |
| Collaborator Contribution | Provided Mtb WGS and phenotype data from around 3000 isolates from drug surveillance project |
| Impact | Contribution of resistance conferring mutations to the CRyPTIC resistance calling catalogue. |
| Start Year | 2018 |
| Description | collaboration with LSHTM |
| Organisation | London School of Hygiene and Tropical Medicine (LSHTM) |
| Department | Malaria Centre |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | Coordination of project and analyses of DST and WGS from approximately 100,000 WGS TB clinical isolates. across the world to determine whether antimicrobial resisatnce can be predicted through WGS. |
| Collaborator Contribution | Subcontracting to Universidad Peruana Cayetano Heredia. Member of the General Assembly |
| Impact | No output as yet as project just started. |
| Start Year | 2016 |
| Description | collaboration with University of Sydney |
| Organisation | University of Sydney |
| Country | Australia |
| Sector | Academic/University |
| PI Contribution | Provide analysis of a large Mtb sequence and phenotype dataset |
| Collaborator Contribution | donation of Mtb sequences and phenotypes |
| Impact | None yet |
| Start Year | 2020 |
| Title | AMyGDA -Automated Detection of Bacterial Growth on 96-well plates (AMyGDA) |
| Description | This software automatically identifies whether there is Mtb growth in each well of a 96 well plate containing a range of anti-microbials to establish the minimum inhibitory concentration per drug for each isolate using plate images taken by Vizion (from Thermofisher). As the project progresses, we will be using this as a method of quality control and will re-evaluate any plates where the manual MIC reading for any drug has more than 1 doubling dilution difference to determine reading errors. Additionally, this software can be expanded to other plates and other drugs for other bacteria so is transferrable. |
| IP Reference | |
| Protection | Copyrighted (e.g. software) |
| Year Protection Granted | 2017 |
| Licensed | Yes |
| Impact | Currently being considered by thermofisher to use with Vizion software instead of manually reading plates. Incorporated in CRyPTIC workflow to assign confidence in the MIC readings. |
| Title | Piezo |
| Description | Software which considers variant calling files from WGS pipeline Clockwork and applies a genetic resistance prediction catalogue to output predicted phenotype for 12 anti-tuberculosis drugs |
| IP Reference | |
| Protection | Copyrighted (e.g. software) |
| Year Protection Granted | 2019 |
| Licensed | No |
| Impact | None as yet. |
| Title | 13 drug anti-microbial microtitre plate |
| Description | 13 anti-microbial microtitre plate allows extensive phenotypic quantiative characterisation of a Mtb isolate using one cheap assay. The plates have been designed by the CRyPTIC team and manufactured by Thermofisher as a standard service, paid for from the CRyPTIC grant. We are currently seeking endorsement for the plate as a Mtb diagnostic tool from the World Health Organisation. It is only available to members of CRyPTIC in accordance with agreements in place with Otsuka and Janssen, we anticipate endorsement will lead to the plates being available to researchers and clinicians outside the project. |
| Type | Diagnostic Tool - Non-Imaging |
| Current Stage Of Development | Refinement. Non-clinical |
| Year Development Stage Completed | 2019 |
| Development Status | Actively seeking support |
| Impact | No impact yet. |
| Title | Piezo software |
| Description | Software which considers variant calling files generated from Clockwork pipeline and the genetics resistance calling catalogue and provides a predicted phenotype output for 13 different drugs. |
| Type Of Technology | Software |
| Year Produced | 2019 |
| Impact | Allows swift phenotype prediction from the WGS files for CRyPTIC whole genome sequences. |
| Title | Software to automatically read CRyPTIC anti-tuberculosis microtitre plate (CRyPTIC_DST) |
| Description | One goal of CRyPTIC is to pursue a validation for regulatory approval of 96 well microtitre pates developed under CRyPTIC (UKMYC5 plates; Trek Sensititre manufactured in collaboration with Thermo Fisher) offering standardized minimum inhibitory concentrations (MIC) for 14 anti-tuberculosis drugs. Seven CRyPTIC collaborators across the world have performed intitial evaluation of this microtitre plate by performing extensive DST on a laboratory-adapted H37Rv MTBC strain followed by evaluation of a panel of well characterized drug resistant strains which were shipped for simultaneous testing by all sites. This initial evaluation involved reading the plates by three different methods: Inverted microscope, mirrored plate reader and Sensititre™ Vizion™ Digital MIC Viewing System (Vizion). Vizion allows the user to capture images which are analysed by the team in Oxford, however, all three methods of reading are subject to user interpretation which is likely to be dependent on experience reading anti-tuberculosis microtitre plates. CRyPTIC_DST is a Python module that analyses photographs of 96 well plates and determines the growth of bacteria in each well. Since each well contains a different concentration of antibiotic and there are 14 antibiotics on the plate, this data can be used to determine the minimum inhibitory concentrations of each antibiotic and hence the drug susceptibility profile of the M.tuberculosis pathogen. The code maintains a local copy of all the metadata for each plate locally in a filesystem-based tree, stored in JSON files. Data and image are automatically downloaded from the CRyPTIC SQL database using its WebService, thereby bypassing the browser. The photograph of each plate is first cleaned up by applying a mean shift algorithm and locally equalising the histograms. The code then iteratively searches for circles in the image using a Hough transform and stops if and only if 96 circles of approximately the correct radius are found. This defines the locations of the wells. A square of pixels in the middle of each well is analysed; specifically the proportion of pixels below a threshold are counted, and if there are sufficient, the well is classified as containing growth. Since the metadata are also stored locally, the results of the image algorithm can be directly compared to the human measurements. The code can be run on a consumer grade laptop and each image takes around 5 seconds to analyse. It is currently stored as a private GitHub repository and will be made public upon publication of the first CRyPTIC validation paper. |
| Type Of Technology | New/Improved Technique/Technology |
| Year Produced | 2017 |
| Impact | This has only just been developed and is currently being tested. Impact of this could minimise interlab and intralab variation of microtitre plate readings due and allow MIC determination irrespective of user experience |
| Description | Bacterial world - Oxford Natural History Museum |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Public/other audiences |
| Results and Impact | Showcasing Bash the Bug and encouraging particpation. |
| Year(s) Of Engagement Activity | 2018,2019 |
| URL | http://www.oum.ox.ac.uk/bacterialworld/ |
| Description | Bash the Bug |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | "Bash the bug" is a website which encourages members of the public to identify whether there is Mtb bacterial growth in a specific well of a 96 well plate containing anti-microbial drugs. These plates are being used as part of the CRyPTIC project, and the objective of this is to use multiple opinions to "call" growth or no growth in a well which is proving problematic to the experts. |
| Year(s) Of Engagement Activity | 2017,2018 |
| URL | https://www.zooniverse.org/projects/mrniaboc/bash-the-bug |
| Description | Discussing CRyPTIC on BBC world Service |
| Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | Prof Derrick Crook spoke about the CRyPTIC project and its impact on TB on News Hour on the BBC World Service Link: https://www.bbc.co.uk/sounds/play/w172xv5c54nxwch (segment starts ~35 minutes in) |
| Year(s) Of Engagement Activity | 2021 |
| URL | http://www.bbc.co.uk/sounds/play/w172xv5c54nxwch |
| Description | Economist article about CRyPTIC |
| Form Of Engagement Activity | A magazine, newsletter or online publication |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | Economist article about the CRyPTIC project and research outcomes: https://www.economist.com/science-and-technology/most-resistance-causing-mutations-in-tb-have-now-been-identified/21805727 |
| Year(s) Of Engagement Activity | 2021 |
| URL | http://www.economist.com/science-and-technology/most-resistance-causing-mutations-in-tb-have-now-bee... |
| Description | Microscope on Modernising Medical Microbiology |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Regional |
| Primary Audience | Public/other audiences |
| Results and Impact | Join scientists as they show us how the Modernising Medical Microbiology group is using DNA to forensically track the spread of infection, detect antibiotic resistance in tuberculosis more quickly and discover the genes responsible for making bacteria dangerous. |
| Year(s) Of Engagement Activity | 2019 |
| Description | New Scientist publication |
| Form Of Engagement Activity | A magazine, newsletter or online publication |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | Project described in New Scientist magazine focussing on the machine learning element. |
| Year(s) Of Engagement Activity | 2016 |
| URL | https://www.newscientist.com/article/mg23130923-000-genereading-software-to-cut-tb-diagnosis-from-mo... |
| Description | Press release |
| Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Public/other audiences |
| Results and Impact | Press release for CRyPTIC project |
| Year(s) Of Engagement Activity | 2016 |
| Description | Press releases for CRyPTIC project publications |
| Form Of Engagement Activity | A press release, press conference or response to a media enquiry/interview |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Press releases to highlight the CRyPTIC project, the manuscripts from this work that were submitted to journals, the WHO TB resistance catalogue, and a link to the CRyPTIC project data. - Oxford University: https://www.ox.ac.uk/news/2021-10-19-largest-ever-global-study-tuberculosis-identifies-genetic-causes-drug-resistance - EMBL-EBI: https://www.ebi.ac.uk/about/news/announcements/cryptic-cataloguing-drug-resistance-mutations-m-tuberculosis |
| Year(s) Of Engagement Activity | 2021 |
| URL | http://www.ox.ac.uk/news/2021-10-19-largest-ever-global-study-tuberculosis-identifies-genetic-causes... |
| Description | Radio Science - Live stream Q&A |
| Form Of Engagement Activity | A broadcast e.g. TV/radio/film/podcast (other than news/press) |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | Live stream involvment in an hour long, show with Q&A about Bash The Bug and the Zooniverse project |
| Year(s) Of Engagement Activity | 2020 |
| Description | Royal Society Summer Science Exhibtion |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | A Stall at Summer Science Exhibition showcasing the work undertaken under CRyPTIC and encouraging participation in Bash the Bug Community project. 1,000,000 reads from Bash the Bug were acheived in 2018. |
| Year(s) Of Engagement Activity | 2018 |
| Description | Science exhibition at school |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Schools |
| Results and Impact | KS2 Science exhibition for local school |
| Year(s) Of Engagement Activity | 2019 |
| Description | Set up patient panels |
| Form Of Engagement Activity | Participation in an activity, workshop or similar |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Public/other audiences |
| Results and Impact | We circulated an advert inviting members of the public to join patient panels to inform all aspects of the groups' work. Over 100 individuals responded, and we held two open meetings where different aspects of the work were presented. Following this smaller groups have been set up to review and advise on different projects. Members of the public have really valued the opportunity to get involved. |
| Year(s) Of Engagement Activity | 2014,2016 |
| Description | Webinar - planning and developing a zooinverse project. Bash the Bug |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Professional Practitioners |
| Results and Impact | Webinar explaining to audience how to set up, develop and manage a zooinverse project for citizen science projects. |
| Year(s) Of Engagement Activity | 2020 |