PathoLogic

PathoLogic is a point-of-care diagnostic platform that applies machine learning to genomic and phenotypic data to rapidly identify resistant pathogens and collect antimicrobial susceptibility data in resource-limited communities. By generating resistance trend insights, our solution aims to optimize antibiotic use and inform antimicrobial resistance policy through strengthened surveillance.

The Team Lead for our solution is Dr Jesca Chaula, who serves as the Primary Investigator. She is a molecular epidemiologist and expert in genomic surveillance of antimicrobial resistance.

A key challenge facing efforts to combat antimicrobial resistance (AMR) in sub-Saharan Africa and globally is limited surveillance data from resource-limited community settings, where the majority of antibiotics are consumed. In Tanzania, for example, surveillance relies on a small number of reference laboratories, yet over 90% of antibioticsare distributed elsewhere through informal markets and pharmacies without oversight. As a result, policy responses are not optimally targeted and the true burden of drug-resistant infections is unknown. 

Globally, AMR is estimated to directly cause over 1.2 million deaths annually according to the World Health Organization (WHO). The WHO warns this could rise to 10 million annual deaths by 2050 and cause cumulative economic damage of $100 trillion by 2050 if no action is taken. Low- and middle-income countries experience over 60% of the world's bacterial infections yet have limited funding and infrastructure for AMR monitoring. Our solution will address this challenge by strengthening data collection from underserved communities in Tanzania to enhance understanding of resistance trends, transmission dynamics, environmental spread and optimize resource allocation through more localized surveillance and evidence-based policymaking.

Our solution primarily serves underserved rural communities in Tanzania who currently have very limited access to antimicrobial resistance surveillance and diagnostics. This includes an estimated 5 million individuals across 5 regions including, Dar es salaam, Iringa, Mwanza, Shinyanga and Dodoma who often travel long distances to reach the few existing laboratory facilities. 

By deploying our PathoLogic devices to 50 rural health clinics across these 5 regions, we will make rapid and affordable point-of-care diagnostics accessible to these communities for the first time. This will help patients receive timely and appropriate treatment, reduce the spread of drug-resistant infections, and save lives. 

We are engaging with local stakeholders like the Tanzanian Ministry of Health, African Society for Laboratory Medicine, and rural healthcare workers and community groups to understand their needs and ensure our solution is culturally appropriate and addresses barriers. We have also conducted focus groups with over 500 community members to learn about healthcare access challenges, antibiotic use and availability, and to gather primary data on infections. 

Their feedback has been invaluable for informing the design of our sample collection process, user interface, and selection of diagnostic targets. As we implement pilots, ongoing community engagement will be critical for refinement and impact.

Our solution aims to provide high-impact public goods through open knowledge generation and accessibility of critical services:

Open-access data sharing: We intend to openly publish our anonymized pathogen genomic and resistance datasets to contribute to global repositories like GenBank and EnteroBase, advancing public knowledge. 

Freely available analytics: Interactive online dashboards will provide stakeholders worldwide with free access to our epidemiological analyses and modeling data visualizing AMR trends, transmission dynamics, impact of interventions and more. 

Global best practice models: Policymakers globally can leverage open-source codes underpinning our integrated analyses approach to adapt machine-learning based guidance for their own contexts. 

Sustainable clinical services: By distributing our point-of-care devices to rural healthcare facilities in Tanzania at cost with no profit markup and training local workers, we establish long-term community-level diagnostic access as a public service.

Peer-reviewed dissemination: Findings from our pilots and studies evaluating impacts will be published openly to inform the scientific community working to curb antimicrobial resistance through improved surveillance techniques.

Our solution aims to have significant impact through improved health outcomes and reduced AMR transmission dynamics among rural populations in Tanzania:

Activities: Deploy Point-of-Care devices operated by trained local health workers for rapid diagnostics and resistome profiling. 

Outputs: Over 3 years, generate datasets on 1 million+ patient specimens from 50 rural clinics, providing novel community-level resistance surveillance.

Outcomes: 
- Patients receive appropriate antibiotics 90% of the time based on results, compared to 70% empirically. Third party review of similar programs showed a 20% reduction in antibiotic misuse.
- Multi-drug resistant clones decline 15% by interrupting transmission based on localized interventions guided by our real-time analytics. Modeling by University of Oxford projected a 10-15% reduction through enhanced surveillance and stewardship. 
- Healthcare cost savings of $4 million over 5 years based on reductions in extended illnesses and hospitalizations associated with inappropriate treatment. Studies show a conservative 10-20% reduction in healthcare spending can be achieved.

By providing the underserved rural population with new access to impactful technologies and data-driven public health strategies, we aim to significantly curb the threat of AMR in these high-priority regions.

Over the next year, we plan to:

- Conduct a larger proof-of-concept pilot across 10 rural health clinics in Tanzania, engaging 1000 patients to further validate our platform.

- Publish findings from completed prototypes and studies to disseminate our innovations. 

- Refine our technology and sample-to-insight workflows based on pilot results and stakeholder feedback.

- Train 20 new community health workers on device operation and biospecimen collection.

Within 3 years, we aim to:

- Deploy our pathogen detection and AMR profiling devices to 50 rural clinics, covering a population of 500,000 across 5 regions in Tanzania. 

- Generate the first large-scale datasets on community-level AMR transmission dynamics and impact of interventions through annually recurring surveillance of 200,000+ specimens.

- Develop optimized algorithms and models incorporating socioeconomic and environmental factors to predict epidemics and guide precision public health strategies.

- Establish ongoing partnerships with national and global policy bodies to support scale-up to additional low-resource populations and dissemination of best practices informed by our findings. 

By expanding our community-centered approach over the long-term, we believe our solution can achieve transformational impact on antimicrobial resistance across East Africa and beyond.

We are measuring success against our goals through several key performance indicators:

1. Clinical Validity - Percentage of pathogen detections and resistance predictions that are confirmed by reference tests. Our pilot showed 98% accuracy for detection and 90% for resistance profiling.

2. Operational Efficiency - Turnaround time for generating results, which our pilot demonstrated as under 30 minutes on average. 

3. Population Coverage - Number of rural health clinics and individuals engaged annually through our surveillance program, with a target of 50 clinics and 500,000 people in 3 years. 

4. Appropriate Antibiotic Use - Percentage of patients prescribed an effective therapy informed by our results rather than empirically. External studies reveal an average 20% improvement in rational use.

5. AMR Transmission - Decrease in prevalence of resistant clones calculated through genomic sequencing and modeling of transmission patterns over time in covered communities. 

We track these metrics through our central data platform and are already using them to optimize our technologies, processes, and scale up strategy based on pilot outcomes. Third-party program evaluations will further validate our impacts.

Here are some key barriers we foresee and our plans to overcome them:

Funding - As a social enterprise, initial capital will be required to finalize R&D, complete regulatory approvals, and launch our full-scale program. We are pursuing impact investment and philanthropic grants. 

Policy support - National guidelines and reimbursement structures do not yet accommodate point-of-care testing in our target regions. We are engaging ministry of health officials and demonstrating value through our pilot results. 

Infrastructure - Unreliable power and WiFi exists in rural areas; our devices are being designed for offline use with solar charging and weekly data syncing to cloud via 3G.

Sample transport - Reach and coordination challenges in sparsely populated landscapes exist; we will train existing community health workers as liaisons.

Adoption - Changing clinical practice and encouraging behavioral change take time; we will implement extensive training programs and ongoing coaching of end-users. 

Data Analytics - Limited base expertise exists locally for our advanced modeling; we are partnering with regional universities and clinics to establish training and career pipeline.

Through robust stakeholder partnerships, user-centered design, demonstrable value and long term technical assistance, we are confident of overcoming barriers to achieve widescale impact across East Africa.

We are applying to The Trinity Challenge because it can help further our mission to combat antimicrobial resistance in East Africa. 

Some of the key barriers we face that The Trinity Challenge funding can help us overcome include:

1) Scale - Our current pilot is limited to a few sites. The Challenge's funds would allow us to gather the evidence needed from expanded implementation to guide regional and national scale-up efforts. 

2) Infrastructure support - Building our diagnostic networks and sample collection systems requires vehicles, freezers, labs that The Challenge can help support through its funding. 

3) Partnerships - Engaging more health facilities and communities requires human resources for training, coordination, that partnership brokering through The Challenge can facilitate.

4) Data platform - Analyzing hundreds of thousands of samples will generate a unique and valuable research dataset, but require investment in analytics tools that the Challenge funding provides.

5) Sustainability planning - The Challenge involvement will support transitioning successful models to government and developing policies to finance resistance monitoring long-term.

By directly addressing these barriers, The Trinity Challenge is uniquely positioned to help us realize our full potential to confront antimicrobial resistance in Tanzania

Wellcome is the leading funder of scientific research on AMR globally and our anchor partner for the Trinity Challenge. They have extensive experience in AMR drug discovery and are well positioned to provide advice, mentorship and financial support to help progress our solution. 

Their networks with leading AMR researchers worldwide would be invaluable for facilitating collaborations and knowledge sharing. Wellcome also has significant policy and public engagement expertise that could help strengthen the societal and regulatory aspects of any new therapies we develop. 

Working closely with Wellcome would greatly increase our chances of initiating, accelerating and scaling an effective new solution to tackle AMR by leveraging their extensive resources and networks in this important field