Science
Science does not stop at trying to understand disease. The work continues through development, production, and then is delivered as medicine to the people who need it. My areas of focus are drug discovery, genomics, computational biology, data science, and process development, which connect the path from idea to product. Together, they help answer: how do we build better treatments?
When lives are at stake
Science can involve working with some uncertainty, but when people face disease, the subject becomes personal. The thinking is then about whether the right treatment or technology for them already exists, or whether science can invent it in time. Workers on a mission, their experiments, their care, do not stop at one breakthrough; they will keep solving every next problem. Drug discovery and development matter to me because the work becomes more than a job when it can help keep saving lives.
From discovery to development
Drug discovery begins biological, by researching what is happening over the course of disease at the cellular and biomolecular levels. Genomic approaches can help identify the genes, pathways, and mechanisms involved, guided by the characteristic biomarkers found in patients. Computational biology can then help analyze molecular interactions, including how drug candidates bind to target proteins through computer simulation, before potential treatments are validated with assays.
Though these are key experiments for the research and development of new medicines, they are only part of the product development process. My background in chemical engineering, with a bioengineering emphasis, shaped how I think about drug discovery and development because chemical engineering does not stop at the small scale. The discovery needs to make it through development, the process needs to be improved, and the medicine needs to be produced at a scale large enough to supply the globe. It requires someone who can work in multi and interdisciplinary teams across R&D and communicate cross-functionally through development. I am interested in discovering and developing better treatments, while keeping in mind enough will need to be produced to serve patients worldwide.
Next-generation medicine
Computational biology, AI agents, and laboratory experiments together help us to work through big data and move ideas faster to accelerate discovery. I am interested in integrating computational and experimental approaches by using data to help guide and decide the most important experiments to pursue next. Together, we can bring modern treatments closer to reality by using smarter tools to build better solutions and improve outcomes for people.
Areas of focus
- Drug Discovery
- Genomics
- Computational Biology
- Data Science
- Process Development
- Bioprocess Development
- Translational Medicine
- Oncology
- Biotechnology
Looking forward
The future of medicine depends on our ability to integrate biological understanding, computational tools, experimental validation, and scaling up. I want to contribute to work that helps us understand disease, discover better therapies, and develop medicines that can reach more patients.
We do not stop for disease, and neither does science.