PredictRx

PredictRx is a machine learning algorithm that predicts antibiotic resistance patterns using patient data, empowering healthcare providers in LMICs to make informed treatment decisions, reduce antibiotic misuse, and combat antimicrobial resistance.

Velian Patrick is the CEO and Team Lead for our solution, overseeing the development and implementation of the antibiotic resistance prediction algorithm.

PredictRx addresses the critical challenge of antimicrobial resistance (AMR), specifically focusing on antibiotic resistance in bacteria, which poses a significant threat to global health, food security, and environmental sustainability. Currently, approximately 4.95 million people die each year due to AMR-related infections, with 1.27 million of these deaths directly attributable to antibiotic resistance. Without intervention, these numbers are projected to escalate, potentially reaching 10 million deaths annually by 2050.

The impact of AMR extends beyond human health, affecting animal health and welfare, food production, and economic stability. Low- and middle-income countries (LMICs) are particularly vulnerable, facing challenges such as limited access to effective antibiotics, inadequate surveillance systems, and poor sanitation and hygiene practices that contribute to the spread of resistant bacteria.

Community-level data on AMR in LMICs is sparse, leading to gaps in understanding transmission dynamics and effective intervention strategies. PredictRx aims to address these challenges by leveraging machine learning to predict antibiotic resistance patterns based on patient data. By providing healthcare providers with a tool to anticipate resistance patterns, PredictRx can guide more targeted treatment approaches, reduce antibiotic misuse, and ultimately mitigate the impact of AMR in communities worldwide.

PredictRx serves healthcare providers, including doctors, nurses, and pharmacists, who are responsible for prescribing and managing antibiotic treatments for patients. These healthcare professionals face the challenge of antibiotic resistance on a daily basis, as they strive to provide effective treatments while minimizing the risk of resistance development.

PredictRx addresses the needs of healthcare providers by providing them with a tool to predict antibiotic resistance patterns based on patient data. This empowers providers to make more informed treatment decisions, choosing the most appropriate antibiotics for each patient while reducing the risk of resistance.

To understand the needs of healthcare providers, we have engaged in ongoing discussions and collaborations with medical professionals and healthcare organizations. Through interviews, surveys, and feedback sessions, we have gathered insights into the challenges they face regarding antibiotic prescribing and resistance management. These insights have informed the development of PredictRx, ensuring that it meets the needs and expectations of its target audience.

PredictRx provides several public goods that benefit the well-being of the public:

1. Improved Antibiotic Prescribing: By predicting antibiotic resistance patterns, PredictRx helps healthcare providers make more informed antibiotic prescribing decisions. This can lead to better treatment outcomes for patients and reduce the risk of antibiotic resistance.

2. Enhanced Surveillance: PredictRx contributes to enhanced surveillance of antibiotic resistance at the community level. By analyzing patient data, the algorithm provides valuable insights into resistance patterns, helping to inform targeted interventions and public health policies.

3. Open Access: PredictRx is designed to be accessible to healthcare providers globally, under fair, reasonable, and non-discriminatory terms. The algorithm can be integrated into existing EHR systems, making it easy for providers to access and use the predictions as part of their regular workflow.

PredictRx provides a public good by improving antibiotic prescribing practices, enhancing surveillance efforts, and ensuring global access to its predictive capabilities.

PredictRx is expected to impact a significant number of individuals within the healthcare system:

1. Patients: PredictRx's impact will directly benefit patients with bacterial infections by improving treatment outcomes. It is estimated that over 20,000 patients per year will benefit from more appropriate antibiotic prescriptions, leading to faster recovery times and reduced healthcare costs.

2. Healthcare Providers: PredictRx will impact healthcare providers, including doctors, nurses, and pharmacists, by guiding them to make more informed antibiotic prescribing decisions. It is estimated that over 500 healthcare providers will use PredictRx, leading to improved prescribing practices and better patient outcomes.

3. Healthcare Facilities: The implementation of PredictRx in healthcare facilities will enhance their ability to combat antimicrobial resistance and improve patient care. Over 500 healthcare facilities are expected to adopt PredictRx, leading to improved surveillance and better management of antibiotic use.

PredictRx's impact will be felt across the healthcare system, benefiting patients, healthcare providers, and healthcare facilities alike.

Over the next year, we aim to scale PredictRx's impact by:

1. Increasing adoption: Expand implementation to an additional 20 healthcare facilities, reaching a total of 70 facilities.
2. Regional expansion: Extend coverage to two new regions, serving a total of five regions.
3. Partnership building: Establish partnerships with three healthcare networks and organizations to facilitate adoption.
4. Training programs: Conduct training programs for 500 healthcare providers on PredictRx's use and benefits.

Over the next three years, our scaling efforts will focus on:

1. Continued adoption growth: Expand implementation to 200 healthcare facilities, reaching a total of 270 facilities.
2. Global reach: Extend coverage to 15 regions, serving a total of 20 regions globally.
3. Advanced analytics: Enhance predictive accuracy through continuous data analysis and algorithm refinement.
4. Integration with stewardship programs: Collaborate with national and international antimicrobial stewardship programs to integrate PredictRx, amplifying its impact.
5. Impact assessment: Conduct regular assessments to measure the reduction in antibiotic misuse and antimicrobial resistance.

These strategic initiatives will contribute to a significant reduction in antibiotic misuse and antimicrobial resistance on a global scale.

We will measure success against our impact goals through several key indicators:

1. Adoption Rate: The percentage increase in the number of healthcare facilities using PredictRx compared to the previous year.
2. Patient Outcomes: Reduction in hospital readmission rates and length of stay for patients receiving antibiotics guided by PredictRx.
3. Antibiotic Misuse Reduction: Percentage decrease in inappropriate antibiotic prescriptions based on PredictRx recommendations.
4. Healthcare Provider Satisfaction: Surveys and feedback from healthcare providers on the usability and effectiveness of PredictRx in guiding antibiotic prescribing decisions.

We will use data analytics and feedback mechanisms within PredictRx to track these indicators regularly. For example, in our pilot implementation, we observed a 15% reduction in inappropriate antibiotic prescriptions based on PredictRx recommendations, demonstrating its effectiveness in reducing antibiotic misuse.

1. Financial Barriers: Limited funding may hinder our ability to scale PredictRx rapidly. To overcome this, we plan to seek additional funding through grants, partnerships, and potentially commercialization of the product in certain markets.

2. Technical Challenges: Ensuring interoperability with existing electronic health record systems and data security are key technical challenges. We will address these by collaborating with IT experts and healthcare institutions to customize the integration process and enhance data security measures.

3. Legal and Policy Hurdles: Adhering to regulatory requirements and obtaining necessary approvals for data use and algorithm deployment may pose challenges. We will navigate these by engaging legal counsel and working closely with regulatory bodies to ensure compliance.

4. Cultural and Educational Gaps: Resistance to change and lack of awareness about the benefits of PredictRx among healthcare providers could impede adoption. We will conduct targeted educational campaigns and training programs to overcome these cultural and educational barriers.

By proactively addressing these barriers, we aim to ensure the successful implementation and scalability of PredictRx over the next year and three years.

We are applying to The Trinity Challenge because it aligns closely with our mission to combat antimicrobial resistance (AMR) through innovative data-driven solutions. The Trinity Challenge provides a platform for us to showcase PredictRx, our machine learning algorithm for predicting antibiotic resistance patterns, and to access resources and support that can help us overcome key barriers in scaling our solution.

One of the main barriers we face is the lack of funding and resources to implement and scale PredictRx. The Trinity Challenge offers the opportunity to secure additional funding and connect with potential collaborators and partners who can help us scale our impact. 

The Trinity Challenge's network and resources can help us validate and refine our solution, ensuring that it meets the highest standards of effectiveness and reliability. Overall, The Trinity Challenge provides a unique opportunity for us to accelerate the development and deployment of PredictRx, ultimately leading to better outcomes for patients and healthcare providers worldwide.

We would like to collaborate with organizations such as the World Health Organization (WHO), the Centers for Disease Control and Prevention (CDC), and Médecins Sans Frontières (MSF) to initiate, accelerate, and scale PredictRx. These organizations have extensive experience and expertise in global health and antimicrobial resistance (AMR) and can provide valuable insights, resources, and networks to support our solution.

Collaborating with these organizations would help us access key stakeholders and decision-makers in the healthcare sector, ensuring that PredictRx is implemented in a way that maximizes its impact and reach. Additionally, these collaborations can help us validate and refine our solution, ensuring that it meets the highest standards of effectiveness and reliability. Overall, partnering with these organizations would enable us to accelerate the development and deployment of PredictRx, ultimately leading to better outcomes for patients and healthcare providers worldwide.