Selected Publications
Towards precision medicine using biochemically triggered cleavable conjugation
comprehensive classification of the intrinsic physicochemical differences found in pathological areas and their applications in drug delivery, prodrug activation, imaging, and theranostics for future personalised medicines.
Nature Communications ChemistryProgrammable multispecific polybodys for T cell engagement and checkpoint modulation enhancing solid tumor immunotherapy
Multispecifc polybodys achieve solid tumor inhibition and immune cell infiltration in mice solid tumor models.
Chemical Engineering JournalSeeing through collagen: integrative pro-regenerative corneal implants for clearer future
This review provides a comprehensive analysis of the current state and the future strategies to optimize collagen.
npj Regenerative MedicineGold nanoparticle transport across tumour-associated biological barriers: in vitro models, imaging, and quantification
Integrating insights from advanced in vitro modelling and cutting-edge detection strategies, this review highlights the current landscape and future directions for optimising the study of gold nanoparticle delivery across barriers in cancer nanomedicine.
Royal Society of ChemistryInference Sandbox
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The Mission
We believe that the future of oncology lies in the synergy between biological complexity and computational clarity.
Traditional drug discovery is often slowed by the "observation gap"—the delay between treatment and measurable outcome. Our lab is dedicated to closing that gap. By leveraging 3D spheroid models and XAI-validated neural networks, we provide researchers with real-time, non-invasive insights that were previously invisible.
Our goal is to transform every microscopy image into a rich data stream, accelerating the journey from the laboratory bench to the patient’s bedside.
50k+
Spheroids Analyzed12
Global Partnerships
Prof. Hirak Patra
Principal Investigator
Advanced Therapeutics in Oncology
Dr. Mark Chen
Lead AI
AI & Computer Vision
Dr Alexandru Chivu
Biological Lead
Oncology & 3D Cell Models
Mr Thomas Lester
Research technician
Optical Imaging
Bridging Biology and AI
Our study demonstrates that machine learning does not have to be a "black box." By proving that our models focus on actual necrotic fragmentation, we provide researchers with a tool that is as interpretable as it is powerful.