SFL Science-as-AI Methodology

Founded in Science - Rooted in Data - Powered by AI

Predicting Immuno-dominant Epitopes in Allergens Using ML

Allergic diseases are the most widespread type of immune disorder in the world. Allergic reactions occur when serum immune system responses bind to allergens, using protein binding sites called epitopes.

SFL Scientific is working on leveraging the data we have to accelerate the process of epitope interaction mapping.

Digitizing the Drug Discovery Pipeline

Effective AI solutions discover and leverage patterns in data. We work with your teams to identify and execute on custom AI solutions for your workflows.

Traditional AI development focuses on technical results before business intelligence; our AI Discovery process mimics Drug Discovery.

Starting from a detailed understanding of your workflows, we prioritize high-ROI solutions that can be integrated into existing IT resources.


01 Observe - Workflows to identify AI candidates.
02 Audit - Operational data to identify ROI and time savings.
03 Design - Endpoints to integrate with your workflows.
04 Develop - POC models with real-world data to quantify impact.
05 Deploy - Custom AI to drive efficiencies.

Designing the Next COVID-19 Vaccine

Our team of interdisciplinary scientists is developing hyper-targeted AI solutions to address your pain points.

Our approach places your data at the center of the discovery process.

Our goal is to provide bench scientists with anticipatory intelligence to inform experiment design and expose unexpected connections.


Meet our Drug Discovery Team

Meet the Team

Annabel Romero, PhD

Director of Drug Discovery & Molecular Modeling
Ben Letson

Benjamin Letson, PhD

Director of Healthcare & Life Sciences
Chris Hayduk SFL Scientific Data Science AI

Chris Hayduk

Solutions Architect, Machine Learning

Brandon Muir

Director of AI Partnerships
Looking to Learn More?

Contact the Drug Discovery Team.

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