Swamy Vijayan

About Swamy Vijayan

Biotech entrepreneur broadly interested in methods to find medicines efficiently…

Experience

1. Chief Executive Officer

   Zafrens

   Jan 2022 — Present

   Zafrens exists to bring the lifesciences to the AI era using cutting edge engineering tools. The costs and pace of data generation in biology/chemistry lag behind our ability to process data by many, many orders of magnitude. We aim to bridge this gap by developing ultra-high throughput, ultra-high resolution approaches to studying cells, both at the single-cell level and in the context of cell-cell interactions in various co-cultures. Considering the quickest way to understand complex systems is to perturb them, we have also developed the ability to perturb single-cell and co-culture systems with extremely large libraries of perturbations to study their molecular and functional responses (eg, MHC-peptide-T cell interactions; APC-immune cell interactions; drug library - cell interactions; etc.). We have built a versatile platform that allows us to probe profound, complex questions by simply swapping the inputs to the system. To truly benefit from the volume, diverse types and resolution of data we generate, we are also pioneering novel causal inference models that connect specific features of the perturbations to the molecular and functional responses of cells. Because we use continually differentiable models, we are able to generate novel chemical matter that could have desired functional and molecular responses in cells (or vice-versa - given chemical structure our model can predict functional responses). Recent advances in single-cell sequencing analysis point to an ability to transpose features between cell types - which raises intriguing possibilities; given a vast collection of data on model cells and small sample set on patient cells, could one transpose the entire learning on model cells to different tissues in a patient?(eg, if we have 10 million compound perturbations on HeLa cells, and data on a 100 compound subset on a patients T cells, could the 10 million knowledge-set be transposed to the patient to design optimal, in-silico therapeutics?)

Skills

• Microfluidics
• Nanotechnology
• Microscopy
• Bioinformatics
• Sequencing
• Dna Sequencing
• Data Modeling
• Dna
• Biochemistry
• Surface Chemistry
• Semiconductor Fabrication
• Life Sciences
• Fluorescence
• Lifesciences
• Image Processing
• Chemistry
• Genomics
• Biotechnology
• Physics
• Assay Development
• Simulations
• Biophysics