BioXcelerate AI, the health data science division of Edinburgh-based Optima Partners, took home the 2025 R&D 100 Professional Award for R&D Team of the Year at the awards gala in Scottsdale, Arizona.
BioXcelerate AI was formally launched in late 2023, founded by academics from Cambridge, Edinburgh, Imperial College, and Oxford. The team has since built a suite of proprietary tools, including PleioGraph, which analyzes complex biological data up to 100 times faster than existing colocalization methods, and the bioX Genetics Platform, a trusted research environment that cuts genetic variant detection time by 98% while maintaining 99% accuracy.
The platform combines AI-driven tools for colocalization analysis, fine-mapping, causal inference, and knowledge graphs to help pharmaceutical clients identify disease-associated risk genes and viable drug targets. Since its launch, bioXcelerate has doubled its blue-chip pharmaceutical client base.
The team
Under the leadership of Chris Foley, Ph.D., CEO, who built the early machine-learning architecture and guided the team’s first collaborations with global pharmaceutical partners, BioXcelerate AI’s core team includes:
- Zhana Kuncheva, Ph.D., Director of Health Data Science — Sets the scientific and strategic direction with expertise in statistical genetics, translational genomics, and biotech consulting.
- Soroosh Afyouni, Ph.D., Director of Health Data Science — Leads product development and day-to-day execution, building tools for causal inference, fine-mapping, and knowledge graphs.
- Daniel McCartney, Ph.D., Lead Bioinformatician — Drives scalable analysis pipelines and integration of multi-omic and clinical datasets for biomarker discovery and genetic risk prediction.
- Manju Dissanayake, Ph.D., Principal of Technology Innovation — Built the production-ready genomic analysis platform using cloud infrastructure across AWS and GCP.
- Alex Southgate, Ph.D., Senior Bioinformatics Engineer — Ensures workflows are scalable and reproducible through containerisation, CI/CD, and cloud deployment.
- Lily Andrews, Ph.D., Health Data Scientist — Specializes in genetic causal inference methods for target validation and statistical methods development.
- Andrew Donald, Director of Engineering — Oversees the engineering infrastructure that underpins the platform.
Foley, a former University of Cambridge research fellow and NIHR Fellow, originally built the machine-learning architecture that still guides the platform’s design. The team’s work spans collaborations with institutions including the University of Edinburgh, Harvard, MIT’s Broad Institute, and King’s College London.
